Services
Three stages, two practices. Leaders who skip straight to implementation usually come back to discovery.
Two practices, three stages
Innovation and Artificial Intelligence are separate practices that run through the same three stages. Most engagements start in one column. The useful ones end up using both.
Inspiration & Activation
Keynotes and inspiration sessions that show you and your teams the art of the possible.
the art of the possible, Amazon's Culture of Innovation, Systematic Inventive Thinking.
what's happening in AI, what are the business opportunities and risks, and how you can prepare for them.
Discovery & Direction
Dive into and explore opportunities, and then select a direction you want to pursue.
design the innovation mechanisms and approach that will help you accelerate and scale.
identify the best opportunities that are relevant for you and select projects for generative AI implementation.
Implementation & Adoption
Targeted engagements that build and launch solutions — and get people across the organization actually using them.
establish your innovation mechanisms and drive their adoption across teams, with the training and champions that make them stick.
implement selected projects and AI-powered products, then embed them in day-to-day work through enablement, governance, and measured usage.
A typical engagement
- KickoffLeadership session
Two hours with your leaders, hands-on and custom, to understand what is possible and what to consider for your strategy and your first projects.
- 2–3 sessionsOpportunity discovery
Explore value for internal productivity, customer value, or industry disruption, and leave with a prioritized portfolio of use cases.
- 4–8 weeksDevelopment sprints
Build the prioritized solutions with your teams or development partners, from proof-of-concept towards production.
- ContinuousScale the value
More teams building and using responsibly, internal sharing, and adoption that makes the value stick.