The GenAI Divide: Why AI Fails (and Why People Do Too)

When AI (and Humans) Add No Value

A close friend recently shared with me the MIT Project NANDA report – State of AI in Business 2025. It triggered a simple but powerful question: when does AI actually add no value to an organization?

The findings are stark. Despite $30–40 billion in enterprise AI investment, the report reveals that 95% of organizations get zero measurable return. The authors call this the GenAI Divide, where adoption is high, but transformation is almost non-existent.

When AI Adds No Value

1. When it stays at the pilot stage

Most pilots never scale. Demos impress, but only 5% of custom enterprise AI tools make it into production.

2. When tools don’t learn or adapt

The core issue isn’t model quality, regulation, or even budget; it’s the learning gap. Tools that forget context and don’t evolve remain static. For mission-critical work, 90% of users still prefer humans.

3. When AI is misaligned with workflows

Employees happily use ChatGPT or Claude for personal productivity, yet abandon corporate AI tools that feel brittle, rigid, or disconnected from the systems they actually use (ERP, CRM, approvals).

4. When investments chase visibility instead of ROI

Executives direct 50–70% of AI budgets to sales & marketing because the metrics are visible (leads, conversions). However, the study reveals that the real ROI lies in back-office automation (finance, procurement, and customer service), where organizations save millions by reducing BPO and agency spend.

5. When culture and design block adoption

The “shadow AI economy” is real: while only 40% of firms buy official subscriptions, 90% of employees use personal AI tools daily. Companies that centralize AI ownership or build everything in-house stall. Those that empower line managers and partner with trusted vendors succeed.

The Human Parallel

When I look at these five reasons why AI adds no value, I can’t help but notice how similar they are to us, humans:

1- We stay at the pilot stage How often do we start something new, a habit, a project, a change and never scale it? Excitement at the start, but no real follow-through.

2- We don’t learn or adapt Feedback is given, but we keep repeating the same mistakes. Without learning, we stagnate.

3- We misalign with our environment Sometimes, we push our ways of working without integrating into the actual culture, systems, or needs of the people around us.

4- We chase visibility instead of ROI We focus on what’s seen and celebrated titles, presentations, and social recognition instead of the quieter, more profound contributions that create real impact.

5- We block our own adoption Just like organisations, we resist change. Even when better tools or behaviours are in front of us, we default to comfort zones.

The Takeaway

The MIT study makes it clear: AI doesn’t fail because it lacks intelligence. It fails because it doesn’t learn, adapt, and integrate into workflows.

And humans? We stumble for the exact same reasons. Sometimes, we’re the ones stuck in pilots.

The GenAI Divide: State of AI in Business 2025 (great read)

https://share.google/iNeukB9Ie3taYC902

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