In 2024, we entered the third wave of AI with autonomous AI agents that can make decisions and take action without human intervention — just as AI was meant to be.
A game-changer for businesses, AI agents allow them to boost productivity, deliver personalised customer experiences , and drive topline growth. But what’s next?
What else can businesses in ASEAN expect, and how can they leverage AI agents to grow their business and develop their workforce further?
We got Sujith Abraham, SVP and General Manager for Salesforce ASEAN, and Gavin Barfield, Vice President & Chief Technology Officer, Solutions, Salesforce ASEAN, to share their top 10 predictions that will shape the course of ASEAN’s dynamic business landscape in 2025.
Sujith leads the Salesforce ASEAN business and brings more than 20 years of leadership experience in enterprise technology to his role. He’s passionate about ensuring the success of our ASEAN customers, partners, employees and community, and transforming good ideas and people into impactful businesses built on strong culture and high levels of engagement. Gavin also has over 20 years of experience, with a solid technology background that includes IT infrastructure, enterprise architecture, cybersecurity, and program management across a variety of industries.
Given their expertise and authority in the field, they foresee ASEAN businesses transitioning from AI experimentation to full-scale implementation in 2025, as businesses work toward a future where humans and agents drive customer success together with AI, data and action. Here are the key trends identified.
1. AI progressing beyond the experimentation stage, driven by autonomous agents
When Generative AI launched in 2022, there was huge excitement around the technology’s potential to revolutionise operations, boost productivity, and enhance customer experiences. Many businesses invested significantly in developing a generative AI strategy.
Despite initial excitement, few organisations have moved beyond Proofs of Concept (POCs) and limited trials to full-scale implementation. In some cases, Generative AI has failed to deliver accurate and useful outputs due to incomplete data. In others, solutions are disconnected from workflows, making them clunky and inefficient. Many applications of Generative AI, such as copilots and chatbots, were created as “solutions looking for problems”, focusing on experimentation rather than solving actual business issues.
Unlike chatbots and copilots, AI agents can autonomously navigate tasks and make real-time decisions directly in the flow of work — moving from mere assistance to taking action based on live data and context, marking a major step forward in enterprise AI.
In 2025, purpose-driven AI agents designed to address specific workflow needs and provide measurable benefits will help organisations move beyond experimentation to achieve tangible outcomes. For this to happen, generative AI needs to be grounded in the right data and delivered in the flow of work to offer meaningful impact.
2. Autonomous agents providing opportunity for topline growth
In the past two years, businesses have focused on cost-cutting measures in response to global economic uncertainties and slowing growth. The availability of autonomous agents today has now surfaced more opportunities for businesses to drive topline growth.
How, you ask? These agents will deliver on the promise of AI, succeeding where solutions such as copilots fall short. One limitation of earlier innovations was their siloed focus on unstructured data. For example, copilots could only act based on data within emails or presentations. This misses critical transactional context, such as customer purchase history or product details.
Copilots could only see part of the customer story, causing them to fall short on providing actionable insights. Businesses, in turn, missed out on opportunities to foster deeper and more compelling customer relationships that generated new revenue streams.
Autonomous agents can significantly impact a company’s growth trajectory. Take a bank that works with thousands of business clients as an example. An initial analysis of spend may lead the bank to think that most of their customers are SMEs with small spends. But a deeper look reveals that these businesses are spreading their spend across banks.
It’s extremely difficult to turn the workforce around to deepen engagements with all customers. Imagine if they implemented autonomous agents to maintain consistent customer engagement without constant human oversight. And agents operate 24/7 – think of how much coverage across customers is now possible. This enables the bank to increase its revenue base, which might otherwise be lost to competitors.
AI agents also allow sales teams to automatically pre-qualify leads before handing them over to human agents. This way, human agents don’t waste time on unresponsive prospects, basic inquiries, or low-engagement leads, which can significantly improve productivity and the bottom line.
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3. Out-of-the-box AI/agentic solutions and unified data will underpin AI success
In the race to operationalise AI, the winners will be those who forgo DIY solutions in favour of out-of-the-box solutions that offer superior speed, deployment, and accuracy. Businesses that adopt out-of-the-box solutions can focus on AI deployment and achieve immediate impact and value. In contrast, those who attempt to “DIY” their AI often face setbacks in the form of hidden costs and a slow realisation of AI capabilities.
Having the right data foundation is also key to maximising ROI from AI investments. Businesses need to consolidate structured data, such as customer transaction records, and unstructured data, such as customer emails, product information, and corporate policies, to build a unified view of their customers.
Without it, AI cannot deliver accurate, contextualised, and trusted outputs. Zero-copy capabilities are needed to ensure companies maximise their existing assets while minimising data preparation costs.
4. An organic AI ecosystem emerging within the region
AI is ushering in one of the biggest technological shifts of our generation, creating new services, roles, and industries. Just as the invention of smartphones and mobile applications created a thriving ecosystem of app developers, the growth of AI platforms is fostering a new generation of AI developers.
This drives innovation in ASEAN and opens the pathway for local talent to develop AI tools tailored to meet the region’s unique needs — whether it is Small Language Models (SLMs) that support native languages like Singlish or Taglish, or advanced models that tackle specific challenges like anti-money laundering.
With a combined population of over 650 million (including individual markets with over 100 million people such as Indonesia and the Philippines), and a combined GDP comparable to major economies, there’s a massive opportunity for AI developers in ASEAN.
The growth of the AI industry in the region will not only attract established global tech giants to set up operations and company headquarters locally, but also catalyse the birth of home-grown startups.
With that, we’ll see a migration of strategic roles typically available in the West to this part of the world, creating new opportunities for the future workforce.
5. AI agents disrupting traditional service models in ASEAN with scalable capacity, intelligence, and personalised experiences
In ASEAN, businesses often hire additional service staff as a quick fix for improving customer experience, especially with lower labour costs in the region. However, increasing headcount alone doesn’t necessarily improve problem resolution or overall customer satisfaction.
AI agents provide a fundamentally different approach by autonomously handling requests and enhancing customer interactions in ways that go beyond scaling capacity. This isn’t about efficiency alone but delivering high-quality customer service. AI agents leverage real-time data to provide context-aware support, making decisions and taking action as customer needs arise.
With AI agents embedded directly into workflows, businesses can reimagine customer service, delivering faster and more accurate responses without increasing complexity or requiring extensive training.
6. AI agents redefining jobs, empowering employees to focus on strategic work
AI agents are transforming the workforce by automating repetitive and time-consuming tasks, freeing employees to focus on higher-value work that drives innovation and growth.
This presents an opportunity for the workforce to transform their skill sets and take on more strategic roles. As AI agents become increasingly integrated into the workforce, employees will need to develop new skills to manage and optimise them. They’ll also have to leverage their industry knowledge to train these agents so that they can deliver the desired business outcomes.
This transformation mirrors the 1980s shift in banking, when staff moved from routine tasks like producing bank statements to customer service and financial advisory roles as automation took over.
Fast-forward to today — a telco that relies on AI agents to handle routine customer inquiries at scale will be able to empower its employees to focus on strategic tasks like optimising AI deployment and enhancing customer experiences.
This not only creates new career opportunities for the telco’s staff, but also allows them to save on operational expenses and infrastructure costs. With virtual AI agents running routine operations, the telco can easily scale operations, without necessarily building new offices or stores for its workforce to service the expanded client pool.
By blending human expertise with AI, companies can create a more agile workforce focused on driving growth and preparing employees for roles that require creativity, problem-solving, and strategic thinking.
7. New AI skill sets required for building and testing agents, including defining guardrails
As AI agents become central to business operations, there’s a greater need for professionals with specialised skills to guide these systems effectively. These skills will include being able to define agent instructions, craft prompts, and set guardrails.
Writing prompts may seem straightforward because they are written in natural language. However, crafting and refining these instructions and establishing clear guardrails to ensure an AI model performs as intended requires expertise.
While prompt engineering for LLMs is common, writing instructions and setting guardrails for reasoning engines will become critical skills. As more organisations integrate AI agents into their workflows, the demand for professionals with the skills to build and test agents in real-world scenarios will increase.
8. New types of AI models will push the boundaries of what AI can deliver
In 2025, we’ll see new, highly specialised AI models that go beyond text generation to drive complex, autonomous actions. Salesforce’s xLAM (Large Action Model) is at the forefront of this evolution. Unlike traditional Large Language Models (LLMs), which excel at generating responses, xLAM models are designed for action and decision-making, allowing AI to autonomously execute tasks and manage workflows without requiring explicit instructions.
These Large Action Models add a new dimension to CRM, enabling AI agents to handle tasks like function-calling, reasoning, and planning, adapting actions to fit real-world business contexts. By managing entire workflows proactively, like an autonomous sous chef that prepares each step, xLAM models can streamline operations and enhance decision accuracy across various environments.
As businesses adopt these models, xLAM can operate across multi-agent systems, coordinating actions between specialised AI agents to tackle increasingly complex, customer-focused processes. This innovation will make AI a powerful partner in business, delivering efficiency, context-aware responses, and automated actions that drive customer success with accuracy and reliability.
We’ll also see a proliferation of Small Language Models designed for particular industries or purposes. These models are trained on smaller but more reliable datasets and are effective at performing certain tasks. They’re cheaper to run, train and often more accurate than Large Language equivalents.
9. Agents building agents, agents talking to agents becoming commonplace
Just as organisations have employees specialised in specific functions, AI agents will soon be assigned unique roles within a network. These agents will work alongside human employees, communicate with other agents, and create new agents as business needs evolve. Each agent will have a defined function, allowing the network to handle a wide range of tasks efficiently.
In this agent network, meta-agents will be crucial, coordinating actions across other agents to keep workflows seamless. For example, a concierge agent might interact with users, guiding them on tasks it can help with and providing updates on task progress.
An orchestration agent would assess user needs and route requests to the proper agent, ensuring tasks are managed effectively. This setup enables collaboration on platforms like Slack, where human employees and AI agents can interact as a unified team, improving responsiveness and coordination.
10. Robotics driving the next wave of AI innovation
Robotics, the fourth wave of AI will emerge, transforming how businesses and customers connect. Beyond agents, robotics will see interactions evolve from text and voice systems to immersive experiences with physical robots and virtual avatars with lifelike, dynamic, and highly interactive engagements.
Picture virtual avatars powered by AI agents, with heads that move, lips that smile, and expressions that react naturally during interactions. This evolution will create more personal and engaging experiences in physical settings like a concierge in shopping malls, where customers can hold a real-time conversation with a lifelike avatar rather than typing queries into a screen.
At the same time, physical robotics will bring AI agents into the tangible world, unlocking new opportunities in environments such as F&B. Imagine a robotic barista powered by an AI agent that can offer personalised drink recommendations based on a customer’s past orders — including details like sugar preferences — and prepare the drink instantly.
Robotics will empower businesses to deliver natural, lifelike, and highly personalised interactions, redefining customer experiences that are powered by AI agents
Take your business to the next level with Agentforce
Now that you know what’s in store for ASEAN businesses in 2025, why not welcome Agentforce into your business so it can unlock unlimited potential with your team?
Agentforce is the agentic layer of the Salesforce platform for deploying autonomous AI agents across any business function — enabling you to scale your workforce. Build and customise autonomous AI agents to support your employees and customers 24/7, and access a library of ready-to-use skills for any use case across sales, service, marketing, commerce, and more.
Our handy ROI calculator can help you measure Agentforce’s value for your business, and you can take a closer look at how agent building works here.
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