Accenture, a global technology consulting firm, has undoubtedly caught the generative AI bug bad. As it spends $3 billion in its capabilities, it expects to increase the number of data and AI professionals it employs from 40,000 to 80,000 over the next few years.

All of this is done to increase its capacity to use AI in three ways: to provide better services to clients, to enhance internal processes, and to change how it works with clients.

I recently reconnected with Paul Daugherty from Accenture. I had the chance to interview him about the changes that have occurred since the publication of his book Human + Machine: Reimagining Work in the Age of AI five years ago. We also discussed how ChatGPT and other generative tools would impact the continuing AI-driven transformation of businesses.

Daugherty claims, “I’ve been really amazed by technology four times over the course of my career.”

The first was the Lisa, a pioneering Apple machine that helped popularise the notion of a graphical user interface for personal computers. The second involved first-time internet browsing. The introduction of smartphones was the third.

“The fourth was around 18 months ago when I first noticed development, particularly with large language models (LLMs).

The rate of development was “becoming breathtaking,” and some skills included the ability to grasp language and the ability to generate content. In terms of the effect on business, it really is game-changing, not simply to diagnose, analyse, or anticipate.

Paul continues to observe organisations struggling to determine how and where to apply technology, despite how amazing it surely can be. They frequently don’t struggle to find use cases because there are so many of them. Instead, difficulties arise when determining which ones are most likely to aid in the achievement of company objectives and where investment should be prioritised.

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