Global tech leaders gather at Bletchley Park to tackle barriers to AI adoption

Aiimi brought together over 100 tech and data leaders at Bletchley Park recently to discuss how businesses can tackle barriers to AI adoption. The event was hosted in partnership with Iron Mountain, and attended by senior leaders from BT Group, Citigroup, Costa Coffee, EY, easyJet, Primark, Shell, and Zoom to address challenges and best practice for AI adoption within enterprises.

Held at Bletchley Park, home of the world’s first AI Safety Summit, speakers at the event included senior leaders and industry experts. The speakers represented PwC UK, Jaguar Land Rover, the Financial Times, and PICCASO (the non-profit network for the privacy and security industry), as well as Aiimi and Iron Mountain.

Discussions centred on how dark and disorganised data poses a significant but common barrier to AI adoption for enterprises. Aiimi’s CEO and Founder, Steve Salvin, explained how the move from physical to digital information has contributed, creating “unforeseen consequences” for how we value, respect and manage data at scale. Teams that have accumulated, copied, and locked away large quantities of data in systems that don’t speak to each other have unintentionally lost sight of the information they need to make intelligent decisions, Salvin commented.

Summarising, Aiimi’s CEO and Founder said:

“Somehow we've managed to inadvertently divest our responsibility for data. I now think it's time that we change that. Restoring the value we place upon data and the respect we treat it with is a good place to start. From these foundations, companies can put in place the data governance systems needed to build a better workplace experience, realise AI ambitions, and unlock the true value stored in digital assets.”

Julia Bonder-Le Berre, Head of Global Privacy at Iron Mountain, also addressed the issue of applying AI to poorly governed data in her own keynote talk. Bonder-Le Berre likened the role of data governance in AI adoption to that of a seatbelt, explaining how it creates conditions that enable businesses to implement AI at “the maximum speed but in a safe mode”.

To help enterprises understand how to effectively govern their data for AI adoption, Chanice Henry, Group Editor at FT Longitude, unveiled new research at the event. The study of 500 large global organisations was conducted over 12 months by the Financial Times in partnership with Iron Mountain.

Talking through the findings, Henry highlighted how the most effective information management strategies prioritise “AI readiness” from the outset, are led by skilled staff with unstructured data specialists, and use AI tools to classify and consolidate data. Henry noted how businesses that automate data governance for wider AI adoption are coming “full circle” with the technology.

Speaking separately, Karl Saunt, a Partner at PwC UK specialising in Data & Analytics, agreed that “90% of the conversation … is around data” when the firm consults customers looking to adopt AI. Saunt added that “traditional approaches to data platforms probably aren’t going to cut the mustard”, and referenced the firm’s own use of Aiimi's workplace AI platform to filter and consolidate only genuinely valuable internal information.

Aiimi’s CTO, Paul Maker, also spoke about the importance of shrinking down data, aided by robust information retrieval technologies, in his talk. Maker’s talk highlighted how feeding AI applications with smaller sets of more relevant information leads to more accurate and trustworthy outputs. Calling out “Gen AI hype", Maker added that “building and training bigger models on more data is not necessarily better” - particularly if that data comes from poor quality AI outputs as this risks generating more “AI slop”.

Speaking again on a panel at the event, Maker identified the other main barrier to enterprise AI adoption: a lack of awareness and education amongst teams. “Everyone around the table needs to be more comfortable underwriting the use of AI” and “spend a bit more time at the coalface”, Maker commented.

Dave Hird, Jaguar Land Rover’s Head of Data Driven Engineering and AI, also discussed how to get buy-in for AI projects during his own keynote talk. Citing Jaguar Land Rover's own work with Aiimi to develop priority data use cases, including an AI Assistant and Knowledge Graph to help 16,000 of their employees harness knowledge from product engineering documentation, Hird highlighted the importance of focusing on specific use cases to gain buy-in.

The event highlighted the shared challenges and opportunities for AI adoption across enterprises, and a clear desire amongst tech and data leaders to build the understanding and data foundations required to navigate the technology.

Watch a summary of the event below, and access recorded sessions from the day on Aiimi's YouTube Channel.