AI Build Lab (1 Day)

Duration

1 Day

Expected Outcomes

• Identify and validate 2-3 high-potential AI use cases grounded in real business needs, sourced directly from cross-functional collaboration

• Deliver working prototypes with real integrations and deployable functionality — not slide decks or mockups

• Surface internal AI champions and build a shared, realistic understanding of AI's impact on productivity, cost, and customer experience across the organization

Introduction

Every department in your organization has processes that are slower, more manual, or more expensive than they need to be — and the people who know this best are already in the building. The AI Build Lab puts them in a room with engineers who can actually build, and gives them a day to turn those pain points into working solutions. This isn't a lecture or a demo. Cross-functional teams whiteboard real problems, prioritize the ones worth solving, and then build functional prototypes with real data integrations and deployable output — live, in the room. By the end of the day, your organization has tangible proof of what's possible, concrete use cases worth pursuing, and a clear view of the path from prototype to production.

Scope

• Open with a focused introduction to AI-assisted development: what's now possible, what the realistic boundaries are, and how cross-functional teams unlock better use cases than engineering alone

• Form 3-4 cross-functional tables, each combining business stakeholders from Finance, HR, Legal, Marketing, Sales, and Operations with software engineers

• Guide structured whiteboarding sessions where mixed teams identify pain points, manual processes, and high-value opportunities across their business functions

• Facilitate rapid use case prioritization based on feasibility, business impact, and data availability

• Build working solutions live during the session using modern AI-assisted development tools, with senior engineers at each table ensuring production-quality architecture, real data integrations, and deployable output

• Deploy prototypes to a live environment during the session, demonstrating end-to-end functionality

• Close with a structured review where each team presents what was built, the business case behind it, and a realistic assessment of what it would take to move from prototype to production

• Deliver a post-session brief identifying the strongest use cases, recommended next steps, and an implementation roadmap tied to measurable outcomes including cost reduction, productivity gains, improved customer experience, and process automation

• Provide clear guidance on which prototypes are candidates for production implementation and what investment that requires

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