All 2026 Conference Sessions

Gartner Opening Keynote: Win the AI Race by Thriving in the Intelligence Supercycle

Speakers:

• Mark McDonald, Distinguished Vice President, Gartner

Key take-aways

• AI does not enable the business, it is the business. Product leaders must build a business, not just a product.
• AI is reshaping business models and competitive advantage — leaders must adapt strategy and execution to thrive in the intelligence supercycle.
• The speed of AI innovation is outpacing traditional approaches — agility and rapid experimentation are now critical.
• Focus on business impact, not just technology — value comes from integrating AI into core decisions and outcomes.
• The winners will be those who embrace uncertainty, invest in AI capabilities and make intelligence central to growth.

Why Product Vision Matters More Than Ever in the AI Race

Speakers:

• Jim Hare, Distinguished Vice President, Gartner 

Key take-aways

• Experiential stickiness is more important than feature and differentiation checklists.
• Anchor the AI vision to clear user problem and strategic bet, then reflect it in a strategy and roadmap that compounds value over time instead of shipping isolated features.
• Make differentiation explicit by defining what your AI uniquely learns or automates and sequence the roadmap to deepen that advantage with each release.
• Build loyalty through trust and habit by embedding reliability, transparency and user control into the vision and reinforcing them with roadmap milestones. 
• Tie the vision to real user outcomes, use the product strategy and roadmap to continuously turn insights into user/business value so switching feels costly and staying feels natural.

GenAI and Product-Led Growth: Inseparable, Intertwined and Indispensable for Effective GTM

Speakers:

• David Yockelson, Distinguished Vice President, Gartner

Key take-aways

• Product-led growth is now essential — buyers expect hands-on experience before committing.
• AI and product-led strategies are converging, accelerating value and user-driven adoption.
• Success depends on blending traditional sales with analytics and automation to improve onboarding and engagement.
• Product experience is a key differentiator — refine your go-to-market approach to stay competitive.

Gartner Keynote: Top Disruptors, 2026

Speakers:

• Annette Zimmermann, Vice President, Gartner

Key take-aways

• The era of generalist AI is ending — domain-specific models will drive future value.
• By 2030, most GenAI will be specialised — tailored to industries and use cases.
• Automation will transform work — but also brings new security and trust challenges.
• Success depends on aligning AI with business outcomes — and building resilience in an uncertain landscape.

2030 Unveiled: Will Product Leadership Survive the Next Decade?

Speakers:

• Clifton Gilley, Vice President, Gartner

Key take-aways

• AI is redefining product leadership — automation, simulation and cross-functional collaboration are now essential for competitive advantage.
• The chief product officer’s remit is expanding — integrating product, engineering, marketing and customer success under unified leadership.
• Autonomous innovation is on the rise — self-evolving products and adaptive pricing require new skills and transparent governance.
• Responsible AI adoption is critical — success depends on upskilling teams, managing risk and keeping customer outcomes at the centre of strategy.

Kill Your Roadmap, Grow a Rhizome: Embrace Organic Product Planning in the Era of AI

Speakers:

• Garrett Astler, Director, Gartner

Key take-aways

• Product strategy is shifting — from rigid roadmaps to adaptive, organic models inspired by decentralised networks.
• Success now depends on enabling autonomous agents — using open APIs, composable architectures and real-time integration.
• Traditional metrics like MAU are less relevant — focus on outcomes per agent, time-to-outcome and ecosystem health.
• Leading organisations are moving away from backlogs and hierarchy — embracing decentralised teams and rapid, outcome-driven experimentation.
• The goal: Capture emergent value by orchestrating capabilities in response to real-time signals — not by predicting the future.