TLDR: A new McKinsey Global Survey on AI, published in March 2025, highlights that organizations are moving beyond AI experimentation to large-scale adoption, fundamentally redesigning workflows, elevating governance, and proactively mitigating risks to capture significant value. Over three-quarters of organizations now use AI in at least one business function, with generative AI use rapidly increasing. CEO oversight of AI governance is strongly correlated with higher bottom-line impact, particularly in larger enterprises. The report emphasizes that successful AI implementation requires a top-down, transformative approach rather than incremental, piecemeal efforts.
A recent McKinsey Global Survey on AI, titled ‘The State of AI: How Organizations Are Rewiring to Capture Value,’ released on March 12, 2025, indicates a significant shift in how businesses are approaching artificial intelligence. Organizations are transitioning from initial experimentation to widespread adoption, implementing strategic changes to unlock substantial value from AI, particularly generative AI (gen AI).
The survey, which gathered insights from 1,491 participants across 101 nations between July 16 and July 31, 2024, reveals that 78% of organizations now utilize AI in at least one business function, a notable increase from 72% in early 2024 and 55% a year prior. The adoption of generative AI has also surged, with 71% of respondents reporting regular use in at least one business function, up from 65% in early 2024. This expansion is evident across various functions, with IT, marketing and sales, product and service development, and service operations seeing the most significant growth in AI deployment.
Strategic Rewiring for Impact:
The report underscores that the true value of AI stems from ‘rewiring’ how companies operate. Out of 25 organizational attributes examined, the redesign of workflows emerged as the most impactful factor in an organization’s ability to achieve EBIT (Earnings Before Interest and Taxes) impact from gen AI. Approximately 21% of organizations using gen AI have already fundamentally redesigned at least some of their workflows.
Leadership and Governance are Paramount:
Effective AI implementation necessitates a top-down approach, with strong C-suite and board engagement. The survey found a direct correlation between a CEO’s oversight of AI governance—encompassing policies, processes, and technology for responsible AI development and deployment—and higher self-reported bottom-line impact from gen AI. This is particularly true for larger companies. While 28% of organizations report their CEO is responsible for AI governance, this figure is lower in larger organizations with over $500 million in annual revenues. On average, AI governance is a shared responsibility, with two leaders typically in charge.
Alexander Sukharevsky, Senior Partner and Global Co-leader of QuantumBlack, AI by McKinsey, commented, ‘The more we see organizations using AI, the more we recognize that it takes a top-down process to really move the needle. Effective AI implementation starts with a fully committed C-suite and, ideally, an engaged board.’ He further emphasized that achieving real value from AI requires ‘transformation, not just new technology,’ highlighting the critical role of change management and mobilization led by the C-suite.
Mitigating Risks and Building Trust:
Organizations are intensifying efforts to mitigate gen-AI-related risks. Respondents are more actively managing risks associated with inaccuracy, cybersecurity, and intellectual property infringement compared to early 2024. These three risks are among those most frequently cited as causing negative consequences for organizations. Larger organizations are more proactive in mitigating a broader range of risks, especially cybersecurity and privacy, though they show similar levels of attention to accuracy and explainability of AI outputs.
Alex Singla, also a Senior Partner and Global Co-leader of QuantumBlack, AI by McKinsey, stressed the importance of ambitious, transformative thinking: ‘It pays to think big. The organizations that are building a genuine and lasting competitive advantage from their AI efforts are the ones that are thinking in terms of wholesale transformative change that stands to alter their business models, cost structures, and revenue streams—rather than proceeding incrementally.’ He advocates for pursuing ‘end-to-end solutions to transform entire domains, rather than taking a piecemeal, use-case-by-use-case approach.’
Workforce Impact and Skill Development:
AI is reshaping workforce needs. While hiring for AI-related roles remains challenging, the difficulty has slightly eased for many positions compared to the past two years, with the exception of AI data scientists, who remain in high demand. The survey also identifies emerging risk-related roles, with 13% of organizations hiring AI compliance specialists and 6% hiring AI ethics specialists. Many organizations are also investing in reskilling their workforces, a trend expected to increase.
Regarding time saved by gen AI, employees are most often reallocating it to entirely new activities or spending more time on existing, non-automated responsibilities. However, larger organizations are more likely to report headcount reductions due to time savings, which analyses link to a significant impact on bottom-line value. Despite concerns about job displacement, a plurality of respondents (38%) anticipate little effect on workforce size in the next three years. Financial services is the only industry where a workforce reduction is more likely to be expected.
Lareina Yee, Senior Partner and McKinsey Global Institute Director, noted, ‘A common fear about the technology is that it will be a job killer… But our survey suggests that this is not necessarily the case.’ She highlighted that while some functions might see decreased headcounts, others, like software engineering and product development, anticipate increases, indicating the evolving nature of the AI revolution’s long-term workforce effects.
Value Creation and Future Outlook:
Organizations are increasingly reporting revenue increases and cost reductions within business units deploying gen AI solutions. However, enterprise-wide EBIT impact from gen AI is not yet material for over 80% of respondents, suggesting that while progress is being made at the functional level, broader organizational transformation is still in its early stages. Michael Chui, Senior Fellow at McKinsey, concluded, ‘AI only makes an impact in the real world when enterprises adapt to the new capabilities that these technologies enable.’ He emphasized the rapid pace of AI advancements and the ongoing need for enterprises to adapt to new capabilities.
Also Read:
- Navigating the AI Frontier: Reskilling for Tomorrow’s Workforce
- Cisco Study Reveals AI-Ready Enterprises Gain Significant Competitive Advantage
The report concludes that while gen AI use continues to surge, capturing meaningful bottom-line value requires organizations to follow a clear roadmap for successful implementation, including robust adoption and scaling practices, proactive risk mitigation, and continuous investment in AI talent and reskilling.
