McKinsey: Managing Risk Vital on GenAI Use in Public Health

McKinsey report details GenAI use cases in public health but warns strong risk management and skills development are crucial for solutions to be scaled

Diligent risk management and strategic skills building are needed if healthcare is to reap lasting benefits from AI, a new report from McKinsey concludes.

“A focus on risk management, change management and skills building is necessary not only to implement the right GenAI pilots but also to sustain value as the pilots scale,” say the report’s authors.

The study – ‘Public Health’s Inflection Point With Generative AI’ – explores how public health organisations can responsibly use GenAI to improve service delivery, bolster outbreak preparedness, accelerate R&D and enhance health outcomes for communities.  

McKinsey says that when it comes to leveraging the power of GenAI, public health leaders would do well to learn from “adjacent industries”, including life sciences and private sector healthcare delivery.

These sectors, it says, “have already begun to seize the GenAI opportunity and consider how to mitigate its inherent risks”. 

McKinsey says that GenAI is expected to deliver a global productivity lift of between 3-5% of global industry revenue (between $60-$110bn) for the pharmaceutical and medical-product industries. It adds that it is also likely to “contribute to a bigger productivity impact in healthcare than in many other industries”, because “private payers, hospitals, and physician groups have well-articulated use cases and budding adoption”.

The report outlines four strong GenAI public health use cases

  • Service delivery and operations
  • Resilience, preparedness and outbreak response
  • Product R&D
  • Foundations for public health action, including data and technology enablers, talent enablers, and policies and standards. 

McKinsey outlines GenAI public health GenAI steps 

It goes on to outline steps that public health leaders can follow to get started with GenAI. These include:

  • Identify high-impact use cases that advance existing strategic priorities
    These, it says, are use cases that can both enable the broader public health mission but also “lighthouse” use cases that can "advance existing near-term strategic priorities".
  • Assess organisational readiness to implement GenAI
    McKinsey says that to develop and scale GenAI use cases, “organisations must have the right data, technology, and talent capabilities”.
    It adds: “While it might be relatively easy to get started with a GenAI pilot from a data perspective, organisations need to ensure there is appropriate capability building and risk mitigation to support an enterprise-wide rollout”.
  • Consider risks unique to implementing GenAI in public health
    Risks, it says, include: the fairness and bias of models; privacy, IP infringement and regulatory compliance concerns; and the need for human oversight and accountability
  • Consider security implications specific to GenAI in public health
    Early adopters, says McKinsey, can look to major stakeholders in the global public health ecosystem for guidance on the responsible use of AI, and points to the World Health Organisation's six core principles aimed at protecting autonomy, providing transparency and accountability, and ensuring inclusiveness and equity.

The report’s authors conclude by saying: “GenAI is ushering in an era of boundless possibilities for public health. Many public health organisations recognise the future potential for GenAI in their missions, and want to start learning and investing, but they struggle to figure out where to start, how to manage risks, and how to navigate this fast-moving field. 

“Like their business counterparts, public health leaders across government, multilateral, and non-government organisations can benefit from a sequenced and structured approach to GenAI, tailoring as needed based on the specific context and organisational readiness.”

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