What’s been your biggest challenge in implementing practical AI solutions was it data quality, stakeholder buy-in, integration with legacy systems, or something else entirely?
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Identifying the right use case to implement a practical AI Solution followed by figuring out ROI. A business problem / opportunity can be addressed in multiple ways but is it the right fit for an AI solution to be implemented (what and the why followed by how)? The next challenge we had to solve is identifying data, ownership and quality.
Agreed, identifying the right use cases (with good ROI) for AI proof of concept should be the key challenge.
Similar to SAP data ownership…. Nobody wants to be a data owner and nobody wants to own accuracy of AI answers
For us broadly in the UK public sector- data quality, unstructured data and data silos are the biggest challenges.
One of our biggest challenges is proper scoping. It's easy to say "use AI" but defining what that actually means and implementing appropriately can be difficult. It's important to fully understand the use case before sourcing or building a solution. AI can be a great tool, but it's not always the best tool for the job.
Agreed CIndy with your point of view.
Scaling the compliance and governance processes to AI - oversight teams like legal are typically small compared to the large numbers of use cases popping up into the minds of product teams