TLDR: A recent McKinsey Global Survey reveals that 71% of organizations are now regularly using generative AI (GenAI) in at least one business function, a significant increase from 33% in 2023. This surge in adoption is prompting companies, particularly larger ones, to redesign workflows, enhance governance, and address emerging risks. While most organizations are still in the early stages of realizing enterprise-wide bottom-line impact, the technology is already driving changes in revenue, cost reduction, and workforce skills, with a focus on strategic implementation and talent development.
The landscape of artificial intelligence is undergoing a rapid transformation, with generative AI (GenAI) emerging as a pivotal force in organizational strategy and operations. According to a McKinsey Global Survey conducted from July 16 to July 31, 2024, a substantial 71% of organizations are now regularly deploying GenAI in at least one business function, marking a significant leap from 33% in 2023 and 65% in early 2024. This widespread adoption signals a shift from initial experimentation to more intentional integration of GenAI across various enterprise facets.
The survey, which gathered insights from 1,491 participants across 101 nations, highlights that larger companies, those with over $500 million in annual revenues, are at the forefront of this organizational rewiring. These larger entities are more actively engaged in redesigning workflows, establishing robust governance frameworks, and proactively mitigating GenAI-related risks compared to their smaller counterparts.
Strategic Deployment and Governance: Effective GenAI implementation is increasingly seen as a top-down process, requiring strong commitment from the C-suite and an engaged board. Alexander Sukharevsky, Senior Partner and global coleader of QuantumBlack, AI by McKinsey, emphasizes that ‘getting real value out of AI requires transformation, not just new technology.’ CEO oversight of AI governance—encompassing policies, processes, and technology for responsible AI development and deployment—is strongly correlated with higher self-reported bottom-line impact from GenAI use. Approximately 28% of surveyed organizations report their CEO is responsible for AI governance, with 17% indicating board oversight. On average, two leaders are typically in charge of AI governance.
Organizations are selectively centralizing elements of their AI deployment. Risk and data governance are frequently managed through fully centralized models, such as centers of excellence. In contrast, tech talent and AI solution adoption often follow a hybrid or partially centralized model, balancing central resources with distributed functional or business unit efforts.
Impact on Workflows and Value Creation: The redesign of workflows is identified as the most significant factor influencing an organization’s ability to achieve EBIT (Earnings Before Interest and Taxes) impact from GenAI. Currently, 21% of organizations using GenAI have fundamentally redesigned at least some of their workflows. While enterprise-wide bottom-line impact is not yet material for most, with over 80% not seeing a tangible impact on EBIT, there are clear signs of value creation within specific business units. The survey indicates increasing revenue and cost reductions from GenAI use cases within deploying business units. For instance, a majority of respondents report cost reductions from GenAI in most business functions.
Risk Mitigation and Oversight: As GenAI adoption grows, so does the focus on mitigating associated risks. Organizations are intensifying efforts to manage risks related to inaccuracy, cybersecurity, and intellectual property infringement – areas that have commonly led to negative consequences. Larger organizations are particularly proactive in managing cybersecurity and privacy risks. Oversight of GenAI outputs varies, with 27% of organizations reviewing all GenAI-created content before use, while a similar percentage checks 20% or less.
Workforce Evolution and Skill Development: GenAI is reshaping the skills organizations require. While hiring for AI-related roles remains challenging, the difficulty in filling many positions has slightly eased. AI data scientists, however, continue to be in high demand, with half of respondents expecting to need more in the coming year. Organizations are also hiring for new risk-related roles, such as AI compliance specialists (13%) and AI ethics specialists (6%).
Reskilling initiatives are underway, with many organizations retraining portions of their workforces due to AI deployment and anticipating further reskilling in the future. The time saved by GenAI automation is most often being reallocated to entirely new activities or increased focus on existing, non-automated responsibilities. While a plurality (38%) expects little effect on workforce size in the next three years, some functions like service operations and supply chain management are predicted to see decreased headcounts, while IT and product development may see increases.
Lareina Yee, Senior Partner and McKinsey Global Institute director, notes that ‘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 highlights that the long-term workforce effects are still in early stages of development.
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Future Outlook: The initial excitement around GenAI is maturing into a strategic focus on value creation. Companies that are achieving competitive advantage are those pursuing ‘wholesale transformative change’ rather than incremental approaches, as advised by Alex Singla. This involves an overarching, enterprise-level vision that influences data capture, model building, and foundational infrastructure, enabling faster and more cost-effective deployment of future functionalities. The coming years will reveal how organizations that follow a clear roadmap for successful GenAI implementation will further shape the future of business.
