I’ve been bringing machine learning and now agentic AI products to market for over a decade. Three years ago, I even started using different AI products to perform the kinds of tasks an executive assistant would. The buzz today is that “agentic” will change everything, and I think it will, just not in the ways most people expect. Agentic AI, the promise of systems that can act with initiative, reason and autonomy, is being sold as the next great leap in AI. In the hype cycle, we hear about “digital employees” and “agents that think.” The real transformation, however, is happening in quieter, more practical ways.

I’ve invested meaningfully in agentic AI because I believe it will fundamentally reshape our world. For business leaders building these systems, understanding this shift is critical. The next tech revolution isn’t about sentience or spectacle; it’s about structure, orchestration and timing.

Here are five contrarian truths about what to expect.

1. Orchestration Is the Next Phase of Agentic AI

Everyone is chasing the dream of the “fully autonomous agent,” but what’s actually emerging in the market is something quieter.

In logistics, for example, I’m seeing agent networks where one forecasts shipment delays, another reroutes trucks and a third updates insurance or customs documentation automatically. None acts independently, yet together they move information seamlessly across systems.

Most organizations still focus on the big outcome instead of the workflow required to achieve it. Trying to get AI to deliver the final result remains high risk and rarely succeeds. The leading edge today begins with introspection, and workflows become the foundation for practical agentic design.

Across industries, the real progress isn’t in replacing human judgment but in extending it. That’s the quiet evolution underway — orchestration over autonomy. Firms pioneering hybrid intelligence, such as Creative Glu and Codestrap, are setting the tone for what comes next. (Full disclosure: I’m invested in Creative Glu Labs.)

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Autonomy captures attention. Orchestration is what’s actually taking shape.

2. Governance Failures Will Be the First Crises

The first real problems in agentic AI will not be caused by bad code but by bad rules.

Consider two procurement agents—one negotiating a discount and another enforcing compliance—arguing over which contract terms take priority. The result is a stalled transaction, not a system crash. These moments will expose the need for governance frameworks as urgently as financial markets once needed regulators.

As leaders, we must think about defining the guardrails now—clarifying decision rights, accountability and escalation paths.

3. Agentic AI Will Replace Human Resources, Not Human Purpose

Let’s be honest: Agentic AI will replace people, but not in the dystopian sense. It will replace human resources in the literal sense—the available labor supply.

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In Japan, for instance, factories already face worker shortages due to aging populations. Imagine AI agents managing quality control and vendor coordination so that a smaller human team can handle creativity and problem-solving. Rather than simply replacing workers, AI can help keep industries viable when people simply are not there to fill the roles.

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4. First Real Use Cases Will Be the Boring Ones

Forget the science-fiction visions of Cylons. The first real use cases in agentic AI will be the boring ones, the systems that quietly replace part of what humans already do.

Alex AI and Clara are AI agent products that schedule meetings across multiple time zones. (Full disclosure: I’m invested in Alex AI.) They check calendars, read the context of each request, select times, send invitations and automatically reschedule if something changes.

I expect the same pattern will appear in logistics, billing, compliance and procurement. These are not glamorous fields, but they are ready for transformation. The internet’s biggest breakthroughs did not come from flashy apps; they came from infrastructure. The same will be true here. The “boring” orchestration layers will quietly become indispensable.

5. Agentic AI Will Redefine How We Measure Trust and Consent

In the future, instead of asking, “Do I trust this person?” we’ll ask, “Do I trust the system that authorized this action?” The battleground won’t be who builds the smartest agent, but who builds the most verifiable one.

Digital identity, consent management and transparent credentialing will form the new trust stack. In a world where agents transact and decide for us, trust itself becomes programmable.

The ethical frontier is consent. When your agent signs a contract or moves money, who authorized it? When a digital counterpart represents you, where does your intent begin and end? The real challenge isn’t making AI moral but ensuring explicit consent in every decision chain. 

As leaders, we would be well served to think of agentic AI as an ecosystem to govern rather than as a system to command. Verification and consent will become the new currencies of trust.

Quiet Revolution Ahead

Agentic AI is already here, threading itself through the operational fabric of business and daily life. It is in the compliance report that writes itself, the scheduling system that negotiates your time and the procurement agent that audits its own contracts.

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The next decade will belong to those quietly designing systems that make autonomy safe through coordination, governance and consent.

If you’re a leader wondering where to begin, start with what is boring. Look at the processes you already run, the ones that are routine, repetitive and rule-based. That’s your first step. Agentic AI is just the next generation of automation. Start with what you can measure, then scale what works.