Dare, Dare, Dare

Our latest study, “Mind the (AI) Gap,” is an invitation to use artificial intelligence audaciously.

The study initially sets out to demonstrate how the world of AI can be viewed as evolving at two different speeds. It confirms China’s lead in this domain, where 32% of companies have adopted AI, compared to 20% in European countries (France, Germany), and only 11% in Japan.

The study highlights an emerging gap between sectors vis-à-vis the adoption of AI. This represents an unquestionably new element of analysis because our previous studies – notably the latest one conducted in conjunction with MIT – showed that no identifiable sectors were trailblazers in terms of AI adoption, but instead, in each sector, there were those who displayed positive adoption rates and those who performed markedly less well.  

The sectors that have succeeded in standing out from the crowd are energy (67% of the “active players”) and above all, media, tech, and telecom companies, with 71% displaying impressive adoption rates.  

But these figures are not set in stone, and it’s not too late to get on-board.

Nowadays, it is company management that holds the key to success for the vast majority of firms. It’s at this level that the impetus must be given, and the decision to be bold should be made, both in terms of investment and resources.

Business leaders have three important topics on their agendas.

Forget detailed preliminary impact studies. You’ll just waste time. We know for sure that AI works! It is something we use on a daily basis with all of our clients. Our study shows that 75% of companies where mangers have decided to invest in AI without a preliminary impact study, are now leaders in this particular subject area.

Managers also have to break away from siloed thinking. Among the companies that have readily adopted AI, 41% understand that projects should be managed by multifunctional teams (compared to 22% for latecomers). In practical terms, for a forecasting project, it’s essential that production and business units work together. For a personalization project in a bank, both market heads and product directors should work hand in hand, in order to devise the best AI solution, going forward.

Finally, management should accelerate innovation cycles to accommodate AI initiatives. In France, Germany and Japan, cycles can fluctuate from between 10 to 13 months, compared to only 7.3 months in China. We know that two-thirds of the most innovative companies – those that plan to go from idea to prototype in 1 to 3 months – are among AI’s shining examples.

Today, daring to adopt AI isn’t really a risk. It’s a responsible choice for the growth of companies, and offers a genuine and fast return on investment. It’s imperative for those who are still slightly reluctant to take the plunge.