The Challenge
95% of enterprise AI initiatives fail to deliver expected value. The conventional approach — pilot projects, vendor evaluations, best-practice frameworks — treats AI deployment as a technology problem. It isn’t. It’s a collaboration design problem.
Enterprise AI fails because organizations violate mathematical constraints on autonomous systems without knowing those constraints exist. They deploy AI in workflows where the mathematics guarantees failure, while ignoring workflows where success is structurally assured.
MOSAIC’s Approach
MOSAIC provides the formal framework to design human-AI collaborations that work — with computable success probabilities, not guesswork. We analyze your workflows mathematically to determine which are viable for AI deployment, which require human-AI collaboration, and which should remain human-led.
The result: AI investments that succeed because they’re designed within the boundaries the mathematics permits.
What You Get
- Workflow viability analysis with computed success probabilities
- Human-AI collaboration architecture design
- AI governance framework aligned with mathematical constraints
- Investment prioritization based on structural viability
- Implementation roadmap with measurable milestones