THE FUTURE OF AI
What are the biggest barriers preventing organisations from scaling AI?
Sue Daley OBE, techUK: Skills comes up as a challenge all the time, but there are two levels to it. First, if an organisation is investing in AI solutions, do the employees actually have the skills to use it? Even back to basics: how do I write a prompt?
The other side of the skills gap is: does the UK have the people to deliver that AI to companies? AI experts, quantum engineers: what kind of skills do we need at that level?
Then there’ s data. I might have loads of data for my AI to consume, but is it good data? Rubbish data in, rubbish data out. There are still a lot of organisations struggling with that.
And the last one is trust. Can I trust this tool? We need good AI assurance – risk management approaches, auditing tools and technologies that can assure people that the AI products and services they’ re putting into their organisations are actually doing what they’ re supposed to do.
Natasha Davydova, AXA: I’ d add regulatory compliance to that. If you take the EU AI Act, for example, it requires you to explain how the decision has been made. You can’ t just push in massive datasets and ask AI to choose without being able to explain it.
“ At IBM, we’ ve taken a‘ Client Zero’ approach, using our own technologies internally before deploying them to customers”
Leon Butler, CEO UKI, IBM
At AXA, we’ ve launched AI and data academies which have several tracks of complexity depending on whether you’ re a data scientist or somebody who’ s less experienced with AI. We also work with our technology partners to create proofof-concept projects, and that actually helps quite a lot.
Vishaal Gupta, Pearson: From a customer perspective, it’ s really hard. We work with Microsoft and Google and all these companies, and there are so many options. It’ s difficult to work out what’ s actually valuable versus what’ s hype. You might not even need AI. You might need something else.
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