Future Decoded 2019: 'AI benefits' slipping away from UK businesses

Most firms don’t feel AI will improve performance, and that socioeconomic conditions aren't right

Brain with circuits in it

Businesses are failing to make the most of artificial intelligence (AI), and remain sceptical that adopting it will lead to material benefits.

Despite the UK being in a leading position to exploit technologies like AI and machine learning, the majority of organisations, 64%, don't believe AI would help to secure their future prospects in the economy.

This is in addition to only 38% of firms striving to be AI leaders, and just 24% of organisations having a concrete strategy at all, according to research by Microsoft and Goldsmiths, University of London.

The findings, disclosed at Microsoft's Future Decoded conference, reveal a juxtaposition between organisations being held back, and a handful of businesses that are running away from the pack. The businesses that have adopted meaningful AI technologies, by way of contrast, report feeling an 11.5% performance advantage.

Although there's a lot of interest and experimentation, Microsoft's head of Azure solutions architect, Kate Rosenshine suggested that companies encounter issues when taking this further.

"What organisations are starting to think about as the next step after doing AI is how do you scale this technology and how do you create enterprise-grade AI," she said.

"That touches on tools that are required, the process, but also thinking about the change in the organisation; in the people and responsibilities.

"To make that really succeed it's not just about the techies, it's about breaking the silos between the different parts of the organisation to foster that co-creation because otherwise AI doesn't really add much value, and isn't really tied directly to business outcome.

"But that takes time obviously, so it's not a change that happens overnight, it's quite different to what we've seen with traditional software development but it's going through a similar journey."

One factor behind the lack of AI adoption could be that the majority of businesses, 74%, don't feel the socioeconomic structures are ready and in place yet. This is despite the fact the UK is considered a leader in several areas; deemed among the top nations for research, entrepreneurship, investment and government readiness.

There has also been low confidence in AI to contribute to inclusivity and diversity challenges, meanwhile, with some organisations put off by the technology due to concerns around bias.

An analysis of bias recognition systems showed that there are key differences between organisations that consider their AI adoption to be 'advanced' versus those just in their experimental phases.

A majority, 56%, of companies have adopted some form of AI, but just 8% deem their technologies to be 'advanced,' with the remaining 48% still in the experimentation phases.

The research found a 40% gap in the confidence organisations have in their ability to detect biases, between those with advanced and experimental systems. This was in addition to a significant gap in an organisation's confidence in the capacity to address bias.

The research also found a significant leadership gap, with 96% of employees revealing that they have never been consulted by their boss about the introduction of AI. This works the other way too, with 83% of employees never themselves asking about AI being adopted in their organisations.

For AI adoption to be successful, according to Lloyds' head of business AI integration Abhijt Akerhar, companies need to bring along their customers, employees and shareholders all at once.

"If you want to succeed in the long-run we need to take all the stakeholders along with us," Akerhar said.

"Let's start with customers. We will have to give them confidence that we value their data privacy; that whatever we are doing we are doing it ethically and in their best interests.

"Next is taking your employees along. They are the ones who are going to live with those machine learning models, and the chatbots, so you will have to get them excited about AI and what AI can do for them. You have to do that skill-building; you will have to make your models explainable."

The final step, Akerhar added, would be to convince shareholders and board-level executives of the business benefits that pursuing such projects could bring, as well as ethical and accountability frameworks.

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