Companies Need To Get Onboard The Generative AI Train

Beyond the confines of the World Economic Forum’s AI House, all conversations in Davos recently seemed to revolve around “GenAI,” amplified by Sam Altman, CEO of Open AI, who participated in more than two dozen sessions on the new technology.

But beyond the media frenzy, where do companies stand?

As in Davos, the enthusiasm is palpable. According to a recent BCG survey, 85% of the leaders of large companies plan to increase their AI budget in 2024. Almost all companies finally allow some use of generative AI – only half did so six months ago. The enthusiasm is reminiscent of the dot-com boom in the late 1990s, only now it’s happening even faster.

Yet, despite the excitement, implementation remains uncertain. The business world is divided into two camps: the “champions” and the “spectators.”

Only 10% of companies are champions, setting ambitious targets for productivity gains worth a billion dollars or more, which they plan to reinvest for growth. Those companies are allocating budgets to match their ambitions, generally at least $50 million per year dedicated to AI initiatives.

Many of these champions have already trained more than 25% of their teams in using AI and have begun to transform functions like marketing, customer relations, maintenance, engineering, and compliance. Yet most leaders have limited confidence in their executives’ generative AI skills. CEOs have taken the helm of generative AI strategy at 27% of companies investing over $50 million in AI this year.

Meanwhile the 90% of companies that fall into the spectator camp believe in AI, but not with their hearts. They hesitate, facing talent shortages, cybersecurity concerns, regulatory uncertainties, and have settled for small experiments. Even though the leaders of these companies estimate that they will eventually need to train nearly half of their teams to be AI literate, most have barely started.

The challenges are certainly real, but they are reasons to hurdle forward rather than hesitate. To remain competitive in the era now beginning, companies will need to continuously evolve their tech infrastructure, their organizations, their processes, and especially, the skills of their teams. Most have not yet succeeded in building this muscle.

Hesitant business leaders ought not wait too long. The gulf is widening between champions and spectators. Near-term, unlocking basic efficiencies through automating routine workflows provides the fastest, clearest ROI.

BCG estimates targeted automation could cut 20% of costs and boost productivity between 30-50% across customer service, operations, and IT. But long-term, we expect even bolder GenAI-driven disruption, from revamped business models to breakthrough products and services.

Only 19% of companies surveyed by BCG ranked cost as their top GenAI selection criteria. This suggests that the promise of tools like ChatGPT often outweighs a sober evaluation of their value. Companies should favor solutions purpose-built for their specific use cases rather than defaulting to the latest viral sensation.

Collaboration is also often overlooked, with only 3% of companies prioritizing pre-existing partnerships when procuring GenAI. Companies should actively curate ecosystems of internal developers, external vendors, researchers and consultants to successfully navigate GenAI’s uncertainties.

Yet, most companies remain stuck between GenAI’s promise and reality. Those who recognize GenAI’s permanence and actively upskill their employees, track costs, forge partnerships, and develop practical strategies are positioned to chart a course through the hype.