Why AI Projects in Insurance Keep Failing

The 3 Reasons Projects Fail:

1. AI Projects are very complex and expensive: To be successful, you have to start with the data and work your way forward.  This requires deep data expertise and cross functional communication and usually outside experts to get it right.  This can be very expensive – millions of dollars.
2. AI initiatives take forever to deliver anything:  Because of the complexity, delays are inevitable.  These projects can take years (and 95% fail).  It is easy to lose focus and political will over this long period.
3. You don’t know what you’re actually buying: When you start you may have a grand vision, but when it gets hard, most will cut the scope, change the timeline and bring in expensive consultants (initial estimate → endless “phases” + consulting). Executives can’t answer: What do we get? When do we see ROI? What’s the real price? Result: project fails after massive time and money spent with no real results.

The root cause?

Most AI arrives as fragile, custom projects — not as robust, repeatable systems. Insurance needs an AI-native foundation built from day one, not more fragile experiments.

How Does Moneo Change the Game?

By Design, We Eliminated Every Structural Risk.

• Defined timelines → no multi-year black holes
• Defined product & outcomes → crystal-clear value, no vague promises
• Fixed price → predictable spend, zero surprises
• Enterprise-ready from launch → built to handle full insurance complexity
• Native & embedded → scales instantly across the org, no pilot-to-graveyard cycle

This isn’t “AI someday.” This is AI at scale. Instantly.

Finally: Moneo delivers AI Without the Risk Defined outcomes. Defined costs. Defined timelines. Real AI that works – in the real insurance world.

AI at scale. Instantly.