Ahead of her appearance at the CA Summit this month, we catch up with Authentic Innovation founder Zoë Webster to talk regulation, bias and the new skills to cultivate

Words: Lysanne Currie | Photography: David Titlow

I’ve heard it said that AI is like teenage sex,” Zoë Webster says mid-photoshoot, in a vault below London’s Waterloo station. “Everyone is talking about it, but not everyone who claims to be doing it really is.”

It’s a surprising thing for Webster to say: she has just been named by AI Magazine as one of the top 10 AI leaders in Europe and has herself been thinking about and working with the technology for more than 20 years. Thirteen of those years were spent at Innovate UK, culminating as Director of AI and Data Economy, followed by three as BT’s Director of Data and AI Solutions.

Webster left BT earlier this year to set up her own consulting company, Authentic Innovation, to help businesses think pragmatically and strategically about the use of AI. “We are in a hype cycle,” she says. “And there’s a bit of Fomo [fear of missing out] around AI. Everyone thinks everyone else is doing it and doing it at scale and getting it right – and that’s not really the case. Everyone is in the same period of uncertainty.”

There is, Webster says, something of a frenzied “where can we put AI?” theme going on in boardrooms. “But AI is one of several tools,” she says. “It can provide insight from data, it can find patterns, generate content, enable conversations between chatbot and customer – but we must use it for the right reasons.”

“Human ingenuity, empathy and working as a team will really come to the fore as AI grows – we will always need the human connection”

Since launching Authentic Innovation, Webster has been helping organisations in sectors ranging from procurement to energy to charity. She looks for the “space of opportunity” based on an organisation’s goals, then assesses options according to what it already has in place, the potential value of candidate ideas, her own practical knowledge of AI and the feasibility of execution. “Something like ChatGPT is only one possible solution,” she says. “AI is far broader.”

So how should businesses approach an AI strategy? “I first ask clients to think about their goals: what is it they want to change in the organisation? Are they looking to attract more customers or maintain the current ones? What insights would be most valuable or what questions do they have? What would you need to know about customers to speak to them in a way that resonates?”

Next, Webster looks at the available data. “AI is nothing without the data,” she says. “But there’s a lot to think through: where is the data coming from, is it representative, is it sustainable, do you have the rights over that data, could it be biased?” 

Webster next looks at what form of AI makes most sense for the particular company, being clear all the time that it is not some kind of magic bullet: “AI is not the answer to all your problems – if you have rubbish data then AI is not going to help. If, however, you want to make sense of the data you have got, and you want to get insight to make things better for your customers, for colleagues, there are a range of opportunities.”

Group think

The one thing Webster stresses to all companies is that AI adoption is not a solitary affair: “It’s a collaborative effort and it’s really important to have different skills around the table: law, marketing, HR, change management and, of course, accountancy.”

Finance professionals have understandably been anxious about the advent of AI, worrying predominantly that it will take their jobs. Webster believes strongly that the situation is, in fact, the opposite – that accountants, in particular, are crucial for the technology’s growth.

Return on investment (ROI) is one area which needs the skills and training of CAs. With organisations finding measuring ROI challenging, how best to assess AI’s value and how to account for it?

“When I did my degree I was one of two women doing computer science, but I haven’t seen radical progress. AI is still pretty male dominated”

“Sometimes it’s straightforward, say, if a company ran an AI model and attracted 5% more new business. But often it’s much more difficult to assess – for example, how it also affects productivity within wider systems and potentially impacts society more widely,” she says.

Webster adds that costs are often uncertain and accounting for innovation is inherently difficult. She also points out that AI lacks the personal touch that CAs use in business: “Human ingenuity, empathy and people working as a team will really come to the fore. We will always need the human connection. And as AI grows, these soft skills will be increasingly critical.”

Webster urges everyone to remember that AI’s knowledge can be limited. “Machines can only learn from things that are in digital form,” she says, “so unless something is in noughts and ones, they can’t learn from it. Think about all the experiences you have learnt from that are not digitised – things that have gone well or not so well that are not accessible to machines. There is so much that machines don’t know. They have harvested a lot of data but there’s a lot of knowledge and life experience that’s within us all – but not on the web.”