Generative AI has accelerated the transition towards more data-driven companies

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The generative AI opportunity is twofold. On the one hand, generative AI has unlocked a series of use cases that were not possible before, and will unlock a lot of value for companies. These new use cases include concision, copiloting, coding, and content generation. On the other hand, generative AI has also boosted awareness of AI in general, especially among the boardrooms of our clients, accelerating the transition to become data-driven companies.

I'm very excited about this last aspect, because generative AI is powering a lot of the use cases delivering value--and helping them uplift that value. For example, if we talk about personalisation, there's been a lot of work over the past few years where the mantra was, “How do we create the next-best-action engine?” It will still be driven by traditional AI, but now we can apply generative AI on top of a next-best-action model to ensure any company content pushed out is personalised on a customer-by-customer basis. So the way generative AI and traditional AI work together to uplift the value we create with AI is a very big opportunity.

We’re also very excited about the potential of generative AI in the sustainability sector. For example, we’ve been working with a sustainability-focused player to develop a use case to extract insights from structured sustainability reports of companies across the globe. This is a great innovation, because for the first time, we can examine a large number of companies through a sustainability lens without having to negotiate what information we extract.

We simply go through their websites and published reports to leverage this mass of information and understand their sustainability behavior and environmental impact. This wasn’t possible before generative AI, because it's always been difficult to process large sets of structural data.

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