Key Takeaways:
- Peter Schwartz predicts 2025 will be a tipping point for agentic AI, also known as Large Action Models
- These AI agents can perform tasks autonomously—booking travel, managing service interactions, and more
- Early adoption is expected in customer service and enterprise systems, with full capabilities still a year or two away
Renowned futurist Peter Schwartz—Chief Futures Officer at Salesforce—suggests that 2025 might be the breakout year for AI agents, which he defines as systems that don’t just understand and generate text, but also take action on it.
In a recent Straits Times piece, Schwartz explained how AI has evolved beyond Large Language Models (LLMs), like GPT, into Large Action Models (LAMs) capable of completing real-world tasks. He gives a clear example: an LLM can search for flights, but an AI agent could actually make the booking.
“I’m going to come into 2025 where we’re going to see agents embedded in many different functions,” he said. “The first big one is things like service centers. About 80 to 90 per cent of calls can be handled by digital agents.”
Why 2025 Matters for AI Agents
– A practical step forward
Over the past year, technical platforms such as LangChain, AutoGPT, and Salesforce’s Agentforce have enabled models to break down goals, act on them, and coordinate across tools. The result is doing more than conversation—actual completion of tasks.
– From novelty to mainstream
While many AI agents are still proof-of-concept, businesses in e-commerce, customer support, and IT automation have begun early pilots. Gartner predicts widespread experimentation in 2025.
– Caution amid optimism
Schwartz and other experts acknowledge that autonomy comes with oversight challenges. IBM researchers have warned against overhyping functional capabilities, urging responsible deployment and monitoring as agencies gain control.
Use Cases to Watch
– Customer service
Agents may soon autonomously handle up to 90% of inquiries, managing everything from order tracking to technical support without human escalation.
– Consumer tools
Imagine a virtual travel assistant that books your flight, arranges lodging, and even plans your itinerary across multiple websites.
– Enterprise operations
AI agents can help with internal processes like IT provisioning, data analysis, or compliance monitoring—searching, evaluating, and taking action based on real-time information.
The Road Ahead
While 2025 may see AI agents become more visible, experts like IBM’s Maryam Ashoori emphasize that true autonomy—where agents reliably plan, act, and adapt—remains under development. We’re in the age of “rudimentary planning and tool-calling,” not fully independent intelligence.
Others urge realism: we’ve been orchestration-first for years, and now agencies are increasingly orchestration-heavy. Expect incremental progress, rather than superhuman leaps.
Still, Schwartz’s forecast aligns with a broader AI evolution—from passive generation to active execution. As investment and experimentation grow, 2025 may well signal the beginning of agentic computing. And with pilots underway in customer service, travel, and business systems, prepare for a year where AI begins to act—and not just speak.
Learn how AI Agents can supercharge your company’s profits and productivity at TMC’s AI Agent Event in Sept 29-30, 2025 in DC.
Rich Tehrani serves as CEO of TMC and chairman of ITEXPO #TECHSUPERSHOW Feb 10-12, 2026 and is CEO of RT Advisors and is a Registered Representative (investment banker) with and offering securities through Four Points Capital Partners LLC (Four Points) (Member FINRA/SIPC). He handles capital/debt raises as well as M&A. RT Advisors is not owned by Four Points.
The above is not an endorsement or recommendation to buy/sell any security or sector mentioned. No companies mentioned above are current or past clients of RT Advisors.
The views and opinions expressed above are those of the participants. While believed to be reliable, the information has not been independently verified for accuracy. Any broad, general statements made herein are provided for context only and should not be construed as exhaustive or universally applicable.
Portions of this article may have been developed with the assistance of artificial intelligence, which may have contributed to ideation, content generation, factual review, or editing.
