From potential to performance by design
TCS AI for Business Study–key findings for healthcare
Reimagining business with AI
Healthcare companies are seeking new ways to deliver quality care to patients, anywhere, anytime, and at affordable costs. This is creating the need for an always-on, patient-centric delivery model, which is driving healthcare players to rethink their cross-industry ecosystems. The latest advances in artificial intelligence (AI) are playing a pivotal role in healthcare transformation, allowing companies to deliver personalized care. In fact, the TCS AI for Business Study shows that over half of senior executives in healthcare are optimistic about the potential impact of AI in their organization. This report provides unique insights into how these healthcare companies are moving forward to create effective AI strategies for their enterprise. The report investigates:
- Driving factors for AI implementations in healthcare companies.
- How AI is redefining the healthcare industry.
- Emerging AI trends in customer experience.
- Evolving employee skills and roles.
- Future of AI in healthcare.
- Alignment of AI implementations with business results.
The transformative power of AI
Many healthcare executives we surveyed have a positive sentiment toward AI.
Power of AI
Power of AI
According to the study, the majority of healthcare companies are preparing for AI or have embarked on their AI journey.
- 65% are currently reworking or planning to rework their business strategy or operations.
- 91% of healthcare companies have AI implementations planned, in process, or already completed.
Yet there’s no consensus on AI adoption strategies and not enough metrics to measure success, with 65% saying they need better KPIs for their AI implementations.
Current state of AI
- 56% of corporate functions have AI implementations in process or have completed AI projects.
- 35% of corporate functions are planning AI implementations.
- Only 8% of senior healthcare executives say AI is a differentiating factor for business transformation.
What is hampering AI progress in healthcare companies?
Surveyed executives identify their main challenges
Surveyed executives identify their main challenges
Challenges around generative AI
When it comes to concerns about AI, especially with the hype around generative AI (GenAI), five strategic challenges are top of mind for healthcare companies.
- Security and privacy focus
- Increased focus on talent development and training
- Shift toward automation and efficiency
- Cultural shifts
- Reevaluation of business strategies and models
Not enough metrics for ROI
As the integration of AI into business processes accelerates, the expected financial return on such an investment becomes increasingly significant. But only 23% of healthcare companies said they have "good enough" metrics and KPIs for their current stage of AI deployments.
Without adequate KPIs for AI-enabled operations, proving ROI and getting future buy-in is challenging.
Key findings—future of AI
Most healthcare executives believe AI will augment and enhance human capabilities, enabling people to focus on higher-value activities that require creativity, empathy, and strategic thinking.
69% think human strategic decision-making and creativity will remain essential to their competitive advantage.
As AI becomes more advanced and part of “business as usual,” the role of humans in the workplace will evolve. 51% of healthcare companies expect most of their employees will be using GenAI on a daily basis in the next three years.
Innovation and revenue growth will be a focus for future AI implementations. 86% of Pacesetters in healthcare companies—the more financially successful companies we surveyed—are primarily focused on using AI to spur innovation.
TCS recommendations
Develop tools and processes to continuously improve the explainability of machine learning systems and outcomes.
Develop processes that allow you to understand, document, and monitor or mitigate bias in AI development and production.
Develop the infrastructure and processes required to enable a reasonable level of reproducibility across operations.
Provide visibility and insights into various aspects of machine learning systems and their functioning across the life cycle—data, methods, algorithms, code, model, predictions.
Develop and implement processes that improve the environmental posture of AI systems.
About the study
TCS’ Thought Leadership Institute conducted an anonymous study of approximately 1,272 senior executives with P&L responsibilities in 12 industry sectors across Asia, Europe, Nordics, LATAM, North America, and the United Kingdom and Ireland, with respondents having an annual revenue of $5 billion to $100 billion. The healthcare industry findings are based on feedback received from 80 survey respondents.
This global study examines how CEOs, LOBs, directors, and business line managers are preparing their business to be AI-ready, focusing on aspects such as their strategy around operations, talent, and future implementation plans. The study also provides best practice recommendations based on these insights.
