For more than forty years, the Stage-Gate process has been the dominant framework for taking new products from idea to launch. It was designed for a world where evidence was scarce and expensive: market studies took months, business cases took weeks of cross-functional effort, and gates existed to manage big bets made on limited information. AI agents are now breaking those assumptions. When research, voice-of-customer synthesis, competitive analysis, and financial modeling can be performed by AI in hours at negligible cost, the bottleneck shifts from doing the work to making decisions — and a process built around long stages and infrequent gate meetings becomes the constraint rather than the safeguard.
Most organizations are responding by bolting AI tools onto an unchanged process and getting marginal gains. This workshop makes the case for a different path: rebuilding the innovation process AI-first. Drawing on Dr. Robert Cooper’s recent work on “Stage-Gate Agentic” and examples from early-adopter firms, attendees will learn what an AI-native stage gate looks like — compressed stages, agent-prepared gate deliverables, continuous evidence streams, and human gatekeepers refocused on strategy and risk — and how to take the first practical steps inside their own organization.
This workshop includes guided exercises in which participants map their own stage-gate process, select a pilot gate, and draft a 90-day transition plan. Attendees leave with a concrete starting plan, not just notes.
What you’ll gain from this workshop:
By the end of the workshop, participants will be able to:
- Explain why the economics that justified long, multi-stage NPD processes are eroding as AI agents collapse the time and cost of generating decision-grade evidence.
- Distinguish “bolt-on” AI tool adoption from an AI-native process redesign, and locate their organization on that maturity curve.
- Describe the core elements of an AI-native stage gate: compressed and merged stages, agent-built business cases, dynamic (continuous) gating, and evidence-scored gate decisions.
- Define how human roles change — project teams as orchestrators of AI agents, and gatekeepers focused on strategic fit, risk appetite, and portfolio balance rather than auditing homework.
- Map their own stage-gate process — stages, gates, cycle times, and evidence bottlenecks — and identify which stage or gate is the best candidate for an AI-native pilot, with the front end of innovation as the highest-leverage starting point.
- Evaluate what agent-built, gate-ready evidence looks like in practice, having directed a live Growth Signals build during the session.
- Leave with a drafted 90-day pilot plan — chosen gate, baseline metrics, and first steps — ready to socialize inside their organization without disrupting projects already in flight.
Who should take this workshop?
This workshop is designed for R&D and innovation leaders in organizations that run a stage-gate or phase-gate new product development process — across manufacturing, CPG, chemicals, food and beverage, industrials, life sciences, and similar sectors. Ideal attendees include CTOs and VPs of R&D or Innovation, gatekeepers and portfolio managers, NPD process owners, and product, marketing, and technical leaders involved in project and portfolio decisions. Because the session is built around applying the material to your own process, attendees get the most value when they arrive familiar with their organization’s current stage-gate structure; teams attending together can work the exercises on a shared process.d product managers, and engineering and technical leaders involved in project and portfolio decisions.
This professional development workshop is designed for current IRI members only. If you are not a member, please contact Clayton Warnke (cwarnke@nam.org)
IRI members can earn a complementary certificate of completion by completing this workshop and a short follow-on activity that highlights how they plan to apply their learning.
