Introduction

MIT’s NANDA initiative found that a staggering 95% of AI pilot programs fail to progress. The culprit? Lack of business alignment, integration roadmaps, and disciplined execution. 

Root Causes

• AI pilots seen as vendor checkbox exercises—not tied to business goals.
• Absence of operational readiness: governance, MLOps, change management.
• Lack of executive sponsorship to fund scaling.

What Works

MIT points to teams that succeed:

1. Define clear business outcomes (e.g., 30% faster document processing)
2. Lock in operational integration and governance early
3. Secure executive buy-in and continuity

DataStunt Labs Approach

We build AI via the pilot-first model—but with discipline:

• KPI-aligned pilot charter
• Pilot includes scaling playbook (MLOps, infrastructure, accountability)
• Executives engaged from discovery through production

CTA:

Don’t let your AI pilot be a dead-end. Launch a pilot that’s built to scale.