AI Adoption Assessment
A 5-minute diagnostic: where will your company's AI rollout stall first?
MIT's 2025 research shows 95% of enterprise AI pilots deliver no measurable results — the bottleneck isn't the model, it's organizational readiness. Enter your details to run the simulation and find where your company would stall.
- Identify the biggest risk and opportunity in your current AI journey
- Get specific recommended actions matched to your company's profile
- Understand what separates the 5% of enterprises that achieve real AI results
Six decisions. Fully anonymous. No real revenue, customer data, or confidential information required.
AI Adoption Stress Test
A 5-minute simulation: where will your company's AI rollout stall first?
Per MIT's 2025 research, about 95% of enterprise AI pilots deliver no measurable results — the blocker isn't a weak model, it's organizations and workflows not keeping up. Take 5 minutes to see where your company would stall.
MIT 2025: only about 5% of enterprise AI rollouts see real results. Want to know how your company lands in that 5%? Run the stress test.
This tool is a scenario estimate; the numbers are for decision reference only, not a guarantee of actual results, and it never asks you to enter real revenue, customer names, or confidential data.
AI Adoption Stress Test
Round 1 / 6
AI Adoption Diagnostic Report
Report summary
Diagnosis
Research support
Key signals
Recommended actions
Suggested adoption roadmap
Sovereignty and data boundaries
Deloitte 2024: data privacy is the top concern in enterprise AI adoption. Want to use AI without sending confidential data to the cloud? That's exactly the gap Omni Edge fills.
The roadmap and metrics are a scenario simulation; actual adoption still depends on your company's data, workflows, and resources. This test is not any guarantee of results or compliance.
References
Sources / research basis
The scores and report tone in this simulation are not a financial forecast, but a scenario judgment framework compiled from enterprise AI-adoption research.
- MIT NANDA (2025). MIT Media Lab NANDA project; report PDF mirror: The GenAI Divide: State of AI in Business 2025. Used for the opening 95% / 5% adoption-results gap, process integration, and contextual-learning judgments.
- Deloitte (2024). State of Ethics and Trust in Technology. Used for data privacy, transparency, data provenance, and enterprise AI risk-governance judgments.
- McKinsey & Company (2025). The state of AI in 2025: Agents, innovation, and transformation. Used to reference AI adoption rates, process redesign, and high-performing organizations.