Intelligent healthcare

Artificial intelligence holds tremendous promise for the healthcare sector, offering powerful solutions to some of its most pressing challenges, from rising patient demand and persistent workforce shortages to growing clinical and administrative backlogs.

However, fragmented implementations, difficulties in demonstrating and justifying the return on AI investments, and the need for deep cultural transformation — particularly in terms of workforce trust, training and engagement — remain common hurdles for the industry.

We surveyed over 183 senior healthcare leaders from mid-to large-sized healthcare systems (49% of which held C-suite positions) to understand the barriers that stand in the way of widespread adoption. We also looked at the opportunities that come with deploying and embedding AI across the sector.

The outcome is our ‘Intelligent healthcare’ report, a blueprint you can use to successfully deliver value with AI within your own organisation.

Read the ‘Intelligent healthcare’ report

Yusuf Ermak

Head of Public Sector Analytics

KPMG in the UK

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AI has the potential to fundamentally reshape healthcare — not by replacing the human touch, but by enhancing it. By integrating AI across different clinical and community settings and different operational streams, we can improve outcomes, ease the burden on healthcare workers, and create more resilient, patient-centred health systems.

Yusuf Ermak

Head of Public Sector Analytics, KPMG in the UK

How you can deliver value with AI

We’ve identified a framework for AI value creation based on leading practice among healthcare organisations. The framework can help you build maturity across three distinct phases. Across these, the model looks at how you can increase the maturity of your tech foundations, the use of AI in functions, and how AI is orchestrated across the enterprise.

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Phase 1: Enable your people

This phase is about enabling your people and building AI foundations. You’ll be creating an AI strategy, identifying high-value use cases, boosting AI literacy, aligning with regulations, and establishing ethical guardrails.

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Phase 2: Embed AI into workflows

The Embed phase integrates AI into end-to-end workflows, products and services. In doing so, you start to deliver greater value. Your focus should be on breaking down silos and embedding AI across your core functions. That will provide real-time insights and improve decision making. You’ll now be measuring customer satisfaction scores and speed to market as key metrics of success, alongside efficiency and cost reduction.

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Phase 3: Evolve the healthcare eco-system

During the Evolve phase, you’re forming new business models and ecosystems to solve industry-wide problems. And you’re part of an ecosystem with customers, suppliers and governments. You’re using predictive insights to deliver sustainable outcomes. AI agents are no longer inhibited by silos or organised along value streams. And real-time monitoring ensures the integrity of your platforms.