Before AI can deliver on its promised value, organisations must first examine their data. Simply collecting large volumes of information isn’t enough — data must be accurate, well-organised, and ready for analysis. Raw data often requires transformation into clean and enriched formats so AI can generate actionable insights and deliver personalised experiences that create tangible business value. 

With 32% of organisations in Singapore already using AI across a range of use cases, and 66% planning to implement it within the next 6-18 months, getting your data in AI-shape has never been more critical. 

Is your data ready to meet the challenges of AI, or is your business at risk of falling behind? 

What is data transformation and why does it matter for ASEAN?

Data transformation involves converting, structuring, and unifying data so it can be effectively used by a system. It’s essential for businesses that want to take the vast amounts of data they have access to and activate it to improve customer experiences, make smarter decisions, and increase operational efficiency. 

Businesses across ASEAN collect data from a variety of sources, including digital channels, customer support, and connected devices. However, this data is often fragmented across different systems, with the same customer appearing under different profiles in each, making it hard to see them as a single entity. This lack of cohesion means businesses can miss key insights and lose potential value. 

Overcoming disjointed data and building a unified customer profile is essential to realising the potential of AI across sales, service, marketing, and commerce — not only to increase efficiency in the back-office but also to unlock new value in customer-facing, front-office functions.

As Alvin Neo,  Chief Customer and Marketing Officer, FairPrice Group and Managing Director, NTUC Link explains in Unlocking Opportunity in the Data and AI Revolution: “Fundamentally, the foundation of AI is data, that is why a major priority for us is ensuring that our data is clean and well organised. This is because the full value of AI is achieved when you can use it at scale, and we can only safely use it at scale if we have that data foundation in place.”

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Data transformation offers a competitive edge for ASEAN

In an AI-driven world, data transformation is not just a technical task but a strategic imperative for businesses across ASEAN. In Singapore, 89% of businesses believe that AI will be somewhat or very critical across a range of use cases, including developing hyper-personalisation and identifying new sales opportunities. And having accurate and secure data is the foundation of AI success. 

As Minh (Martin) Tran, Global Sales Development Manager at FPT Software shares: “Integrating Einstein has streamlined our operations with predictive analytics. We can target the most promising prospect by combining AI with human expertise.”

Simply put, AI makes it possible for businesses to streamline processes, empowering teams to solve problems faster and deliver better customer experiences. 

Understanding types of data transformation

Data transformation can be broken down into several processes that ensure data is clean, structured, and ready for AI-powered systems. These processes are generally grouped into four key classifications: 

1. Data cleaning and preprocessing: This includes tasks such as imputation, outlier detection, data standardisation, and normalisation. Cleaning ensures that AI models work with accurate, high-quality data.
2. Data aggregation and summarisation: Data is grouped and summarised to enable analysis at higher levels, improving the clarity of insights generated by AI tools. Techniques like rolling up and pivot tables are common here.
3. Data derivation and enrichment: New data can be derived through feature engineering, while enrichment involves adding context to existing data, making AI more effective in delivering insights.
4. Data integration and transformation: Unifying data from different sources (merging, joining) and ensuring it flows correctly into AI systems is critical for maintaining data consistency and accuracy.

What tools can organisations use to implement data transformation?

Once you understand the ‘what’ and ‘why’ of data transformation, the next step is ‘how’. 

In Singapore, 96% of business leaders agree that a strong data strategy is crucial, yet only 30% report having one integrated across their business. 

Bridging this gap in data readiness is critical to unlocking the power of AI — and the right tools make it simpler and easier to do so.

As the only data platform native to the #1 AI CRM, Salesforce’s Data Cloud allows ASEAN businesses to unify data without moving or duplicating it, thanks to its zero-copy architecture. With over 200 out-of-the-box connectors, Data Cloud simplifies the process of activating data in real-time — minimising complexity, reducing costs, and lowering both security and data cleanliness risks. This provides businesses with a comprehensive, up-to-date 360-degree view of each customer.

MuleSoft complements Data Cloud by seamlessly connecting systems and integrating data across departments, unlocking even more value from existing data and extending Data Cloud’s capabilities. Together, they empower businesses to derive actionable insights and deliver personalised customer experiences efficiently.

With Mulesoft and Salesforce’s Data Cloud for Marketing, Lotus’s — a major retailer in Thailand and Malaysia — was able to unify its data, eliminating duplicate records and halving the overall volume. This not only streamlined the data but also enriched the remaining records, making them more valuable for activation. As a result, Lotus’s gained a comprehensive view of its 9 million customers that could be activated directly in the flow of work.  

Tools like Agentforce and Prompt Builder make it possible to automate tasks, personalise workflows, and surface insights, unlocking new opportunities for informed decision-making and operational efficiency. The key to unlocking trusted, relevant responses from AI lies in unified data. By integrating data across departments, AI agents deliver accurate recommendations, efficiently route cases to representatives when necessary, and ensure faster resolutions — enhancing customer satisfaction while allowing service teams to focus on higher-value tasks. 

For example, Lion Parcel unified customer data from Sales Cloud and Service Cloud with external sources including warehouse data, to create an integrated view of operations and customer interactions. By segmenting its customer database, Lion Parcel can identify issues based on customer tier and automatically route cases to specialised agents. This approach has led to a 73% reduction in case resolution times. Additionally, by integrating generative AI with Salesforce, AI-powered chatbots now answer 90% of WhatsApp queries, significantly reducing service times and allowing service representatives to focus on more complex tasks.

Data security is a top priority in data transformation

As AI becomes integral to business operations, the need for strong data security becomes even more pressing. Businesses are increasingly focused on security, governance, and ethics as they explore new AI use cases and prepare for future advancements.

72% of business leaders in Singapore cite privacy and security concerns as a barrier to purchasing AI, while 92% agree that trust is critical when partnering with an AI vendor. This highlights the growing need for solutions that not only deliver powerful AI capabilities but also prioritise data protection.

The Einstein Trust Layer provides a robust set of features and guardrails that protect the privacy and security of your data while improving the safety and accuracy of AI results. Key safeguards include Secure Data Retrieval, which securely grounds AI prompts in business data, maintaining permissions and access controls, and Data Mask, which prevents sensitive information from being exposed or used for training AI models. This means businesses can use AI to ground results in real-time data while keeping that data secure. These protections build confidence in AI by addressing concerns over privacy, security, and ethics — critical for fostering trust in AI solutions.

Towards a data-driven future

To ensure successful and secure AI adoption, businesses must consider the following:

• Data quality: Ensuring data is clean, consistent, harmonised and accurate is essential for maximising the potential of generative AI. While 74% of organisations in Singapore are concerned about AI output quality, grounding it in well-maintained business data significantly improves results. 
• Documentation and version control: Keeping track of changes and updates to data.
• Testing and validation: Regularly testing AI systems to ensure they deliver the desired outcomes.
• Efficiency and scalability: Ensuring the data infrastructure can handle growth. 82% of organisations in Singapore believe that a CRM’s ability to perform and scale is important – even critical – when partnering with a CRM vendor.
• Data governance: Implementing policies and procedures to manage data securely.

By following these best practices, businesses across ASEAN can bridge the data strategy gap and unlock AI’s full potential.

Victor Setya, Vice President of Data at Tiket notes that: “As you mature in your data journey, you want to have trust and accuracy in the data so you can make the right decisions. Then, it is about how you can actually use your data to drive a competitive advantage.”

This focus on data maturity is echoed across ASEAN, where forward-thinking organisations are adopting cloud-based solutions and leveraging AI to turn vast amounts of data into actionable insights

As Yeap Yan Han, Head of Marketing, GXBank affirms: “What I’m really excited about, and looking forward to as our operation scales up and the volume of data continues to grow, is being able to make sense of all these data signals and grow our audience from 10 segments to possibly hundreds. We will then be able to anticipate customers’ next actions and deliver increasingly personalised offers.”

AI’s continued evolution will see data playing a crucial role in helping businesses stay ahead of the curve. Cloud-based solutions, such as Salesforce’s Data Cloud, will be central to this transformation, enabling businesses to unify and process data across systems.

Building a strong foundation for AI success

Data transformation is the foundation for any successful AI implementation. 

Businesses that prioritise data quality, security, and a well-structured data strategy will lead the way in the AI-driven future. 

To support your data transformation journey, we’ve put together Unlocking Opportunity in the Data and AI Revolution guide. With insights from 14 ASEAN business leaders, you’ll discover how to drive AI innovation and personalised experiences with connected data. 

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• The 2024 Connectivity Benchmark Report: Key Trends Shaping APAC’s Digital Landscape
• AI Trends from Singapore and the World Reveal Keys to Success
• Meet Agentforce: A New Era of Humans with AI Agents

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In Singapore, 96% of business leaders feel their data holds untapped potential, yet many are struggling to translate this into meaningful business outcomes. 

To explore how ASEAN businesses are overcoming hurdles and blazing new trails for an AI-driven future, Salesforce gathered insights from hundreds of Singaporean analytics, IT, and business leaders. Their perspectives, alongside those from 10,000 global leaders, are featured in our State of Data and Analytics Report.

Here are key takeaways from Singapore’s leaders — including practical tips on how you can make the most of your data and seize the AI opportunity.

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Takeaway #1: Without trusted data, your AI can’t deliver

It’s no surprise that 9 in 10 analytics and IT decision-makers in Singapore agree that trustworthy data is more important than ever. Every AI use case — from predictive analytics to IT management — runs on data. But your AI solutions won’t produce the results you’re looking for if you aren’t working with quality, trusted data. Simply put: flawed data leads to flawed results.

Yet, only 59% of analytics and IT leaders in Singapore are fully confident in the accuracy of their data. This gap shows there’s still plenty of work to do, which is why improving data quality emerged as a top priority for many businesses in the region.

So, how do you make sure your data is “trustworthy”? As data volumes grow, what are the best practices to ensure quality and consistency? Here are a few things to ask yourself:

• Do you have a clear and consistent data collection and data entry process? 
• Has your data been cleaned and normalised?
• Is your data protected and secure? 
• Do you have a governance framework addressing all aspects of the data life cycle, including access and control, management, privacy, security, compliance and regulatory requirements? 
• Is the data fit for the purpose? Does it follow ethics and integrity expectations?

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Takeaway #2: Getting more value from your data is easier when your data and business strategies are aligned

Data generation is exploding worldwide, and ASEAN is no exception. The digital ecosystem in this region is expected to triple in size by 2030, jumping from US $300 billion to nearly US $1 trillion. Data usage per user in Southeast Asia is set to skyrocket from 9.2 GB per month in 2020 to 28.9 GB by 2025.

Amid all this growth, 98% of Singaporean business leaders agree that data and analytics improve decision-making. However, two major challenges are holding many back: the sheer volume of data and the time it takes to turn that data into insights.

Our survey found that 82% of analytics and IT leaders in Singapore say their organisations struggle to drive business priorities with so much data. Only 63% feel their data strategy is fully aligned with business goals, making it clear why their second-highest priority — after improving data quality — is aligning data strategies to better harness the volume for meaningful business outcomes.

Understanding your business objectives is crucial when planning your data strategy. Start by clearly defining your goals, then map out the specific data needed to achieve them. With high volumes of data, it’s even more important to be selective — focus on the data that will have the greatest impact, and ensure you have the right tools in place to leverage it effectively. This targeted approach helps to drive much-needed insights across the organisation and reduce data silos that impede collaboration and decision-making.

The results? Better financial performance, higher productivity, and a stronger competitive edge. Research from McKinsey Global Institute shows that data-driven companies are 23 times more likely to acquire customers, 6 times more likely to retain them, and 19 times more likely to be profitable.

Takeaway #3: Higher data maturity opens doors to growth

When an organisation is data mature, we mean it’s well advanced on its data transformation journey — using data to drive decisions, fuel innovation, and plan for the future. But according to our research, only 28% of Singaporean businesses describe their data maturity as best-in-class.

Why does this matter? Because data maturity brings clear rewards. McKinsey’s research shows that data-driven companies achieve goals faster and see at least 20% higher contributions to earnings before income taxes.

Singaporean IT and analytics leaders report that a well-developed data culture — where everyone has the insights needed to be data-driven — leads to outcomes like higher cost savings, better productivity, improved customer service, more innovation, and faster decision-making.

And as AI becomes more integral to business strategies, data maturity is also a key indicator of AI success. Globally, organisations with higher data maturity are twice as likely to have the quality data needed to use AI effectively and recognise the growth benefits that come with a well-executed AI strategy

Unified data is the foundation that enables AI — first predictive, then generative, and now agentic — to work smarter and more autonomously. Agentforce taps into this unified data to deliver automated, intelligent responses and actions across your business. For example, when a Service Agent is connected to your order management system, knowledge articles, policies, and purchase history in Service Cloud, it can autonomously handle refunds, exchanges, and inquiries — boosting customer satisfaction while freeing your team for higher-value tasks.

With the right data foundation, agents streamline processes and unlock growth by helping businesses scale efficiently, improve retention, and generate new revenue through cross-selling and loyalty-building initiatives. Humans with agents can transform business growth — but it all starts with data maturity.

AI and Data Transformation in Singapore

Businesses that thrive are the ones that adapt, and today, data transformation is one of the most important adaptations a company can make. With AI poised to be as pervasive as the internet, companies must be ready to unlock its potential — but great AI starts with great data.

Yet, 84% of Singaporean business leaders are worried about missing out on the opportunities that generative AI presents. With AI set to revolutionise industries, Singaporean businesses that focus on improving data maturity, strengthening governance, and aligning data strategies with business goals will be the ones best positioned to succeed in the AI era.

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• How To Build a Data Culture: What Leaders Need To Know
• 5 Key Behavioural Elements that Build Successful Data Cultures
• The 2024 Connectivity Benchmark Report: Key Trends Shaping APAC’s Digital Landscape

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Agentforce World Tour Jakarta kicked off with a special address by Bapak Aris Kurniawan, Director of Government Informatics Application Services Ministry of Communication and Informatics of the Republic of Indonesia. His address set the stage for an action-packed day of keynotes, live demos, and interactive workshops.

Fresh off the excitement of Dreamforce 2024, the Jakarta event highlighted how Agentforce is driving customer success, improving operational efficiency, and unlocking new growth opportunities for businesses across Southeast Asia.

Agentforce arrives in Jakarta: What AI was meant to be

In Jakarta, a new era of AI-driven business transformation took centre stage. Iman Muhammad, Salesforce’s Country Leader for Indonesia, introduced the audience to the power of AI agents, designed not to replace humans, but to work alongside them.

By handling routine and time-consuming tasks, Agentforce allows teams to focus on strategy and customer engagement. These AI agents don’t just automate tasks — they anticipate needs, make informed decisions, and adapt to complex workflows, all while driving efficiency and delivering smarter outcomes.

The audience got a glimpse into some early success stories, including Saks, where Agentforce is already helping deliver a high-touch, luxury experience for millions of customers  — a feat previously unthinkable. Saks deployed its first AI agent in just one week, and is set to give every shopper their own AI stylist and concierge, across any channel.

Local Trailblazers imagine the future with AI agents

It was inspiring to see Telin, one of Indonesia’s leading telecommunications companies, share its vision for how Agentforce could transform its customer service operations. Telin’s Chief Commercial Officer, Kharisma, emphasised the potential of AI to deepen customer insights and enhance productivity across the company’s CRM processes. 

“For quite a long time, we have been searching for a way to improve our productivity internally. We’ve been trying to get as many insights as we can to make better decisions and improve financial outcomes,” Kharisma explained. 

“Agentforce is a very impressive innovation coming from Salesforce, and we believe it presents a big opportunity for us to achieve this moving forward.”

Cipta Ciputra Harun, Director of Ciputra Group, highlighted the potential of AI to streamline sales operations by taking over routine tasks, such as following up on lower-priority leads, freeing their sales teams to focus on higher-quality prospects. 

“What we want to be able to do one day is have AI follow up on lower-rated leads to give our sales team back time and energy,” Harun explained.

Data Cloud is the backbone of AI agents

To deliver truly personalised and relevant experiences, AI agents need the right data. Siddharth Rastogi, Vice President of Salesforce ASEAN, explained how at the heart of the Salesforce Platform lies Data Cloud — a powerful tool that seamlessly unifies both structured and unstructured data to activate with Agentforce. 

With Data Cloud, companies can integrate data from platforms like Snowflake, Google Cloud, and AWS without the headache of complex migrations — thanks to the new Zero Copy Partner Network. This keeps data secure and makes every agent smarter and more responsive, able to act on customer information in real time.

In just one quarter, Data Cloud processed an astounding 767 trillion records. By transforming siloed data into unified customer profiles, Data Cloud powers Agentforce to deliver personalised experiences at scale, whether through automated marketing, proactive service, or tailored sales recommendations.

Humans with AI deliver effortless service

Customer service is one of the first areas where AI agents are driving meaningful change. While traditional chatbots can handle basic, repetitive tasks, they struggle when conversations become more complex or fall outside their pre-set parameters.

This is where Agentforce Service Agents truly shine — engaging in nuanced conversations, adapting on the fly, and responding to customer needs with a level of empathy and accuracy that elevates the overall service experience.

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AI and Agentforce for every industry

Each industry faces unique challenges, and Agentforce is built to solve them. In banking, AI agents are driving proactive financing to help customers secure better loan terms, while in retail, businesses are boosting sales with always-on concierge services that provide personalised shopping experiences. 

For manufacturing, Agentforce enhances operational efficiency by improving uptime through proactive maintenance, and in healthcare, AI agents match patients to the right doctors, leading to improved care and outcomes.

With over 100 new industry-specific AI prompts introduced, Agentforce is designed to tackle the diverse needs of each sector. Explore the new AI use case library to see the out-of-the-box solutions tailored to your industry.

Unlock productivity through connected work

In today’s fast-paced work environment, too much time is lost to busy work — endless meetings, chasing emails, and juggling apps. In fact, 41% of work is spent on low-value tasks, and 47% of workers struggle to find the information they need to be productive, switching between an average of 11+ apps just to get the job done.

Enter Slack. As a single operating system for work, Slack brings people, data, workflows, and now AI agents together, unlocking the full potential of Agentforce within the flow of work. By eliminating barriers like disjointed communications and fragmented data, teams with Slack can collaborate seamlessly and get back to what matters — delivering results.

At Agentforce World Tour Jakarta, audiences watched a compelling customer video from Grab, Southeast Asia’s leading super app, on how Slack is transforming its operations. 

“Before Slack, we faced issues of siloed communications, spread across different platforms. This caused disjointed conversations and slowed down decision-making,” says Daniel Foo, Head of Grabber Technology Solutions at Grab. Now, with Slack, Grab has saved hundreds of thousands of hours by streamlining their internal processes and automating tasks.

You can hear more from Quinny Lei, Head of Business IT Solutions, GTS at Grab, speaking at the Salesforce Innovation Day Broadcast.

Bringing Agentforce to life on the Campground

The Agentforce Campground gave attendees hands-on experience with AI tools, showcasing over 10 live demos to illustrate how businesses can solve real-world challenges with AI agents. Participants explored solutions for automating customer service, streamlining workflows, and improving decision-making — and even built 240+ agents themselves during the Build an Agent experience.

Didn’t get a chance to build your first agent at Agentforce World Tour Jakarta? Sign up for a virtual workshop to give it a try, with the help of Salesforce experts.

Looking ahead with AI and Agentforce

As the event came to a close and attendees gathered at the Campground, one thing was clear: Agentforce is set to transform how ASEAN Trailblazers operate.

Agentforce World Tour was just the beginning, but the real transformation starts now as you welcome Agentforce into your organisation, where it can unlock unlimited potential with your team.

What if your workforce had no limits?

It’s possible when humans with agents drive customer success together.

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• 16 (Human) AI Influencers You Need to Know
• Salesforce Report: Teams Tap AI and Data to Drive Revenue as Service Expectations Rise

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An AI chatbot is a computer program designed to simulate human-like conversation through text or voice. In contrast to older rules-based chatbots, which have been around for decades, AI chatbots are created by training large language models (LLMs) on vast datasets of human conversations and knowledge, which helps the chatbot to understand natural language and generate relevant, contextual responses. 

Here, you’ll discover how to clarify your needs, cut through the chatbot clutter, and find the best AI chatbot for the job.

What you’ll learn:

• The benefits of using AI chatbots
• How to pick the best chatbot
• The AI chatbot revolution

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The benefits of using AI chatbots

Thanks to AI chatbots, gone are the days of canned robotic responses, endless hold times, or making customers wait days for an email reply. Having always-on digital assistants available to deliver fast and personalised service is now the norm.

But chatbots don’t just benefit customers — they’re transformative for businesses, too. Every customer interaction is an opportunity for bots to uncover insights quickly and systematically, and potentially pinpoint ones you may have missed otherwise.

In an age where data is king, chatbots can collect and analyse conversational data from direct interactions with your customers. What are their biggest pain points? What questions keep coming up? With that knowledge, you can fine-tune your products and deliver even better service and support for your customers. (Back to top)

How to pick the best AI chatbot

With new chatbot options constantly hitting the market and offering varying specialties, it’s important to sort through the clutter and determine what is the best AI chatbot for your business. Understanding your specific needs, comparing costs, exploring customisation options, utilising your company’s existing data, and weighing functionality are all important factors to consider when deciding which AI chatbot to use.

To get started, consider these questions to pick the best AI chatbot for your business:

1. What are your goals?

There are specialised chatbots for everything from customer service to sales to marketing. So, the first step is to identify how a chatbot will help you accomplish your business goals. “What is the business outcome you want? For example, reduce cost, increase sales, or minimise customer service volume?” said Aron Kale, director of product management on the Salesforce AI team. “Getting really clear on what you want out of your chatbot is an important first step.”

For example, if providing better, more efficient customer service is your goal, prioritise chatbots that are adept at resolving common customer queries. Or, if automating repetitive internal tasks is the priority, look for chatbots that will integrate with existing systems and can handle multi-step workflows. If you’re focused on finding a solution to help increase sales and drive more conversions, find an AI assistant that can do things like make personalised customer recommendations and manage transactions. 

A broader view is also beneficial to consider the ways an AI chatbot could make a bigger long-term impact. Are there downstream key performance indicators that your AI chatbot could affect?

For example, an HR chatbot could improve employee productivity and engagement by providing around-the-clock employee support, answering questions about company benefits, or sending automated reminders for project deadlines. A sales chatbot might boost conversion rates and lower customer acquisition costs by helping sales teams zero in on the highest-quality prospects. Or a customer service chatbot can improve satisfaction, loyalty, and retention metrics by providing personalised customer assistance. 

Whatever your goals are, it’s important to understand the varied abilities of the different AI chatbot solutions on the market. Chatbots run the gamut, from those that are purely question-and-answer solutions to tools that can resolve issues independently from start to finish. Map out the ideal level of conversational complexity, task automation, language support, and human-AI interaction for your business.

2. Where does your data live?

One of the most important factors to consider when picking the best AI chatbot for your business is access to your data. How easily the tool can tap into your company’s own data can mean the difference between a richly personalised output and one that’s generic and unhelpful. 

“Think about it in terms of what your human workers need in order to do their jobs well. Those are the same things your chatbot needs,” Kale explained. “So if you want your chatbot to focus on customer service issues, your chatbot needs to know your policies and look up an order status. Which you can pull in through tools like Data Cloud and MuleSoft.”

Think about the wealth of information contained in your company’s customer records, product information, service histories, internal policies, prospective customer data, and more. This data is a goldmine of insights, but it’s often spread across siloed databases, CRM software, conversation histories, and document repositories. Instead of giving generic responses, an AI chatbot that can access, understand, and seamlessly use this data can provide actionable answers that are specific to your business.

Let’s say that you run an online sports apparel store and a new customer asks the chatbot, “When will my order arrive?” A basic chatbot might reply with a standard line like “Orders typically ship in 3-5 business days.”

In contrast, a chatbot with access to your order management system would be able to respond in a much more personalised way: “Your order #913 for a Sacramento Kings jersey shipped yesterday via UPS. It’s expected to arrive this Thursday.” This kind of interaction goes a long way toward building brand loyalty, and the customer data needed to enable it likely already resides within your existing systems. 

A data-connected chatbot can also work wonders for your HR team. A chatbot that can tell employees exactly how many vacation days they have left or explain retirement plans based on their personal file makes for a great employee experience. And in sales, it can recommend products that complement a customer’s past purchases. In short, an AI chatbot that connects seamlessly to your company data is a true expert in your business, not just a generic assistant.

When comparing chatbots, understand how different solutions connect to various data sources. Can it integrate with common systems like Salesforce, SAP, or Microsoft Dynamics? Does it support APIs to link to custom databases? How does it handle data security? The best chatbot for your business is the one that not only understands natural language, but also transforms your data into an important asset that can build lasting brand loyalty. 

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3. What resources do you need to get going?

As you evaluate different chatbot solutions, it’s important to have realistic expectations around technical expertise, budget, time to invest in learning, and what the AI can and can’t do right out of the box. How easy it is to integrate into your existing system should be a consideration.

For example, is it a low- or no-code option that needs minimal training to get up and running? What level of technical skill is required for customisations or updates? Are there additional costs for scaling or advanced functionality down the road? Getting a strong handle on the real human effort and total cost of ownership needed to get the most out of your chatbot is key.

Finally, consider what internal data your chatbot needs to be trained on to be effective across your marketing, service, sales, and IT teams. Uniting all your structured and unstructured data under one roof is the best way to get the most out of it, and making that data available through a tool like Agentforce which is a proactive, autonomous application that provides specialised, always-on support to employees or customers.

And if this big, exciting new world of AI is all a bit overwhelming, it’s important to know that you can start small and build up. “It’s really possible to start small and really simple, with things like Q&A and knowledge articles,” Kale said. “It doesn’t have to integrate to 50 things right away — you can add use cases and expand it to meet different use cases over time.” (Back to top)

The AI chatbot revolution

As natural language processing capabilities continue to advance, we can expect these virtual assistants to become even more humanlike and intuitive. The pace of AI innovation will continue to pick up speed, making now the best time to learn these tools, Kale said. 

“The space is rapidly evolving. We’re seeing so much innovation, and businesses are seeing real value like never before,” he said. “It’s going to keep getting faster and faster, better and better. Start learning and getting hands-on now so that you’re well prepared as the technology evolves.” (Back to top)

Cassidy Myers-Sims contributed to this blog article.

The post 3 Easy Steps to Pick the Best AI Chatbot for Your Business appeared first on Salesforce.

The number of voices sharing insights on AI is growing, and as visions for the future increasingly become our reality, this momentum shows no signs of slowing down. As AI reshapes industries, including yours, you need to stay in the know by following a handful of individuals playing key roles in the revolution.

The people influencing AI aren’t just those building the technology. This list includes individuals from academia and technology, writers chronicling the AI revolution, and those hoping to shape ethics and regulation. 

Here are sixteen AI influencers from around the globe you should follow, including leaders from Australia, Singapore, and India.

• APAC Voices
• Academia
• Technology
• The Chroniclers
• Ethics/Regulations

APAC Voices

Who: Ayesha Khanna

What she does: 

• Co-founder and CEO, Addo AI, headquartered in Singapore
• Founder, 21st Century Girls
• Served on several Singapore government boards
• Author of “Straight Through Processing” and the upcoming “U+AI”

Social media presence: LinkedIn (56,241 followers; LI Top Voice); X (11,371 followers)

Why you should know Ayesha: Khanna is a visionary force in the AI space, helping governments and corporations use AI to drive innovation and growth. As co-founder and CEO of Addo AI, she’s reshaping industries with her deep expertise in AI, smart cities, fintech, and the metaverse. Named one of Southeast Asia’s groundbreaking female entrepreneurs by Forbes and included in the Top 50 Asia Women Tech Leaders for 2024, Ayesha is also a passionate advocate for women in tech. Through her charity, 21st Century Girls, she empowered thousands of young girls with coding and AI skills over 10 years, preparing the next generation for the future of technology. Her influence stretches far, with board roles at Johnson Controls, NEOM Tonomous, and L’Oreal’s Scientific Advisory Board, making her a key player in both corporate and social impact arenas.

Insight: “Technology will never replace humans, as there will always be a need for people to be involved in technology to maximise its potential. AI, for one thing, is fundamentally dependent on good-quality data, and will need people who understand data or can create a ‘golden source of truth’ (a single source of truth from which data is constructed), which is critical to good data governance.” — Khanna, on Tatler

Who: Amanda Johnstone

What she does:

• Founding CEO and High Technology Communicator, Transhuman
• Co-founder and CEO, Be A Looper
• Seed investor and mentor, Tech Ready Women Academy

Social media presence: LinkedIn (15,868 followers; LI Top Voice); X (3,973 followers)

Why you should know Amanda: As one of Australia’s most recognised AI technologists, Johnstone has earned global acclaim for her work in social impact technology. Named a Next Generation Leader by TIME and awarded Start-up Executive of the Year by The CEO Magazine, she has combined her passion for tech with a deep commitment to mental health. Johnstone founded Be A Looper, an AI-powered app that uses EmotionAI to support individuals struggling with mental health challenges, a venture inspired by her personal experiences with suicide prevention. Over her 20-year career, she has advised organisations such as Commonwealth Bank, Optus, and the Australian Digital Health Agency, while also building Talk Nerdy to Me, a social audio channel that engages over 300,000 subscribers.

Insight: “Technology is going to make us more human again. We’ve gone through this phase where we’ve been hiding behind the internet and creating more work for ourselves, and I really am looking forward to us outsourcing that to personal digital assistants so we can spend more eyeball time with each other.” – Amanda, on YouTube

Who: Mark van Rijmenam

What he does:

• On-demand keynote speaker, The Digital Speaker, based in Australia
• Founder and strategic futurist, Futurwise
• Founder, Datafloq
• Author of five books, including “Step Into the Metaverse” and “Future Visions”

Social media presence: LinkedIn (42,041 followers; LI Top Voice); X (6,164 followers)

Why you should know Mark: A globally recognised futurist, van Rijmenam helps businesses and governments adopt emerging technologies like AI, blockchain, and quantum computing. As founder of Datafloq and Futurwise, and with a PhD focused on big data and AI, Mark has delivered pioneering TEDx talks, including the world’s first in virtual reality and a 2023 talk featuring his digital deepfake. Known as The Digital Speaker, he has also created an app offering 24/7 access to his AI-powered digital twin, providing personalised insights via text, audio, and video in 28 languages, helping organisations navigate the future on-demand.

Insight: “The convergence of AI and AR will enhance experiences via intelligent insights and interactions in augmented environments. It holds vast potential for training, assistance and data visualisation for enterprises. As AR and AI synergise, they promise to redefine information sharing and use at work.” – Mark, on The Digital Speaker

Who: Nikhil Malhotra

What he does: 

• Chief Innovation Officer, Tech Mahindra, based in India
• Creator, Maker’s Lab
• AI Fellow, World Economic Forum 

Social media presence: LinkedIn (17,945 followers); X (1,618 followers)

Why you should know Nikhil: Malhotra is the visionary behind Maker’s Lab, Tech Mahindra’s R&D hub dedicated to advancing AI, machine learning, robotics, and quantum computing. With decades of experience, he leads the company’s innovation efforts, including the creation of India’s large language model, Project Indus. As a World Economic Forum AI Fellow, Malhotra champions responsible AI and quantum ethics, guiding organisations through the complexities of emerging technologies. His leadership has earned him numerous accolades, including the Innovation Congress awards in 2020 and 2021. A key part of his vision is enabling machines to communicate in India’s diverse local dialects, addressing the linguistic richness of a country with over 1,645 dialects.

Insight: “Public-private partnerships are pivotal in India’s LLM journey, with the government and industry working together to develop and deploy AI technologies for public services. For instance, the Indian government’s collaboration to develop AI solutions for agriculture is a prime example of how LLMs can be leveraged to address critical societal challenges.” – Nikhil, on timestech.in

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The Evolution of AI in CRM

Businesses are moving up the AI maturity curve at a rapid pace. See how they’re progressing in the Trends in AI for CRM report.

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Academia

Who: Ethan Mollick

What he does: 

• Associate professor at the Wharton School, innovation and entrepreneurship
• Author of “Co-intelligence: Living and Working With AI”
• Founder, “One Useful Thing” newsletter

Social media presence: LinkedIn (111,000 followers); X (211,000 followers)

Why you should know Ethan: Dubbed the “AI whisperer,” Mollick advises some of the most prominent people building, using, defining, and regulating AI, including Meta, OpenAI, Anthropic, the White House, and private industry. His primary area of focus deals with the impact of AI on work and everyday life. He is frequently quoted as an AI expert in major publications like the New York Times, Wall Street Journal, Reason, Fast Company, and Politico, and he publishes AI research on topics including the effects of AI on knowledge worker productivity, and using AI as a classroom teaching tool. He is a featured author in many other publications including Harvard Business Review. 

Insight: “Smaller AI models that can run on your phone are available and will soon connect to larger networks of AIs to solve hard problems. And the nature of our interaction with AIs themselves might be changing, as agents and AI devices start to spread.” — Mollick, writing in his newsletter

Who: Ayanna Howard

What she does:

• Roboticist, entrepreneur, educator
• Board member for Black in AI
• Dean of the College of Engineering at Ohio State University
• Founder and president of the board of directors of Zyrobotics, an award-winning company that develops mobile therapy and educational products for children with special needs

Social media presence: LinkedIn (30,290 followers; LI Top Voice); X (7,682 followers)

Why you should know Ayanna: Few things are more synonymous with “the future” than AI and robotics. Howard is a leading voice on both. A distinguished roboticist who leads Ohio State University’s engineering department, she’s also a member of the Advisory Board for Black In AI, an organisation focused on increasing the inclusion and presence of Black people in AI. Additionally, Howard founded Zyrobotics, an award-winning organisation that develops AI-powered tools for special-needs children. 

Insight: “If we are not careful, we might be living another 1957 Sputnik moment. Today, with nearly every aspect of life evolving to include AI, the U.S. cannot afford to sit back and wait for an AI-based crisis to hit. The U.S. must make bold investments in growing the AI talent pool to help protect democracy, citizen’s quality of life, and the overall health of the nation.” — Howard, in testimony to the U.S. Joint Economic Committee

Who: Dr. Fei-Fei Li

What she does: 

• AI researcher & professor, Stanford 
• Co-director, Stanford Human-Centred AI Institute
• Author, “The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI” 
• Co-founder, Chair, AI4ALL

Social media presence: LinkedIn (35,320 followers); X (458,800 followers)

Why you should know Fei-Fei: The “godmother of AI” has, among other things, published more than 300 scientific articles in top journals. She is the inventor of ImageNet, a database of annotated images that was a catalyst for today’s AI. What started as an idea to “map out the entire world of objects” led to an annual competition to see what algorithms could identify objects in the dataset’s images with the lowest error rate. Competition winners went on to work across tech from Google to Huawei. That’s partly why Wired called her “one of a tiny group of scientists … who are responsible for AI’s recent remarkable advances.” She is focused on what she calls “human-centred AI” that works to support scientific breakthroughs and advocates for peoples’ role alongside AI in the future. 

Insight: “The public sector is now significantly lagging in resources and talent compared to that of industry. This will have profound consequences because industry is focused on developing technology that is profit-driven, whereas public-sector AI goals are focused on creating public good.” — Li, to the Washington Post

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What to read next

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Technology

Who: Yann LeCun

What he does: 

• VP & Chief AI Scientist at Meta 
• Professor of computer science, data science, and neural science at NYU
• Professor, researcher, and R&D manager in AI, machine learning, deep learning, computer vision, intelligent data analysis, data mining, data compression, digital library systems, and robotics.

Social media presence: LinkedIn (709,155 followers); X (723,400 followers)

Why you should know Yann: Often called one of the godfathers of AI, along with Geoffrey Hinton and Yoshua Bengio, LeCun was a co-recipient of the 2018 Turing Award, which recognises major contributions to computer science (think of it as the Nobel Prize for computing). A highly distinguished pioneer in the field, LeCun was named a Chevalier in the French Legion of Honour in 2023 by French President Emmanuel Macron, and received the 2024 Global Swiss AI Award at the WEF at Davos. He is widely credited for advancing convolutional neural networks, which are deep-learning networks used for image classification and object recognition tasks. He has also published or co-published dozens of papers on AI, machine learning, robotics, computer vision, and image compression in the last two years alone.

Insight: “We can make humanity smarter with AI. AI, basically, will amplify human intelligence. It’s as if every one of us will have a staff of smart AI assistants. They might be smarter than us. They’ll do our bidding, perhaps execute a task in ways that are much better than we could do ourselves.” — LeCun, on the Lex Fridman Podcast

Who: Clara Shih 

What she does: CEO of Salesforce AI

Social media presence: LinkedIn (659,000 followers, top voice); X (24,000 followers)

Why you should know Clara: In addition to leading AI efforts across Salesforce, Shih has been a powerful advocate for using only trusted data and ethical processes in AI. She is a frequent speaker at major AI events including ones hosted by the Milken Institute, the FCC and Nvidia, and she hosts a podcast, Ask More of AI, in which she conducts in-depth interviews with leading AI entrepreneurs, investors, and creatives. She was named one of Time magazine’s 100 most influential people in AI in 2023. 

Insight: “I feel a tremendous sense of personal responsibility toward creating AI that is trusted … AI is going to be transformational for jobs, the way the internet was. I do have a healthy level of concern about it, but I’m an action-oriented person, so being in this role gives me a great platform to use to educate others, including members of Congress, CEOs and our customers.” — Shih, to the New York Times

Who: Reid Hoffman 

What he does: 

• Strategic partner, Greylock Ventures
• Co-founder, Inflection AI
• Author, Long Reids newsletter
• Co-founder, LinkedIn
• Many board roles

Social media presence: LinkedIn (2.6 million followers) X (710,000 followers)

Why you should know Reid: Hoffman has a deep, multi-pronged involvement in AI. He invests in AI startups (he was a founding investor of OpenAI), advocates for using AI to improve education and healthcare, and is a prolific speaker and author. As an uber- successful entrepreneur, he is one of tech’s most influential proponents of AI. His observations about the promise and peril of AI are helping shape the conversation. Case in point: his mind-bending interview with an AI version of himself demonstrated the awesome possibilities of the technology, and a book, Impromptu: Amplifying Our Humanity Through AI, which he wrote with GPT-4.  

Insight: “One thing that’s certain in the next five-to-ten years is that we are going to have agents everywhere, doing all kinds of things for us through all kinds of interactions. There will be agents for groups, agents for companies, and many other types. And the most natural thing when you’re doing engineering is to get IQ correct. But one of the things that’s really essential for people is how we bring EQ (emotional quotient) into it.” — Hoffman, on McKinsey’s On the Edge podcast

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The Chroniclers

Who: Rowan Cheung

What he does: Founder of The Rundown AI, one of the largest AI newsletters 

Social media presence: LinkedIn (36,000 followers); X (512,000 followers)

Why you should know Rowan: AI email newsletters have sprung up everywhere over the last year or two. Rowan Cheung’s daily publication, The Rundown AI, is one of the fastest-growing, currently boasting more than 600,000 subscribers. His newsletter covers AI news, spotlights AI tools, and offers step-by-step guides for implementing AI workflows. He also recently launched The Rundown University, a learning community with one-on-one AI support and expert-led workshops. In addition to The Rundown, Cheung has built a following of more than 500,000 on X, where he breaks AI news and shares tips for using AI tools. 

Insight: “We’re in the early innings, but especially as capabilities continue to increase, there will be a massive gap between early adopters who spend time testing and have a real grasp of everything possible, and those who just try ChatGPT once and never again. If you’re reading this, you’re still early. Start now or you’ll be playing catch-up in a year’s time.” — Cheung, on X

Who: Karen Hao

What she does: 

• Contributing writer, The Atlantic  
• Lead designer, AI Spotlight Series at the Pulitzer Centre
• Author of an upcoming book on OpenAI 

Social media presence: LinkedIn (20,000 followers)  X (61,000 followers) 

Why you should know Karen: Hao has been explaining AI since at least 2018. That year, she published a flowchart in MIT Technology Review called “What is AI?” which was later exhibited as an installation in the Museum of Applied Arts in Vienna. She has a uniquely diverse set of skills and interests that make her work a must-read for anyone following AI. With a degree in mechanical engineering from MIT, she’s as comfortable getting into the weeds as she is writing about the human aspects of technological progress, the poor treatment of African data annotators, and the outsized water consumption of AI data centres.

Insight: “A big question looms over generative AI: what really is its impact on the environment? I spent months investigating a single campus of … data centres in the Arizona desert — designated in part for OpenAI — in an attempt to find out. The process underscored just how little visibility we have into basic information, such as the water and energy consumption of these silicon monstrosities, which are now being built at an unprecedented rate, including in the desert.” — Hao, in a LinkedIn post

Who: Zain Kahn 

What he does: Co-founder and CEO, Superhuman newsletter 

Social media presence: LinkedIn (916,000 followers, Top Voice); X (517,000 followers)  

Why you should know Zain: He is the primary writer of the fast-growing AI newsletter, Superhuman. Like other newsletters, it summarises and analyses AI news, but what makes it stand out is its practicality for business users, focusing on how to use AI at work. In each newsletter, he includes a “prompt of the day,” a regularly updated list of best AI productivity tools, and a cool section on AI-generated images with the prompt used to create them. He regularly posts popular AI tips on LinkedIn. A recent one described how ChatGPT can create any Excel formula using natural language. And he uses AI to run his newsletter. It summarises dense papers, generates ideas, and writes full email drafts.

Insight: “We live in strange times. People both hate their jobs and the technology that can replace the worst parts of their jobs.” — Kahn, on X

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Ethics/Regulations

Who: Kay Firth-Butterfield 

What she does: CEO of Good Tech Advisory, which helps companies mitigate AI risks 

Social media presence: LinkedIn (22,000 followers); X (8,900 followers) 

Why you should know Kay: Firth-Butterfield is one of the world’s leading experts on AI governance. In 2014, she became the world’s first chief AI ethics officer, and was formerly the inaugural Head of AI at the World Economic Forum. She currently serves on the WEF’s Global Future Council on AI and AI Governance Alliance, and is a key voice for safe and equitable AI. In 2023, she received a Time100 Impact Award for her work in shaping responsible AI governance. 

Insight: “If we are to succeed in creating better economic prospects for all with AI, we have to start by doing better with data. About 3 billion people cannot access the internet … [and] billions more have not created a sufficiently large data footprint for their contributions to be evaluated by generative AI without very precise prompts.” — Butterfield, in her Time100 Impact Award speech

Who: Tristan Harris 

What he does: 

• Co-founder, Centre for Humane Technology 
• Host, Your Undivided Attention podcast

Social media presence: LinkedIn (49,000 followers); X (199,000 followers) 

Why you should know Tristan: He’s been sounding the alarm about tech’s harms since at least 2013, with a viral presentation about addictive social media. That sparked TED talks, a 60 Minutes interview, the documentary The Social Dilemma, and the nonprofit Centre for Humane Technology. The latter educates and provides resources to individuals, tech companies, and policymakers to mitigate the negative impact of social media and AI. He has testified to Congress multiple times on how algorithms are manipulated to influence choices and keep users engaged. He has advocated for “a humane digital democratic infrastructure” to help the U.S. mitigate tech’s risks. However, there is no federal regulation, yet, to tackle these problems. 

Insight: “There’s a 1,000-to-one gap between the collective resources going into increasing AI capabilities versus those that are invested in AI safety …. If we spend trillions of dollars on increasing AI’s capabilities, shouldn’t we be spending 5% of that on upgrading its governance?” Harris, at the AI for Good Global Summit

Who: Joy Buolamwini

What she does:

• Founder, The Algorithmic Justice League
• Computer scientist, digital activist
• Author, Unmasking AI

Social media presence: LinkedIn (92,362 followers); X (98,000 followers) 

Why you should know Joy: Buolamwini holds a PhD in Media Arts & Sciences from MIT, is the bestselling author of Unmasking AI, and is the founder of The Algorithmic Justice League, an organisation that combines art and research to illuminate the social implications and harms of AI. A self-proclaimed “poet of code,” she breaks down technical jargon and uses storytelling and creativity to humanise AI by teaching people about both the costs and possibilities of technology. Buolamwini is also featured in an award-winning film centred on her push to pass first-ever legislation to govern algorithmic bias, and was invited to join a closed-door roundtable discussion with President Biden last year. She’s undoubtedly helping shape ethical AI policy at every level of discourse.

Insight: “One of the challenges when you have such large data sets is knowing what’s even in those data sets in the first place. One of the [alternative] approaches is actually having smaller models where you can actually trace the data providence, so you have a better sense of what’s gone into these systems.” — Buolamwini, on the Ask More of AI podcast

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Trends in AI

AI doesn’t sit still — explore how businesses are evolving their AI strategies in the Trends in AI for CRM report.

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The post 16 (Human) AI Influencers You Need to Know appeared first on Salesforce.

Digital transformation isn’t just a trend. It’s a core shift to the business landscape, with IT leaders refining their strategies, headcounts and budgets to cater to growing customer expectations and project demands. The 2024 Connectivity Benchmark Report sheds light on the state of digital transformation worldwide, with the latest trends in AI, integration, automation and API management. So how do businesses in the APAC region measfure up in the evolving digital landscape?

IT leaders are optimistic about AI

The report reveals that 88% of organisations in APAC are already using AI, and adoption is continuing to grow. IT leaders in the region foresee an 89% increase in their usage of Large Language Models (LLMs) over the next three years, exceeding the 69% increase expected globally. Moreover, 86% are confident that AI will increase developer productivity at their organisations in that timeframe.

This optimism is a good thing, considering they’re simultaneously reporting a 39% increase in IT requests. AI will play an essential role in sustaining productivity under these demands, helping IT teams to manage growing workloads and expectations both efficiently and cost-effectively.

The trends shaping IT

A pulse check on the priorities, challenges and strategic direction for IT leaders in the age of AI.

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Organisations need to get their data ready for AI

Despite the optimistic outlook, 69% of APAC IT leaders say their organisation is ill-equipped to harmonise data systems to fully leverage AI, with 82% pointing the finger at data silos as hindering digital transformation efforts. While this figure is lower than the 81% global average, organisations across APAC still have a way to go to break down silos and better integrate data across the business. 

Integration hurdles are blamed by IT leaders for stalling digital transformation for 82% of APAC organisations. Kurt Anderson, Managing Director and API Transformation Leader at Deloitte Consulting LLP explains, “A lack of integration is the top barrier to adopting emerging technologies, especially AI. And as demand grows for seamless, personalised customer experiences, the interoperability of systems is crucial for harnessing the full potential of data, AI, and automation. That’s why integration should be the cornerstone of every IT leader’s digital transformation efforts in 2024.”

The potential of AI is limited only by the data that organisations can connect it to, and the outcomes they can drive from it. The report shows that IT leaders across APAC are increasingly aware of these integration and automation challenges, and underscores the need for a robust data strategy, with a focus on data currency, reuse and access.

IT teams are under pressure, but workflow automation can help

With 98% of APAC IT teams struggling to integrate efficiently, workflow automation emerges as a solution. Robotic Process Automation can drive efficiency and reduce the workload on IT teams. As automation is demanded across businesses, IT often plays a gatekeeper role, but workflow automation permits other teams to self-serve. The global investment in RPA is now 31%, up significantly from 13% in 2021, as IT teams realise its potential.

Singapore Institute of Management (SIM) underwent its digital transformation with Salesforce and MuleSoft, integrating multiple back-end systems to streamline the end-to-end experience for its learners and administrators. Learners can now access courses with a single sign-on and automated processes encourage self-service and more efficient case management.  

APIs become a strategic lever for growth

APIs are now a staple in the digital ecosystem, with 99% of organisations using them to streamline data access and fuel growth. In APAC APIs and API-related offerings contribute to 33% of all revenue. Furthermore, APIs have contributed to increased revenue for 41% of APAC respondents and cut operational costs for 27%.

M1, Singapore’s most dynamic communications company, found its legacy on-premise API gateway was too labour-intensive and slowed down the delivery of new offerings. Supported by MuleSoft Professional Services, it migrated to a more agile solution in just 9 months and is now completing 13% more projects a year through API reuse, while saving 15 man-days per project. 

“I’m really excited about the scalability we have with MuleSoft. In a fast-paced industry, we now have the confidence that we can stay ahead of the game with a future-proofed environment and delight our customers as we grow our business,” says Chiam Chee Kong, Deputy Head of Software Engineering & Architecture at M1.

With outlets in Thailand and Malaysia, popular retail brand Lotus’s chose Salesforce and MuleSoft to unify its systems and data so it can provide more personalised and streamlined customer experiences. MuleSoft’s API reuse and prebuilt assets helped it complete its digital transformation in just 14 months – half the time it allotted. 
“We knew that with MuleSoft as our API gateway and integration layer we would be able to be more agile and transform more quickly,” says Wiphak Trakanrungsi, Head of Technology Software Development and Innovation at Lotus’s.

Digital transformation is the competitive advantage

An enterprise API strategy that facilitates data integration across applications will empower leaders to accelerate innovation and operationalise AI to drive business value and growth for the future. Through revenue generation, operational cost reduction and the promotion of self-service, integration, automation and APIs will help businesses maintain their competitive edge in 2024 and beyond.

Read the full 2024 Connectivity Benchmark Report for a comprehensive understanding of the digital transformation landscape in APAC and beyond.

2024 Connectivity Benchmark Report

Discover how enterprise organisations around the world are using AI and automation to power digital transformation.

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The post The 2024 Connectivity Benchmark Report: Key Trends Shaping APAC’s Digital Landscape appeared first on Salesforce.

In my 20-plus years as a sales leader, my goal has always been to create forecasts that are so accurate they astound the C-suite. That’s really the goal of every sales leader — we want to use sales-forecasting techniques like a meteorologist uses climate signals to accurately predict the weather. Then, when we say it’s going to be sunny, we know it will be. It all comes down to answering two basic questions: How much will we sell? And when?

When we’re right, we’re living the dream: predictable revenue that shows consistent growth and reveals the future of your business. But getting there isn’t easy. It’s taken me a lot of trial and error to figure it out. Below I share five forecasting tips I wish I’d known sooner.

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1. Decide which deals to include in your forecast

The answers to “how much” and “when” are found in individual deals — the likely revenue of a given deal, and when that revenue will hit. But those questions come at the end of the forecasting process. To see if my deals are even worth including in a forecast, I analyse the health of each one by answering three questions: who, what, and why. 

• Who? Sales comes down to whether people buy, so begin your sales forecast with the people in your pipeline. List the stakeholders you’re talking to in every deal, and determine whether you have key decision-makers involved. If you do, then count the deal as part of your forecast. If you don’t, keep working on looping in someone with purchasing power. 
• What? What products are you selling? Your sales forecast should count only deals that have a strong product-customer fit, because deals that don’t are not likely to close. Take the ones that do and roll them up to your forecast.
• Why? Identify whether the prospect feels a strong need for your product. If they don’t, the deal will probably stall. This need can take many forms: Maybe there’s an external factor, like an event, that will make them sign on the dotted line, or maybe you’ve done a good job convincing them to switch to your solution in order to save costs, reduce risk, or support a strategic goal.

“When I was a sales leader, I had to figure out whether the deals in my pipeline were nothing more than hopes and dreams,” said Nikki Ivey, senior strategic account broker at OppGen and former chief revenue officer at Inclusivv. “Looking at our pipeline with a critical eye is scary, but forecasting is about accuracy, not aspiration.”

Build your own accurate sales forecast, step by step

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2. Use negative forecasting to understand risk

You can also use forecasts to assess current risk to your business. This is called negative forecasting. For example, one of our customers sells to manufacturing businesses. Some of the businesses in this industry have struggled with supply chain challenges and new regulations, and are cutting budgets as a result. So, our customer added a Budget Cuts field in their customer relationship management (CRM) software to tag deals connected to these businesses.

Now, sales leaders at this company can quickly spot which deals need extra attention, and expedite them to stay on the forecast course. Another benefit: The company has a clearer view of how this potential risk may affect their numbers.

Your forecast can change in a flash, and negative forecasting is useful for studying the impact of the unexpected and adapting to it (think extreme weather, economic crisis, or global unrest).

3. Create forecasts the entire company can use

When I started out in sales, I knew I had to turn in accurate forecasts to make my sales leaders happy. Now that I’ve grown in my career, I’ve learned that every department relies on sales forecasts.

I encourage my sellers to communicate regularly about sales forecasts to every team in the company, whether it’s through periodic leadership syncs or sharing documentation of plans and commitments with internal stakeholders, like finance and marketing reps.

“Forecasting is not just about getting the revenue in. It’s about seeing the bigger picture and predicting the future state of the company,” said Lizanne Kiel, executive vice president of SMB sales at Salesforce. “For example, the amount of growth you’re predicting means human resources will commit to a certain hiring strategy. Product managers will commit to building a certain number of products. Marketers will set new budgets to support the trajectory.”

4. Stop going with your gut and lean on the data 

“Sales is an art and a science,” said Dave Borrelli, senior vice president of sales at Salesforce. “But we actually need a lot more science.” Put another way: We need reliable numbers, not guesswork, to fuel accurate forecasts. If you forget all the sales forecasting techniques but one, it should be this: Listen to the data.

Reps need opportunity data to map out the best path for closing deals. Managers need dashboards that show which reps are on track to beat their targets, and which reps need coaching to stay on track. Finally, sales leaders need to visualise data from around the company to spot problem areas and adjust the strategy to stay on course. 

Your team can rely on data only if it’s rock solid. That’s where building a data culture comes in. When it comes to data, here’s my guidance: If there isn’t a record of it, it doesn’t exist. When you focus on documenting the status of your deals and customers, you can answer those critical questions from before: who, what, and why? How much and when? This makes your sales forecasts that much more accurate.

5. Use technology like AI to make better predictions and take action

I wish I’d leaned on technology sooner. The old back-of-the-napkin tricks and predictions from the most confident sales rep can’t hold a candle to today’s sales forecasting tech. AI, in particular, is reaching a tipping point. High performers are almost twice as likely to use AI as underperformers, according to the 2023 State of Sales Report.

That’s why I’m leaning into AI these days. You’ll see two primary kinds of AI in sales: predictive AI (which creates predictions based on patterns in existing data) and generative AI (which uses data to create new content, like emails). Forecasting benefits primarily from predictive AI.

I recommend using a CRM with built-in predictive AI so you don’t have to juggle extra tools. The best ones show you, via real-time dashboards, where in the sales process deals are likely to stall, and when revenue will be at risk. AI can also digest conversations from sales calls and identify trending topics, like competitor mentions or pricing objections. These insights give you a better sense of which deals will close, and when, improving forecast accuracy.

Leaning on technology lets me go from merely predicting the weather to changing the weather. It also helps me avoid human error — a pitfall of sales teams that rely on manual processes and calculations. 

Bring in sales forecasting techniques that boost accuracy

Can you imagine a meteorologist who shows up to a sunny picnic wearing a raincoat and carrying an umbrella? You probably wouldn’t watch their forecasts anymore. Become that trustworthy, confident sales leader whose forecasts live up to their promise. With data and AI on your side, I’m predicting sunny days ahead.

Bring your sales forecasts to new heights of accuracy

Sales Cloud, powered by Einstein, uses data and AI to take the guesswork out of forecasting and helps you hit your numbers every time. Visit our product page to learn how.

Forecast like a beast

The post 5 Tips To Create the Most Accurate Sales Forecasts of Your Career appeared first on Salesforce.

Learn new skills and win fun prizes with Trailblazer Quests

There’s no better way to learn than on Trailhead, the free online learning platform from Salesforce. Trailhead allows individuals, teams, and companies to skill up by learning Salesforce skills, along with crucial interpersonal and business skills like data literacy and emotional intelligence.

We know that there is a lot to learn these days, and we want to make sure you have some fun while doing it. While learning is its own reward, there’s always room for a little extra motivation. That’s where Trailblazer Quests come in. Trailblazer Quests combine the challenge of learning new skills with the chance of winning sweet prizes.

How to participate in these Trailblazer Quests

Get started on your quest with two simple steps:

1. Sign up for your free Trailhead account, if you don’t have one already.
2. Complete any or all of the three quest trailmixes

• Data Cloud Quest
• AI Skills Quest
• Automation Quest

*Official rules apply. See the Trailblazer Quests page for full details and restrictions.

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As technology advances, the state of customer service changes along with it. Customers expect companies to adapt to their needs, and technologies like generative AI are playing a major role in meeting those evolving expectations. Here are five customer service trends to keep on your radar as you prepare for the future of customer service, based on new data from the “State of Service” report.

Table of contents

• Service organisations are now revenue generators — not cost centres
• Self-service is a clear competitive advantage
• Connected data enables a better customer experience
• Conversational AI is taking proactive, personalised service to the next level
• AI is improving productivity and safety in the field
• Staying one step ahead of customer service trends

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High-performing service organisations are using data and AI to generate revenue while cutting costs — without sacrificing the customer experience. Find out how in the 6th edition of the State of Service report.

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1. Service organisations are now revenue generators — not cost centres

Companies are looking for new ways to drive growth and protect their margins, and many see service as a prime opportunity. In fact, 85% of decision makers say service is expected to contribute a larger share of revenue this year. 

So how can you take action? Our research shows that leading organisations are actively tracking key performance indicators (KPIs) that are linked to tangible business outcomes. In fact, the share of service organisations tracking revenue generation has nearly doubled since 2018, from 51% to an astonishing 91%. The share tracking customer retention rose by 29 percentage points over the same period. If those customer service analytics aren’t already on your radar, it’s time to make some changes — otherwise you risk getting left behind. (back to top)

2. Self-service is a clear competitive advantage

Self-service helps customers resolve simple issues, freeing agents to spend more time on high-complexity, high-value interactions. 

Our latest research shows that high-performing organisations are much more likely than underperformers to provide self-service tools like knowledge-powered help centres, customer self-service portals, and chatbots powered by AI. When customers can interact with a chatbot to answer a question or use a guided journey to start a return, live agents have the time they need to manage more complicated requests. That’s critically important for the 69% of agents who report difficulty balancing speed and quality. (back to top)

3. Connected data enables a better customer experience

Many organisations keep data in different silos or applications, so it’s difficult to get a complete view of the customer across all channels. 

Bringing customer data together is all about creating an end-to-end view of the entire customer journey. This way, you’ll have a continuous feedback loop between sales, service, and marketing, keeping everyone on the same page. Maybe that’s why 82% of high-performing organisations use the same customer relationship management (CRM) platform across all departments — up from 62% just two years ago.

The stakes are high: 92% of analytics and IT leaders say the need for trustworthy data is greater than ever. That’s why privacy, security, and trust have already become a major competitive advantage in the evolving AI landscape. 

As companies try to stay one step ahead of these and other customer service trends, leading organisations are adopting programs that prevent large-language models (LLMs) from retaining sensitive customer data. More organisations are training their own domain-specific models to access a secure AI cloud while storing data on their own infrastructure. These efforts are essential to preserving customers’ loyalty and trust in the years to come. (back to top)

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4. Conversational AI is taking proactive, personalised service to the next level

When it comes to meeting customers’ sky-high expectations, proactive service is more important than ever. “It’s essential to proactively resolve issues before they have any significant business impact,” says Jules O’Donnell, Salesforce administration manager at Quickbase. “This means keeping up with technology solutions to scale service and meet customers where they are.” 

Our latest research backs that up: 95% of decision makers at organisations with AI report cost and time savings, and 92% say generative AI helps them deliver better customer service. It should come as no surprise, then, that 83% of decision makers plan to increase their AI investment over the next year, while only 6% say they have no plans for the technology whatsoever. 

The introduction of conversational AI assistants is one of the innovations that’s making these benefits possible. From the contact centre to the field, AI assistants surface the right information at the right time to enable proactive service, improve Net Promoter Scores, and increase loyalty. 

Here’s what that looks like in practice:  

• Responding to customers with personalised, relevant answers grounded in trusted company knowledge across any preferred channel — including email, SMS, live chat, and social media 
• Resolving customer issues faster using generative answers seamlessly integrated into agents’ and technicians’ flow of work
• Autonomously completing tasks like auto-summarising intricate support cases and field work orders (back to top)

5. AI is improving productivity and safety in the field

Our research shows that mobile workers say innovative field service technologies make them feel safer and more effective at their jobs, empowering them to be better brand ambassadors. These technologies include intelligent scheduling, route optimisation, AI-generated reports, and augmented reality (which can create detailed 3D rendering of large areas in seconds). 

One of the emerging benefits of these and other technologies is the ability to generate insights and predict job duration. For example, workers can use AI to easily view asset condition as well as maintenance and repair history, then schedule proactive service to minimise downtime.  

Customers are benefiting, too. They can book and reschedule their own appointments using intelligent appointment assistance. And many customers have the ability to check when a technician is on the way, reducing no-shows and call volume for a better customer experience all around. (back to top)

Staying one step ahead of customer service trends

A great strategy starts with the right questions. How can you pursue innovation while maintaining the integrity of your data? How do you build customers’ loyalty and trust? And what’s the secret to delivering faster, more effective customer service without breaking the bank?  

The right technologies can help you prepare for the future while keeping up with the latest customer service trends. That’s why your organisation must combine people, technology, and processes to deliver faster, more effective service at scale — with AI assisting you every step of the way. (back to top)

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The post 5 Customer Service Trends You Need to Watch appeared first on Salesforce.

Self-service lets your customers find the answers they need on their own time, without the help of an agent. Most importantly, it’s what they prefer: our research found that 61% of customers would rather use self-service for simple issues. 

Enabling your customers to help themselves also increases efficiency. We found that 67% of organisations are now tracking case deflection, typically done through customer self-service or automated processes.  

To ensure your self-service customer service channels always make the biggest impact, what can you do quickly — even in just one hour? Turns out, it’s a lot.

What you’ll learn:

• What is self-service customer service?
• Benefits of self-service
• How to set up for self-service customer support success

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What is self-service customer service?

At a high level, self-service customer service simply means letting customers help themselves. To give customers this option, you can provide:

• A help centre, also known as a knowledge base, where customers can search for answers to common questions.
• A customer portal, a branded website customers log into to access personal information and complete actions related to their account.
• A customer community, where customers gather to share ideas, answer questions, and solve problems together.
• Chatbots that provide 1:1 assistance to customers without an agent having to step in.

These self-service tools give your customers convenience, speed, and anytime availability. (Back to top)

Benefits of self-service

Self-service customer support is a win-win for both your customers and your business.

Nobody likes to wait in a support queue for assistance. Self-service can also provide fast or even instant answers in some cases. This can lead to a better customer experience and higher customer satisfaction scores (CSAT). 

Your business benefits by reducing support costs and improving operational efficiency. By deflecting routine questions to self-service channels, you can allocate your resources more effectively. For example, your agents can focus on complex cases that require critical thinking and empathy. (Back to top)

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How to set up for self-service customer support success

Your goal is to make it easy for your customers to find solutions independently. To set your business up to deliver successful self-service, let’s look at three key steps to take.

1. Address frequently asked questions

Taking a few minutes to connect with your team will help you understand the most common customer questions to address in your self-service options. Even with advancements in AI, there’s still no substitute for human experience. You can use your team’s insights to make continuous improvements to your self-service customer service channels.

• Host a daily standup
  Round up your team and gather commonly asked customer questions and how your agents resolve them. (This can be done virtually or in-person). With advancements in artificial intelligence (AI) technology, soon your AI-powered customer service software may be surfacing commonly asked questions to you.  
• Streamline collaboration with technology
  Encourage agents to use collaboration tools like Slack to communicate and work together. Slack helps your team stay aligned and move fast. Use it to bring the right people into the right conversations – like swarming on a difficult case with experts from across your organisation.
• Make sure your help centre has an accurate knowledge base
  Knowledge provides the key foundation to building out your self-service experience. Create and consistently update knowledge base articles to make sure your users always have the most relevant information. It’s also the foundation for generative AI in self-service. Remember: the more advanced your knowledge base, the more robust the overall search experience will be to find the right answers faster.

2. Find ways to streamline workflows

Simplifying processes by making it easier to find information goes a long way for customers, increases efficiency, and frees up agents from cases that can be handled with self-service.

• Make it easy to find self-service channels
  Customers don’t want to search for support. Make sure that when they search online for customer support, the results provide a clear path to your help site’s landing page.
  
  Your company’s contact information shouldn’t be displayed in the search results. A customer will be less likely to access your help site and use self-service. 
  
  Once customers get to your site, make it easy to get self-service. With a simple widget or code snippet, you can integrate a fixed channel menu on your help site home page. This can direct customers to chatbots, your knowledge base, or a customer community, like the Serviceblazer community
  
• Route cases with chatbots
  Chatbots can streamline workflows – especially AI-powered ones, which are programmed to have human-like conversations. AI chatbots use natural language processing (NLP), which allows them to better understand human speech – including the intent behind what the customer is saying. These bots can interpret the context of what a customer types or says – and then, with generative AI, respond intelligently based on existing data.
  
  Rules-based chatbots also do a lot for self-service. They respond based on buttons a customer clicks or particular keywords the customer uses. If you have a rules-based chatbot, review the chatbot data to find specific keywords for easy answers, and be sure to have an FAQ database the chatbot can use to answer questions. But do consider upgrading – an hour spent learning about the latest in AI chatbot technology could be a step toward greater efficiency.
  
• Create guided processes
  In your customer self-service portal, you can automate specific processes for customers and free agents from receiving a high-volume of calls. What are the simple issues that take up agents’ valuable time, but could be just as easily done by customers? By integrating a workflow on your end, such as canceling an order or booking a field service appointment, the automation process appears on their screen and walks customers through each step. This not only saves on cost, it increases productivity and efficiency. 

3. Continuously improve with data and human review

The quick ways we’ve discussed to improve your self-service customer support offering can make a big impact. But there’s even more you can do over time. Tackle the ideas below in one-hour chunks, and soon you’ll be well on your way to building an excellent self-service experience.

• Prioritise reviewing self-service
  Regularly assess your company’s self-service customer support experience from every angle. For example, how does your help centre home page look? How do your search features perform? Are your article pages consistent? Is your chatbot performing well? Does your site allow visitors to provide feedback – not only about your products, but also the support experience? This handy self-service assessment tool can help you identify any gaps where you’re currently not meeting best practices. It gives you helpful guidance on where to focus your improvement effort.
• Review your data
  What are your objectives for self-service customer service? Perhaps you want to increase case deflection, so you can give customers the kind of assistance they prefer and reserve your agents’ energy for more complex matters. Or maybe you want to increase CSATs. Decide on the key performance indicators (KPIs) that matter to your team. Then use service analytics to track and monitor this data with easy-to-understand charts and graphs.

Ready to get started? With a few simple updates, you can ensure your self-service customer support channels are working hard to help your customers quickly find the answers they need. In time, your customers will be getting an efficient and easy self-service customer service experience they’ll love. Then watch your CSATs soar. (Back to top)

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The post 3 Ways to Take Your Self-Service Customer Service From ‘Meh’ to Marvelous — Quickly appeared first on Salesforce.