June 2 & 3, 2026 | Boston, MA
Agenda
Day 01
Tuesday, June 2, 2026
- 12:30 PM
- 12:40 PM
- 1:00 PM
- Why promising AI pilots rarely translate into sustained enterprise value
- A new operating model where AI senses, decides, and executes, with humans steering
- Rethinking strategy, talent, economics, and data to unlock real value
- From experimentation to scalable, outcome-driven transformation
- 1:35 PM
- How AI is reshaping engineering, product, and operations workflows from the inside out
- Where AI is delivering the most operational leverage today, and where it's still harder than expected
- The build, buy, and partner trade-offs behind running AI at scale in-house
- What other leaders should be paying attention to as AI moves from tool to operating layer
- 1:55 PM
- The disconnect between local AI wins and enterprise-level ROI
- Value governance as the missing layer in AI investment strategy
- A Strategy Realization Office linking AI execution to enterprise KPIs
- 2:30 PM
- The widening disconnect between AI spend and measurable business outcomes
- Data readiness, value attribution, and governance as structural barriers to ROI
- Moving from experimentation to scaled adoption, and what keeps breaking in between
- 3:05 PM
- Why most AI pilots fail to graduate into production-ready solutions
- Frameworks for connecting pilot results to enterprise-level value metrics
- The organizational and technical gaps that stall the path from proof of concept to scale
- 3:25 PM
Recharge, connect, and spark new ideas as you mingle with peers and industry leaders.
- 3:40 PM
- The accountability gap when decisions are co-produced by humans and AI
- Decision rights, ownership, and governance in hybrid operating models
- Leadership and operating model changes as AI reshapes authority structures
- 4:15 PM
- Who owns the outcome when AI shapes sourcing, pricing, or workforce decisions
- Designing accountability into AI operating models across business, tech, and risk
- Explicit value framing and governance as prerequisites for scaling, not afterthoughts
- 4:50 PM
- The operational reality of embedding AI into enterprise decision workflows
- Balancing speed and oversight as AI takes on higher-stakes decisions
- Technology architectures that support governed autonomy without creating bottlenecks
- 5:50 PM
Entrepreneurs behind innovative solutions will each present pitches on why their technology is best and how it will add the most value to business. After some tough questions from our judges, the audience will have their chance to vote on which technology they are more likely to implement within their own organizations. Who should win this startup challenge?
- 5:55 PM
- 6:55 PM
Day 02
Wednesday, June 3, 2026
- 9:00 AM
- 9:10 AM
- 9:40 AM
- Why real AI impact requires redesigning how work, decisions, and accountability flow across the enterprise
- Aligning human-AI decision-making, incentives, operating models, and data foundations for measurable outcomes
- A practical framework to scale AI beyond pilots and deliver ROI that stands up in the boardroom
- 10:15 AM
Step into JurAIssic World, where AI promises automation, augmentation and productivity while introducing complex regulatory and data protection challenges
• Why "can we?" is the wrong question, and the framework leaders need to ask "should we?" instead
• The responsible AI practices that turn regulatory and data protection challenges into competitive advantage
• How governance, done right, becomes the engine of innovation, not the brake on it
- 10:35 AM
Recharge, connect, and spark new ideas as you mingle with peers and industry leaders.
- 10:50 AM
- The validation bottleneck between AI output and human oversight
- Scarce SME bandwidth as the real constraint on AI autonomy
- Repeatable QA frameworks that shrink review cycles and taper human-in-the-loop
- 11:25 AM
- The shifting economics of build vs. buy as AI transforms service delivery
- Compute, platform, and model-based cost structures replacing legacy headcount models
- Commercial leverage and value capture as strategic levers for scaling AI
- 12:00 PM
- How provider-mandated contract overhauls, forced cloud transitions, and aggressive audits are reshaping enterprise leverage
- Why AI contracting requires a different playbook, and where traditional risk allocation breaks down
- Practical takeaways for negotiating in a market moving faster than internal procurement and legal processes
- 1:00 PM
- 1:10 PM
- 1:40 PM
• Why most enterprise data foundations weren't built for AI, and what has to change before it can scale
• The common failure patterns and early warning signs leaders are missing, backed by ISG Research
• A practical lens for assessing whether your architecture is truly AI-ready
- 2:15 PM
- The architectural requirements for data that supports real-time, AI-driven decisions
- Why governance and observability are non-negotiable for production-grade AI
- Closing the gap between data infrastructure built for analytics and data ready for autonomy
- 2:35 PM
- The reemergence of master data as a critical enabler of enterprise AI
- The overconfidence trap in data governance, and the acid test that exposes it
- Autonomous AI agents as unintentional stress tests on data architecture
- 3:10 PM
- The architectural requirements for data that supports real-time, AI-driven decisions
- Why governance and observability are non-negotiable for production-grade AI
- Closing the gap between data infrastructure built for analytics and data ready for autonomy
- 3:45 PM
- Why analytics-grade data falls short when AI needs to act, not just inform
- The contextualization, trust, and integration requirements for autonomous decision-making
- Proving that data, models, and outputs are auditable, explainable, and production-ready
- 4:05 PM
You’ve absorbed ideas, insights, and inspiration—now it’s time to put them to work. ISG will provide guidance on your next steps!
- 5:05 PM