Companies across all industries are rapidly adopting A.I., drawn by the promise of increased productivity and reduced costs. However, more than 80 percent of businesses using the technology are not yet seeing significant earnings gains, according to a new report by McKinsey & Company published last week. McKinsey calls this the ‘‘gen A.I. paradox’’: while the use of A.I. tools is widespread, their measurable business impact remains elusive. That’s because real-world A.I. adoption lags behind the progress of the technology itself. While “agentic A.I.” today dominates discussions at industry giants like Google and OpenAI, companies that don’t build their own A.I. systems still largely operate in the “copilot” phase.
Copilots, a term popularized by Microsoft since early 2023 (shortly after the launch of ChatGPT), are designed to assist users with specific, prompt-based tasks. These tools are helpful but require human direction and can only operate within narrowly defined use cases—think Microsoft Copilot in Word, which can rephrase sentences, or a sales tool that drafts follow-up emails. Because copilots require a human to initiate each task, their value is limited to the scope of the task, such as writing faster, organizing data or summarizing meetings. These benefits are real but often difficult to quantify and rarely scale across an entire organization.
In contrast, A.I. Agents can manage entire processes autonomously from start to finish. These systems can plan, adapt to evolving conditions and datasets within enterprise workflows, and even make decisions about the next best steps. In a customer service scenario, for example, an A.I. agent could handle a customer support ticket from initial input to resolution independently, even escalating issues to a human only when necessary.
Most companies are still stuck in “pilot mode,” running small-scale experiments in isolated teams, the report said. To reap the benefits of agentic A.I., organizations must “reset their A.I. transformation approaches from scattered initiatives to strategic programs, from use cases to business processes, and from siloed A.I. teams to cross-functional transformation squads,” the consulting firm advised.
Among companies that have successfully embraced agentic A.I., the results are significant. For instance, Lenovo’s engineering teams experienced up to a 15 percent improvement in code quality and speed after implementing A.I. agents, McKinsey found in a case study. And in customer support, Lenovo’s A.I. agents resolved the majority of inbound queries, leading to a reduction in response times by up to 90 percent.
The cost of remaining in the copilot phase can be hefty. McKinsey warned that, in a world where competitors can condense a month’s worth of work into a single day using agentic systems, the cost of remaining in “pilot mode” may soon exceed the cost of doing nothing at all.
McKinsey did not disclose which specific companies were included in this report. However, it said the report was built upon an earlier study conducted this year that surveyed businesses with over 500 employees across various industries.