Get ready to make the most of AI

Practical applications for AI are increasing and firms need a strategy for its adoption, including knowing where to start

Rebecca Keenan, global head of intelligent automation at Expleo

By now, everyone in business is aware that data is not just a byproduct of commerce but crucial to decision-making processes. Little wonder, then, that many of us are interested in the prospect of using data to inform an artificial intelligence (AI) strategy ready to meet tomorrow’s challenges.

Company Details


Year founded: The Expleo brand was launched in 2019 after the merger of Assystem (founded in 1966) and SQS (1996).

Number of staff: 19,000+

Why it is in the news: Generative AI is only beginning to reveal its potential business uses, so there is still time to develop a strategy

But some organisations are more ready than others. For example, sectors that are notable for their use of data include automotive, life sciences, healthcare and financial services.

Partly, this is due to regulation: businesses that are required to pay strict attention to data tend to be ahead of those regulated with a lighter touch, said Rebecca Keenan, global head of intelligent automation at Expleo.

“I think it’s interesting. It can be a benefit, as you’re focused on what you’re allowed to do,” she said.

In fact, Keenan said that she has observed a key blocker to AI adoption is not knowing how to get started.

“What I’m seeing that is slowing down AI [adoption] is people don’t know where to start, or where business value is going to come from. In a sense, the potential benefit is so huge that they don’t know where to start,” she said.

And yet, now really is the time to think about it, as developments are only going to speed up, both in terms of the technology and businesses adoption.

“I think generative AI is a progression in terms of how we’re going to see projects delivered, but I think it will have a disproportionate effect on outcomes,” Keenan said.

“The impact and speed of how it’s going to change things is the issue: how we’re adopting it and how the impact will be felt, how it will change how we work, how we live. The effect on people will be astonishing, both in the workplace and outside of it. It will be game-changing,” she said.

In light of this, businesses and other organisations need to think about potential use cases, yes, but also about ensuring that both the right governance policies and underlying technical infrastructure are in place.

“Part of it is about going back to the start to develop a clear strategy, asking: ‘What is the business goal?’ You need to understand the cost of AI, the potential impact of AI, and ask if there is a simpler option, as well as ask should you do it now or wait 12 months,” she said.

The effect of AI on people will be astonishing, both in the workplace and outside of it. It will be game-changing

There can be a case for holding back if an organisation is not yet ready, either in terms of having its data in a usable state or staff readiness, but practical applications for AI are coming thick and fast.

“We’re seeing generative AI being used a lot within customer services and contact centres, both in terms of seeing the user self-serve better by talking to an intelligent chatbot and in terms of empowerment of human agents, using gen AI for hyper-personalisation, being able to look at the history of a customer,” she said.

In such an example, the contact centre must have the right data, it must be accessible to the AI, and it must be data that is allowed to be processed under regulations such as the forthcoming EU Artificial Intelligence Act. Once these are in place, an AI can then offer recommendations of action for the call centre agent or end customer, including using sentiment analysis to measure things such as frustration level.

Keenan said that Expleo is ready to work with customers to be ready with not only the technology, but also the people and the platform, leaving them in a position to use AI as a true value play.

“Data quality and availability are the biggest challenges companies are having. Typically, organisations have data silos, with data scattered across different systems that don’t talk to each other. The data quality within those systems can [also] be incomplete. Then there’s privacy and security to consider on top of that, too, GDPR and now the EU AI Act,” she said.