The state of AI: How organizations are rewiring to capture value

Organizations are starting to make organizational changes designed to generate future value from gen AI, and large companies are leading the way. The latest McKinsey Global Survey on AI finds that organizations are beginning to take steps that drive bottom-line impact.  Some of its major findings are:

Survey analyses show that a CEO’s oversight of AI governance—that is, the policies, processes, and technology necessary to develop and deploy AI systems responsibly—is one element most correlated with higher self-reported bottom-line impact from an organization’s gen AI use.   That’s particularly true at larger companies, where CEO oversight is the element with the most impact on EBIT attributable to gen AI.

The value of AI comes from rewiring how companies run, and the latest survey shows that, out of 25 attributes tested for organizations of all sizes, the redesign of workflows has the biggest effect on an organization’s ability to see EBIT impact from its use of gen AI. Organizations are beginning to reshape their workflows as they deploy gen AI.

Some essential elements for deploying AI tend to be fully or partially centralized. For risk and compliance, as well as data governance, organizations often use a fully centralized model such as a center of excellence. For tech talent and adoption of AI solutions, on the other hand, respondents most often report using a hybrid or partially centralized model, with some resources handled centrally and others distributed across functions or business units.

Organizations have employees overseeing the quality of gen AI outputs, though the extent of that oversight varies widely.

Respondents are more likely than in early 2024 to say their organizations are actively managing risks related to inaccuracy, cybersecurity, and intellectual property infringement—three of the gen-AI-related risks that respondents most commonly say have caused negative consequences for their organizations.

Most respondents have yet to see organization-wide, bottom-line impact from gen AI use—and most aren’t yet implementing the adoption and scaling practices that we know from earlier research help create value when deploying new technologies.

Respondents at larger companies are more likely than their peers at smaller organizations to report hiring a broad range of AI-related roles, with the largest gaps seen in hiring AI data scientists, machine learning engineers, and data engineers.  Many respondents also say that their organizations have reskilled portions of their workforces as part of their AI deployment over the past year and that they expect to undertake more reskilling in the years ahead.

Respondents most often report that employees are spending the time saved via automation on entirely new activities. They also often say that employees are spending more time on existing responsibilities that have not been automated. Respondents at larger organizations, however, are more likely than others to say their organizations have reduced the number of employees as a result of time saved.  Overall, though, a plurality of respondents (38 percent) whose organizations use AI predict that use of gen AI will have little effect on the size of their organization’s workforce in the next three years.

Reported use of AI increased in 2024.3 In the latest survey, 78 percent of respondents say their organizations use AI in at least one business function, up from 72 percent in early 2024 and 55 percent a year earlier (Exhibit 8). Respondents most often report using the technology in the IT and marketing and sales functions, followed by service operations.

While organizations in all sectors are most likely to use gen AI in marketing and sales, deployment within other functions varies greatly according to industry. Organizations are applying the technology where it can generate the most value—for example, service operations for media and telecommunication companies, software engineering for technology companies, and knowledge management for professional-services organizations.

Overall, respondents are also more likely than in the previous survey to say they are seeing meaningful cost reductions within the business units using gen AI.  Yet gen AI’s reported effects on bottom-line impact are not yet material at the enterprise-wide level. More than 80 percent of respondents say their organizations aren’t seeing a tangible impact on enterprise-level EBIT from their use of gen AI.

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