Enterprise GenAI pilots still struggle to deliver ROI, MIT says
A widely discussed MIT report argues that most enterprise GenAI pilots are failing to produce measurable returns, with integration and process fit emerging as the key issues.
A recent MIT report has reignited debate over why so many enterprise GenAI pilots fail to deliver ROI. The core message is not that AI is ineffective, but that many projects stall because they are not deeply integrated into real business processes, lack customization, and do not improve over time.
What changed. The conversation is moving away from model hype and toward whether AI systems are actually embedded into workflows that matter.
Why it matters. For agentic systems, success depends on end-to-end task completion, exception handling, and measurable business impact, not just promising demos.
Builder takeaway. Evaluate agents on process outcomes, error recovery, and human handoff quality, and keep iterating them against real production data.