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Five steps for companies to make AI pilots a success

Source | blogs.lse.ac.uk| Terence Tse | Dilpreet Sall | Mark Esposito | Danny Goh

The pandemic has made the need for organisations to digitise and increase technology adoption even more urgent. More and more companies are turning to artificial intelligence for help in their processes. But how can managers ensure that they go about it in the most effective way possible? Terence Tse, Dilpreet Sall, Mark Esposito and Danny Goh created a five-step methodology to improve the odds of success in AI adoption.

It’s really unsurprising to see the pandemic has driven many companies to redouble their digital transformation efforts, with automating costly labour-intensive processes as a key immediate initiative. Among the different routes to automation, an increasing number of businesses is looking at artificial intelligence (AI) to help. While the media are more attracted by the shiny benefits brought by the latest AI technology, getting value out of it demands more than just understanding how it works.

Why pilots don’t always succeed 

The beginning to a full AI solution is often establishing a proof of concept or pilot project. Yet, many of these first attempts end up in failure. Why? One reason is simply picking the wrong opportunities for first tries. Modern companies’ processes are often complex, thereby offering many possibilities for automation. But which one to work on? Placing bets on the wrong cases is essentially setting up for failure.

To complicate matters further, even with the opportunities with the greatest potential identified, pilots can easily get stuck in the planning stage. IT teams often face pressure to ensure initial pilot projects succeed to be able to secure funding for full implementation later. While such financial prudence is commendable, it can lead the teams to spend months on planning a pilot. They would be better served by getting started with testing the feasibility of the technology.

But sometimes even if IT teams manage to get the pilot launched and the technical feasibility conducted shows promise, they are set back by many unforeseen challenges that emerge along the way to implementation that add integration complexities, incur high maintenance costs and demand excessive business process reengineering.

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Source
blogs.lse.ac.uk
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