24 Jun The Missing Element: Why AI Adoption is Lagging
Posted at 11:52h
in In the media
Written by Kiia Lang
I recently spent four days at VivaTech, a conference focused on tech developments for businesses. Across all the talks attended and conversations had in Paris, one theme emerged: companies are investing in AI technology but not one key element. The humans using it.
This hidden challenge is manifesting in five ways:
- Technology capability is running ahead of adoption. Organisations need to trust AI enough to build their operations around it, which is easier said than done when AI still makes mistakes. Responsible AI practices are starting to fill that gap, with companies investing in independent certifications, transparency reporting, and open tools to make AI systems safer and more trustworthy. Building trust takes time but fast-track adoption isn’t possible without it.
- Moving beyond personal productivity. Companies are talking about being “AI-first,” but many still use AI as a personal productivity tool rather than something that runs through the whole business. This can manifest through shadow AI: where employees use AI without the knowledge or approval of the company, creating silos of AI use. Until leaders define what AI-first means in practice and create a clear AI policy that bridges personal implementation and shared workflows, shadow AI will remain a
- AI is breaking the career ladder. As mentioned by Saadia Zahidi from WEF and a few others, Companies face tensions between short-term productivity and investing in workers long-term. While a clear majority of companies are investing in AI, far fewer are investing in training their own employees to use it. And you cannot just hire your way out of this skills deficit; training is essential regardless because without training in 10-20 years there will be nobody with the skills to fill senior positions.
- The human cost of AI productivity. In the middle of all this, workers are burning out. Their cognitive load is increasing as routine tasks are handed off to AI, best articulated by Tom Pickett, the CEO of Headspace. But what companies do with this newly freed-up time matters: often it leads to more intensive tasks or a flood of “busy work” (like extra meetings). Yet very few organisations are supporting workers through job transformation and clearly defining what is expected of workers when AI is being adopted.
- Previous career advice no longer applies. Even tech leaders cannot predict the impact of AI on work, which places education institutes and young people in a difficult position: investing in education now feels risky, but alternative paths may not be any safer. What leaders like Becky Frankiewicz from ManpowerGroup say is that curiosity, judgment, and a willingness to keep learning are becoming the most valuable skills. Unless hiring practices start reflecting these priorities, however, young workers will remain caught between the old and new paradigms.