As artificial intelligence is deployed across organizations, what steps can leaders take to drive bottom-line impact? In the latest McKinsey Global Survey on AI, Senior Partners Alex Singla, Alexander Sukharevsky, Lareina Yee, and coauthors share examples: mitigate gen-AI-related risks, redesign workflows, experiment with gen AI tools, and place senior leaders in critical AI governance roles. Need to make some decisions on the AI front? Discover these insights on strategic alliances, workforce planning, technology deployment, value capture for investors, and more.
Organizations are beginning to create the structures and processes that lead to meaningful value from gen AI. While still in early days, companies are redesigning workflows, elevating governance, and mitigating more risks.
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—for example, redesigning workflows as they deploy gen AI and putting senior leaders in critical roles, such as overseeing AI governance. The findings also show that organizations are working to mitigate a growing set of gen-AI-related risks and are hiring for new AI-related roles while they retrain employees to participate in AI deployment. Companies with at least $500 million in annual revenue are changing more quickly than smaller organizations. Overall, the use of AI—that is, gen AI as well as analytical AI—continues to build momentum: More than three-quarters of respondents now say that their organizations use AI in at least one business function. The use of gen AI in particular is rapidly increasing.
How companies are organizing their gen AI deployment—and who’s in charge
Our 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.1 That’s particularly true at larger companies, where CEO oversight is the element with the most impact on EBIT attributable to gen AI. Twenty-eight percent of respondents whose organizations use AI report that their CEO is responsible for overseeing AI governance, though the share is smaller at larger organizations with $500 million or more in annual revenues, and 17 percent say AI governance is overseen by their board of directors. In many cases, AI governance is jointly owned: On average, respondents report that two leaders are in charge.
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. Twenty-one percent of respondents reporting gen AI use by their organizations say their organizations have fundamentally redesigned at least some workflows.
Organizations are selectively centralizing elements of their AI deployment
The survey findings also shed light on how organizations are structuring their AI deployment efforts. Some essential elements for deploying AI tend to be fully or partially centralized (Exhibit 1). 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—though respondents at organizations with less than $500 million in annual revenues are more likely than others to report fully centralizing these elements.
Organizations vary widely in how they monitor gen AI outputs
Organizations have employees overseeing the quality of gen AI outputs, though the extent of that oversight varies widely. Twenty-seven percent of respondents whose organizations use gen AI say that employees review all content created by gen AI before it is used—for example, before a customer sees a chatbot’s response or before an AI-generated image is used in marketing materials (Exhibit 2). A similar share says that 20 percent or less of gen-AI-produced content is checked before use. Respondents working in business, legal, and other professional services are much more likely than those in other industries to say that all outputs are reviewed.
Organizations are addressing more gen-AI-related risks
Many organizations are ramping up their efforts to mitigate gen-AI-related risks. Respondents are more likely than in early 2024 to say their organizations are actively managing risks related to inaccuracy, cybersecurity, and intellectual property infringement (Exhibit 3)—three of the gen-AI-related risks that respondents most commonly say have caused negative consequences for their organizations.
