Despite near-universal AI adoption, most organizations remain stuck in pilot mode: McKinsey's latest State of AI research finds that nearly two-thirds of organizations have not yet begun scaling AI across the enterprise, even as 88 percent report regular AI use in at least one business function. The gap between experimentation and enterprise-level value is where most transformations stall, and where a deliberate roadmap makes the difference.
This session, led by QuantumBlack, AI by McKinsey, will walk participants through the building blocks of an effective entity-level AI roadmap: how to move beyond isolated use cases toward a coordinated strategy that ties AI investment to business value, sequences capability-building across the organization, and sets the conditions for scale. Drawing on McKinsey's research into AI transformation, including the finding that organizations seeing the greatest impact from AI often look beyond cost reduction toward growth and innovation as explicit objectives, the discussion will cover what separates high-performing organizations from the rest: leadership ownership of AI initiatives, fundamental redesign of workflows rather than bolt-on automation, and sustained investment in talent, data, and operating-model readiness.
Participants will leave with a practical framework for assessing where their entity sits on the AI maturity curve, identifying the highest-value opportunities for their specific business context, and structuring a roadmap that builds durable capability rather than one-off wins.
At Amazon, AI isn't a future ambition—it's the engine running one of the world's most complex operations today. We deploy over one million robots powered by AI foundation models across our fulfillment network, use machine learning to predict customer demand before a purchase is made and pre-position inventory across 2,000+ facilities, and leverage generative AI agents that monitor supply chains 24/7. Amazon processes over 13 billion items annually with AI embedded at every layer—demand forecasting, inventory placement, robotic sortation, and real-time operational decision-making.
For an enterprise like Ilitch Holdings, managing the intersection of food service, sports, and entertainment at scale, the lessons from Amazon's AI-driven operations offer directly transferable strategies: how to unify disparate supply chains across venues and geographies, how to use predictive analytics to anticipate demand surges (whether game day or a Tuesday lunch rush), and how to deploy automation that empowers your workforce rather than replaces it.
Author, Delivering the Digital Restaurants; previous keynoted at various QSR + Tech conferences
Currently Go To Market Leader with InvisibleTech.ai
YouTube Channel, https://www.youtube.com/@thedigital.restaurant
AI is no longer a future concept for the restaurant industry — it is quickly becoming a competitive differentiator in how brands serve guests, support teams, and operate at scale. In this session, Carl Orsbourn, Senior Vice President at Invisible Technologies and co-author of Delivering the Digital Restaurant, will explore how QSR and hospitality leaders can move beyond AI experimentation and begin creating measurable business impact
AI deployment is outpacing the frameworks designed to govern it and organizations that wait for regulatory clarity before building responsible AI practices are already behind. Oversight is coming but will your governance posture hold up when it does.
More importantly, compliance alone will not be enough. An organization can pass every audit, satisfy every regulatory requirement, and still deploy AI that erodes the trust of the workforce, the customer, and the public it serves. Responsible AI is a higher standard than governance and the gap between the two is where the most significant and least visible organizational exposure lives.
