Future of health 6 - The AI (r)evolution in health

By Ulrich Kleipaß, Karsten Neumann, Thilo Kaltenbach, Morris Hosseini and Oliver Rong

The sixth annual Roland Berger Future of health study turns the spotlight on a topic that has dominated public discourse across all areas of healthcare in recent times: artificial intelligence (AI), including generative artificial intelligence (GenAI). With healthcare systems facing pressure on multiple fronts, AI could turn out to be a game-changer, improving the quality of care and delivering economic benefits right across the sector. But will it cause a revolution or rather lead to a process of evolution? How are players applying AI technology today, and how do they see it impacting healthcare over the next five years?

To find out the answer to this question we consulted 100 Board-level executives and further professionals in a dozen countries, using a combination of detailed interviews and a broad survey of attitudes and expectations. Our conclusion? AI will cause what can best be described as a rapid evolution in healthcare – a fast-paced process of transformation that will bring substantial change but will still allow enough time for players to formulate careful strategic responses. Some areas of healthcare are already seeing rapid transformation: for example, customer service in health insurance or R&D in pharma. Other areas of healthcare are transforming more slowly: sourcing and procurement in MedTech or Therapy in hospitals.

What can AI-driven technology do?

Advancements in AI technology and the adoption of AI solutions are likely to cause a major transformation in healthcare over the next five to six years. In just the past three years, investors have injected more than USD 30 billion into healthcare AI companies, making this one of the most heavily funded sectors. By the end of the decade, the global healthcare AI market is expected to be worth up to USD 190 billion. The applications of AI in the healthcare sector range from the large language models (LLMs) and AI systems that already serve as the backbone for many healthcare-specific applications – including chatbots, image recognition, administrative tasks, data analysis, diagnostics and treatment planning – to multimodal AI healthcare models that integrate data from multiple sources such as text, images, audio, video and sensor data with the patient's history, genetic information and clinical notes, leading to more accurate diagnoses and effective treatment decisions.

Changes along the patient journey

Many companies are already more advanced in their AI journey than commonly perceived. In the survey, all respondents said that they currently used AI, with 74 percent saying that they did so frequently. However, just 15 percent say that they have at least partially employed AI solutions in their operations of AI across their company.

Most respondents believe that AI will significantly assist physicians in daily tasks. Specifically, 82 percent believe that AI will reduce decision-making time, which is particularly valuable in acute care settings. Another 72 percent view AI as a useful aid in supporting diagnostic and treatment decisions. Furthermore, 78 percent anticipate that AI will make autonomous decisions in specific areas, such as image interpretation, indicating a generally low barrier to AI making certain medical decisions.

Regional differences occur in the acceptance of AI along the patient journey, as also noted in our study Future of health 5 , with patients in the Middle East more open to ideas such as interacting with their health insurance company via a digital platform and those in Asia rather more skeptical, say.

Future challenges

Keeping up with the fast-paced process of evolution triggered by AI will be challenging for healthcare organizations. In many cases, they will need to partner up with one of the various startups, scale-ups, established tech companies and "hyper-scalers" that can provide them with dedicated solutions and infrastructure components. Many organizations have already set up such collaborations rather than trying to build AI solutions all by themselves. This can be particularly useful where the organization in question lacks the necessary infrastructure, AI expertise or data management capabilities. In the survey, less than one-third of healthcare executives considered their organization adequately prepared to gain competitive advantage from the use of GenAI: Their main concerns were a lack of technical expertise, followed by concerns over other technical and infrastructure issues.

Strategies for stakeholders

The leaders of healthcare organizations must fully embrace the reality of an AI-driven future. We suggest a number of strategies that focus on the factors under organizations' control – internal areas where they can have a tangible impact:

• Boost customer-centricity: Focus on the patient as the central figure, use AI to create tailored treatment plans and shape the patient journey, and always keep the patient outcome in mind when designing new AI-driven tools and solutions
• Think strategically: Understand the potential of AI to challenge existing ways of doing business, drive new revenue streams and create efficiencies, and do not underestimate future transformative advancements in data analytics and GenAI
• Enable the workforce: Empower the workforce with AI tools, provide tailored training and resources at all levels, and create a culture of innovation around AI that fosters collaboration and creativity
• Secure the technical foundation: Critically review the current IT infrastructure – especially the infrastructure used for handling large amounts of unstructured data and real-time analysis – and partner up with established tech companies where necessary
• Start investing now: Give yourself a competitive edge by identifying which areas of operations are most likely to benefit from AI and investing in technology in those areas, taking a long-term perspective

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