AI tools aren't making much of a difference for companies

"Enterprise-level AI systems aren't doing a lot to impress either. While 60% of the enterprise companies that the researchers spoke with said they evaluated these tools, only 20% made it as far as the pilot stage. And just 5% took those to a full production model. A lack of contextual learning, brittle workflows, and misalignment with day-to-day operations were cited as the chief reasons the tools were rejected."

"Behavioral researcher BetterUp Labs, in collaboration with the Stanford Social Media Lab, says it has identified one possible reason enterprise companies are rejecting AI: slop. Employees, the two labs say, are using AI tools to create low-effort, passable-looking work. They've taken to calling this "workslop"-well-formatted slides, reports, summaries, or code that might seem helpful at first, but that ultimately"

""Just 5% of integrated AI pilots are extracting millions in value, while the vast majority remain stuck with no measurable P&L [profit and loss] impact," the report reads. "This divide does not seem to be driven by model quality or regulation, but seems to be determined by approach.""

Enterprise investments in generative AI reached as much as $40 billion, yet 95% of organizations have seen no return on investment so far. Only about 5% of integrated AI pilots are extracting millions in value, while the vast majority show no measurable P&L impact. Widely tested tools such as ChatGPT and Copilot often boost individual productivity but deliver little measurable effect on overall profit and loss. Sixty percent of large companies evaluate enterprise AI systems, twenty percent reach pilot stage, and five percent enter full production. Rejection reasons include lack of contextual learning, brittle workflows, and misalignment with day-to-day operations. Employees sometimes produce "workslop"—low-effort, passable outputs that undermine long-term value.

Read at Fast Company