AI at Work: Why the Hype Isn't Paying Off

AI has been the talk of the town for years, but a recent study reveals a harsh truth: most companies aren't seeing any real benefits from it. In fact, 95% of businesses that have adopted AI tools report zero return on their investment. This is despite the fact that companies have spent billions of dollars developing or purchasing AI platforms in the past two years alone. The study, which surveyed hundreds of senior business leaders and employees, found that only 5% of firms have reported any return on their AI investment. The results were even more stark when broken down by industry. Only two sectors—technology and media and telecom—showed any significant changes based on the use or performance of AI. So why is AI falling short of expectations? The study identified two main reasons. First, only 5% of tools designed to fulfill specific company needs or business functions ever reach production. The rest remain stranded on the drawing board, despite developer promises. Second, many companies are using more generalist AI tools like ChatGPT or Copilot. While these tools can automate repetitive tasks, they fail to generate significant increases in key metrics like productivity, customer acquisition, or profits. The study also identified two additional divides in AI use by businesses. The first was that more than 80% of organizations have tested or piloted apps, with about half of those saying those are now being used in workplaces regularly. Startups, small companies, and midmarket businesses were found to be the fastest in that transition. But the vast majority of that experimentation and integration involved platforms like ChatGPT or other general performance AI bots. While those do often help increase individual employee productivity on certain tasks, study participants said, those gains tend to plateau fairly fast because the apps can't extend them higher. The study also found that human employees still need to oversee the tech's results, and pursue myriad business objectives that apps can't. But survey participants who faulted the limitations of general apps were even harsher with AI created for and tailored to their companies or specific business applications. So how can employers adopt AI into their operations without winding up on the wrong side of the divide? The study urges companies to build their own AI platforms whenever possible. Those apps, meanwhile, should be based on their particular business needs, which should enable them to provide better outcomes than generalist tools. When necessary, employers can turn to outside providers to design solutions for their specific uses. The report's authors also advise businesses to allow managers, and even team leaders to decide the best ways of deploying apps to get the desired results, rather than having the tech department designate a one-size-fits-all use. Over time, executives should also base evolving AI deployment on where it is creating the most profitable gains.