The rapid emergence of generative AI is reshaping the healthcare landscape, with leading organisations moving from exploration to full-scale implementation. According to recent research from McKinsey & Company, 85% of healthcare stakeholders surveyed are either pursuing or have already adopted generative AI solutions. This widespread interest reflects a growing recognition of the technology’s potential to unlock operational efficiencies, improve patient experiences and drive clinical productivity. As health systems, payers and technology providers consider how to maximise generative AI’s value, McKinsey’s survey of 150 U. S. healthcare executives offers key insights into their strategies, priorities and expectations.
Growing Momentum: From Exploration to Execution
The transition from experimentation to implementation marks a turning point in generative AI adoption across the healthcare sector. While some organisations remain in the proof-of-concept stage, most are advancing toward integrated solutions. According to McKinsey’s Q4 2024 survey, the proportion of respondents actively deploying generative AI exceeds those still exploring or waiting for results from others. This shift suggests that early adopters are beginning to realise tangible benefits from their investments and are expanding their AI capabilities accordingly.
Notably, only 15% of surveyed organisations had not yet begun to develop proof-of-concept use cases. This group risks falling behind as competitors accelerate development and deployment. Health systems and payers are particularly active, with many already demonstrating implementation at scale. Healthcare services and technology groups are also progressing, though at a slightly slower pace. This growing momentum reflects increasing confidence in generative AI's potential and a willingness to invest in its strategic application.
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The evidence points to a broader trend: generative AI is no longer seen as an experimental frontier but as a viable tool for operational transformation. For organisations that have taken early steps, the opportunity now lies in scaling use cases, integrating AI into workflows and quantifying the return on investment to justify further expansion.
Partnerships as Catalysts: Building Capabilities Through Collaboration
Given the technical and organisational complexity of generative AI, most healthcare leaders are not going it alone. Instead, partnerships have emerged as the preferred approach to adoption. Among survey respondents already implementing generative AI, 61% reported that partnering with third-party vendors to co-develop tailored solutions was their primary strategy. By contrast, only 20% preferred to build in-house capabilities, and 19% opted to purchase off-the-shelf tools.
Within these partnerships, existing IT solution providers remain the most common collaborators, reflecting the value of leveraging established relationships. However, hyperscalers—large cloud and data management firms—are also playing an increasingly important role, cited by 46% of respondents. These vendors offer essential infrastructure and data expertise that can support scalable, secure and efficient AI deployment.
The preference for partnerships highlights several key factors in generative AI implementation: flexibility, speed and access to specialised talent. By collaborating with experienced partners, healthcare organisations can bypass internal capability gaps and accelerate time to value. Moreover, working with hyperscalers may enable better handling of sensitive healthcare data and ensure compliance with emerging regulatory standards.
This model of collaborative innovation appears to offer a pragmatic path forward for healthcare leaders seeking to integrate AI while managing cost, risk and complexity. It also reinforces the importance of ecosystem thinking—recognising that healthcare transformation through AI depends on coordinated efforts across stakeholders.
Unlocking Value: Use Cases and Measurable Impact
The scope of generative AI in healthcare is both broad and promising. Across all subsectors surveyed, the greatest perceived potential lies in improving administrative efficiency and enhancing clinical productivity. These use cases are already delivering results in areas such as automating documentation, assisting with prior authorisation processes, and converting unstructured clinical notes into structured data for electronic medical records.
Patient or member engagement also emerged as a key opportunity, including applications such as hyperpersonalised outreach and real-time support tools. IT and infrastructure improvements—such as code generation and system modernisation—were also seen as areas of significant potential, particularly for healthcare services and technology groups.
As adoption progresses, many organisations are also focused on quantifying their return on investment. Of those that have implemented generative AI use cases, 64% reported realising or expecting a positive ROI. A meaningful proportion indicated returns of two to four times their investment, while a smaller subset cited even greater gains. These findings suggest that well-targeted generative AI initiatives can deliver measurable value, supporting both efficiency gains and strategic growth.
While ROI varies across organisations, the survey findings underline a key takeaway: success depends on how generative AI is applied. Strategic alignment, governance and delivery capability all play crucial roles in determining the impact of technology. As healthcare leaders mature their AI capabilities, expanding use cases into quality-of-care, research and patient-facing applications could further amplify benefits.
Generative AI is no longer a speculative technology in healthcare. As illustrated by McKinsey’s comprehensive survey of sector leaders, it is a growing force for operational transformation, clinical support and stakeholder engagement. The organisations that are advancing most rapidly are those pairing strategic intent with strong execution—whether by leveraging external partnerships or by embedding AI into high-value functions.
The path forward will require careful navigation of risk, governance and capability gaps. Nevertheless, the early outcomes point to a high-value future for generative AI in healthcare. As more organisations measure their success and expand their implementations, the technology’s role is likely to deepen, reshaping not only how healthcare is delivered but also how it is experienced by patients, clinicians and systems.
Source: McKinsey
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