Salesforce 2025 ASEAN Predictions: Part 2

Autonomous AI agents promise to reshape industries, create new business models and unlock unprecedented opportunities for growth and innovation. Gavin Barfield, Vice President & Chief Technology Officer, Solutions, Salesforce ASEAN, shares his predictions for 2025.

If you missed Part 1, Sujith Abraham, SVP & GM, ASEAN at Salesforce, shared his insights—check it out here.

#1 AI Progresses 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 the 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 AI Agents Disrupt 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. AI agents enable organisations in ASEAN to move beyond traditional service models, creating a personal and frictionless experience while providing lasting value through smarter, real-time support.

#3 New AI Skill Sets Required for Building and Testing Agents, including Defining Guardrails

As AI agents become central to business operations, there is 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.

#4 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 will also see a proliferation of Small Language Models design for particularly industry or purpose.  These  models are trained on smaller but more reliable data sets and are effective at performing certain tasks.  They are cheaper to run, to train and often more accurate than the Large Language Equivalents.

#5 Agents Building Agents, Agents Talking to Agents Become 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 instance, a concierge agent might interact with users, guiding them on tasks it can assist with and providing updates on task progress. An orchestration agent would assess user needs and route requests to the appropriate 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, enhancing responsiveness and coordination.

This new era of agents will redefine collaboration, creating a blended environment where humans and agents work side by side to enhance productivity, improve customer experiences, and support business growth through streamlined operations.

#6 Robotics to Drive 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.