Understanding AI’s potential in healthcare: progress and next steps

Artificial intelligence (AI) offers new opportunities for healthcare to improve patient care, streamline workflows, and reduce costs. From enhancing diagnostic accuracy to personalising treatments, AI is becoming an essential tool in healthcare. In this article, we’ll take a brief look at where AI stands today, what the future holds, and what reforms are needed to fully leverage its potential in healthcare.

AI’s role in healthcare: current and future outlook

AI will not replace healthcare professionals, but it will allow them to use their time more efficiently in the future. Currently, AI is used in areas such as diagnostic imaging, where AI-based tools help to detect diseases like cancer with greater accuracy and speed. AI models also analyse patient data, predict health risks and recommend early interventions, contributing to better treatment outcomes. However, AI use in healthcare is still in its early stages, and comprehensive statistics on its extent are not yet available.

As AI technology continues to evolve, its applications will expand into areas like AI-assisted surgeries and treatments that are personalised to a patient’s individual health information and needs. With its predictive capabilities, AI can help healthcare providers identify disease risks, optimise resource use and improve patient care overall.

AI has the potential to automate up to 36 % of tasks in health and social care, helping to address the anticipated shortfall of 3.5 million healthcare professionals in OECD countries by 2030.^1,2

What needs to happen next?

Despite AI’s potential, challenges remain. Data quality and integration are critical issues, especially in healthcare, where patient safety is paramount. Integration refers to combining information from different systems and sources to enable its effective use in care and decision-making. Nonetheless, the biggest challenge for AI in healthcare is not the development of advanced technologies but ensuring their adoption into daily clinical practice.³

To enable the systematic, responsible, and purposeful utilisation of AI in healthcare, the following measures are thus necessary:

1. Investment in research and development: Continued investment in AI research is essential to create healthcare-specific solutions, including algorithms that manage complex medical data.
2. Cross-sector collaboration: Effective AI implementation requires collaboration among technology developers, healthcare providers, and policymakers to share best practices and develop comprehensive integration strategies.
3. Data standardisation: AI requires standardised data to function effectively. In other words, information collected from different sources must be well-structured and compatible.
4. Regulatory frameworks: Clear guidelines are needed to ensure AI is used ethically and that patient data is protected.
5. Training and adaptation: Healthcare professionals need proper training to integrate AI tools into their workflows. This transition must be smooth to ensure that the new technology supports both professionals and patients in the best possible way.

While these measures will eventually be addressed, the process takes time. It is estimated that the adoption of AI in clinical practice will remain limited in the short term, with wider implementation expected within the next 5–10 years.^3,4

Sources:

1. Chebrolu Kumar R. (2020): Smart use of artificial intelligence in health care, Deloitte.

2. OECD (2023): Ready for the Next Crisis? Investing in Health System Resilience. OECD Health Policy Studies.

3. Davenport T, Kalakota R. (2019): The potential for artificial intelligence in healthcare. Future Healthcare Journal 6(2):94-98.

4. Bajwa et al. (2021): Artificial intelligence in healthcare: transforming the practice of medicine. Future Healthcare Journal.

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