The phrase “AI agent” has entered the corporate vocabulary almost overnight—yet behind the buzzword lies a profound shift in how enterprises operate. Unlike generative AI tools that wait for prompts, AI agents act as teammates: autonomous, goal-driven collaborators that plan, decide, and execute within governed guardrails.

The impact is tangible. At a global logistics firm, an inventory management agent monitored supply levels, negotiated contracts, and triggered route optimisation automatically. Downtime plummeted, excess capital tied up in stock fell, and customer fulfilment improved. Managers shifted from transactional firefighting to strategic supplier and client work.

This isn’t science fiction; it’s an operating model transformation. The challenge is that many pilots stall because organisations underestimate the foundations required—data quality, integration, governance, and cross-functional alignment. Without these, agents remain curiosities. With them, they become value-creating colleagues.

For the C-suite, the question is no longer whether AI agents work. It is how to embed them into the enterprise as trusted teammates—driving measurable ROI, reshaping workforce design, and delivering durable competitive advantage.

In August 2025, headlines announced that GPT-5 was on the horizon, with early testers praising its improved reasoning and problem-solving. Within hours, I was in a boardroom where a utilities client had printed the Reuters article, circled the headline, and written across the top: “What does this mean for us?”

It’s the question every CEO, CFO and CIO is now asking as they weigh the impact of generative AI on enterprise strategy. The answer is deceptively simple: GPT-5 changes everything—and nothing. A new foundation model may fuel experimentation, but it does not transform an enterprise on its own. New AI models grab headlines; operating models create lasting competitive advantage.

That distinction explains the paradox facing executives today. Surveys show nearly 80% of companies have deployed generative AI tools such as copilots, chatbots or content assistants, yet most admit they have seen little measurable impact on revenue or margin. Adoption alone does not equal ROI.

The real opportunity lies in moving from predictive models to agentic AI systems—autonomous agents that integrate into workflows, make governed decisions, and deliver measurable outcomes in areas like supply chain, asset scheduling, and risk management. Early research suggests enterprises that adopt agentic automation achieve up to 6x the ROI of traditional automation.

For leaders, the key question isn’t “When does GPT-5 launch?” but “How will we redesign our operating model for AI transformation?” Those who focus on embedding AI into core processes, governance, and decision rights will build the next-generation enterprise. Those who don’t will remain stuck in pilot projects while competitors move ahead.