From proof of concept to real-world impact: why so few AI projects make it across

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Our GTM Associate has loads of conversations each week with customers and prospects across lots of different industries. The details change but one challenge keeps coming up.

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It's the jump from proof of concept to a scaled system that delivers real-world impact.

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Getting a test up and running is the easy bit. The hard part is turning it into something thousands of employees use day to day. That gap is big, and not many teams are making it across.

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The good news is that advances in AI coding mean we can move into scaled systems much faster than we could even a short while ago. Getting from prototype to production and delivering value along the way, is quicker than it used to be.

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Faster doesn't mean effortless. Scaling a system still takes real expertise and that's the main thing standing between a promising test and something people rely on.

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AI coding tools can shorten the journey, but you still need people who know how to build, deploy and support something at scale. That's where we spend a lot of our time at Passion Labs, helping teams get their proof of concept out of the test phase and into the hands of the people who need it.

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