Companies are still increasing their investment in AI, but this money has not generally translated into improved profits. A latest McKinsey survey shows that employees generally believe that AI has enhanced efficiency, however, the proportion of companies that have truly felt the profit contribution is not high.
The survey covered 1,719 professionals and business managers worldwide. The results showed that nearly 90% of the respondents stated that their organizations have normalized the use of AI in at least one business function, and 44% indicated that they are promoting its expansion across the entire company.
Productivity improvements have become quite common.
From the perspective of user experience, 80% of respondents indicated that AI improved their personal productivity; about half believed that AI helped them make better decisions. This indicates that AI has already produced visible effects in daily work, especially in areas such as information processing, content generation, and assisted decision-making.
But on the financial front, the situation is not so optimistic. Only 37% of the respondents stated that AI has had a significant impact on earnings before interest and taxes (EBIT), and this proportion has not changed compared to a year ago.
High-return companies are reengineering their processes even more.
McKinsey defines companies that attribute at least 5% of EBIT to AI as “high performers.” These companies account for only 6% of the sample, but they exhibit clear differences in their deployment methods compared to other firms.
Nearly three-quarters of the high-performing companies stated that they have undergone fundamental reengineering of their work processes, which is a higher proportion than last year's 55%. In contrast, simply adding AI tools to existing processes is less likely to result in significant financial returns.
This means that whether the investment in AI is effective depends not only on the model, software, or computing power procurement, but also on whether the enterprise is willing to adjust its organizational division of labor, approval processes, and execution methods.
Large companies expand faster.
Enterprise size also affects the advancement speed of AI. Among companies with an annual revenue of over $1 billion, 54% have extended AI across the entire company; for smaller enterprises, this proportion is about one-third.
In terms of AI intelligent agent applications, large enterprises also experience faster expansion rates. Over the past year, the proportion of large companies that have deployed AI intelligent agents in at least one business function has increased from 27% to 40%; whereas small companies have remained at 22%.
For corporate financial officers, the message conveyed by this survey is quite clear: increasing the AI budget is not difficult in itself; the challenge lies in whether the processes need to be re-established simultaneously. If the organizational structure and working methods remain unchanged, the efficiency improvements brought about by AI may not necessarily translate into increased profits.
