What Gartner’s Product Leadership Conference Made Clear: AI Is No Longer a Feature. It’s the Business

AI dominated the room

What stood out most was not just the volume of AI discussion, but the urgency behind it.

One stat captured the mood of the event: by 2035, Agentic AI is expected to generate $450 billion in market revenue opportunity and become a table-stakes capability in 75 percent of software offerings. That forecast helps explain why the conversation has shifted so quickly from cautious curiosity to active planning.

But the tone of the event was not blindly optimistic. It was more complicated than that.

There was real excitement around AI’s potential to unlock new business models, improve productivity, and support more value-based offerings. At the same time, security, governance, and long-term accountability came up again and again. Many attendees seemed to share the same concern: AI capabilities are moving fast, and the guardrails are struggling to keep up.

The big shift: AI is becoming the business

One of the strongest themes from the keynote sessions was that product leaders can no longer treat AI as an add-on.

In Eric’s notes, one idea came through clearly: AI does not simply enable the business anymore. It is becoming the business. That changes the conversation entirely. Product teams are not just thinking about feature roadmaps or isolated use cases. They are being pushed to rethink how products create business value in the first place.

That shift has major implications for strategy, team structure, and execution.

One keynote noted that the average life of durable skills has shrunk from 15 years to 5 in the AI era. Gartner also estimated that since 2022, 65 percent of skills will be disrupted through 2026. Those are not small changes around the margins. They point to a deeper reset in how organizations build capabilities and prepare teams for what comes next.

Value-based pricing is gaining traction, but questions remain

Another idea that surfaced repeatedly was value-based pricing.

There was plenty of energy around the idea that AI could help companies price around outcomes rather than effort or access. Some organizations are already moving in that direction. But the practical questions are still unresolved. If value looks different for every customer, how do you define it? How do you measure it? And how do you price consistently at scale?

That tension felt very representative of the event overall. The potential is obvious. The operating model is still catching up.

Vision and prioritization still matter, maybe more than ever

For all the attention on AI, some of the most useful takeaways were refreshingly foundational. A session on product vision reinforced the importance of connecting strategy to roadmap and roadmap to delivery. One line stood out: positioning wins acquisition, but vision wins retention. It is a sharp reminder that strong products do not just attract users. They give people a reason to stay.

That same throughline appeared in sessions on objective-focused prioritization. Rather than relying on intuition alone, Gartner emphasized the value of structured scorecards and intake models to evaluate ideas more objectively. The point was simple: prioritization should not be a scramble. It should be a visible, repeatable mechanism that connects enterprise objectives to portfolio plans, product direction, and team-level work.

Five ideas stood out in that framework:

For organizations trying to move faster without losing focus, that kind of structure matters.

A few signals about where the market is going

The event also offered a handful of broader signals about where product leadership may be headed next.

One estimate that stuck with Eric projected that more than 42 million drones will be in use globally by 2032, supporting everything from deliveries to defense. Another session focused on tech and innovation trends in China, with attention on embedded AI, robotics, and emerging results-oriented service models.

These examples may seem far from day-to-day product operations, but they point to something bigger: product leaders are heading into a market where AI will not just sit inside software. It will increasingly shape physical systems, autonomous workflows, pricing models, and customer expectations.

• Lock in predictable database costs
• Retain flexibility to change instance sizes or configurations
• Reduce financial risk while scaling workloads

For finance, procurement, and cloud teams alike, this bridges a long-standing gap between financial planning and technical flexibility.

Security is no longer just a technical issue

Cybersecurity was another important thread throughout the event, especially as AI makes threats more scalable and more convincing.

A session on disinformation security made the case that cybersecurity products will need to address more than traditional system threats. Deepfakes, impersonation, manipulated narratives, and AI-assisted social engineering are becoming part of the risk landscape too. That expands the conversation. Security is no longer only about protecting systems and data. It is also about protecting trust.

Three things to know if you missed it

Why this matters for Rego

For Rego, the conference offered a useful view into where product leadership is heading.

The themes around strategic alignment, objective-based prioritization, business value, and execution discipline all map closely to the challenges many organizations are trying to solve right now. Even in areas where the answers are still taking shape, like value-based pricing, the direction of travel is clear. Product leaders need better ways to connect vision to outcomes, and they need systems that can keep pace with rapid change.

Final thought

Gartner’s Product Leadership Conference did not present a neat, settled picture of the future. That is part of what made it useful.

What it revealed instead was an industry in motion: excited, uneasy, ambitious, and still working out the rules while the ground shifts beneath it. That may be the most honest snapshot of product leadership in 2026.