As artificial intelligence (AI) redefines boundaries across various sectors, perhaps no field is witnessing a more profound shift than healthcare. From diagnostics to drug discovery, AI is not only enabling precision but also bringing a transformative mindset to the very philosophy of medical practice. The convergence of data, computing power, and innovation is reshaping healthcare delivery, and the time to capitalise on this shift is now.

Why AI Is Dominating Global Conversations

Though AI has existed for over six decades, recent breakthroughs have accelerated its potential dramatically. Six key factors have converged to ignite this revolution:

1. Data Explosion: The volume of global data is doubling every two years.
2. Computational Advancements: Processing power is increasing at an exponential rate.
3. Reduced Costs: Training AI models has become 99% cheaper over time.
4. Research Boom: AI-related academic and industrial research is soaring.
5. Massive Investments: Tech giants like Google, Meta, and Microsoft invested nearly $150 billion in AI in 2024 alone.
6. Technological Convergence: Foundational technologies are aligning to create a fertile ground for innovation.

These developments position AI as a force three times more disruptive than the internet, a tool with unmatched power to transform lives.

Healthcare: A Sector Ripe for AI Disruption

Despite healthcare’s traditionally slow digital adoption, with only around 5% of data currently digitised globally, the field is ripe for innovation. AI technologies are being rapidly deployed across the healthcare value chain:

• Prevention & Promotion: AI is enabling personalised lifestyle recommendations and predictive analytics.
• Diagnosis: From imaging to pathology, AI enhances speed and accuracy.
• Treatment & Care Delivery: AI supports clinical decision-making, robotic surgery, and even empathetic patient communication.
• Rehabilitation & Monitoring: Wearables and predictive models help track patient progress post-treatment.

Large Language Models (LLMs) such as ChatGPT have become central to this transformation. In less than two years, over 40 foundational AI models have emerged. These models are increasingly sophisticated, with studies even showing that patients sometimes find chatbot interactions more empathetic and engaging than those with humans.

Multimodal AI: Mimicking Human Reasoning

One of the most exciting developments is the rise of multimodal AI, which processes not just text but also structured data, images, audio, and video, much like how a human doctor synthesises multiple data points to reach a diagnosis.

This convergence enables AI to reason, interpret, and make informed decisions. From reading scans to analysing symptoms and lab reports together, AI is coming closer than ever to replicating human cognition in clinical settings.

The Challenges: Hallucinations & Readiness

Despite progress, challenges persist. LLMs are still prone to “hallucinations,” confidently providing incorrect information. However, methodologies like Retrieval-Augmented Generation (RAG) are helping mitigate these issues by grounding responses in factual databases.

Hospital readiness is another concern. Even globally renowned hospitals like Stanford show only about 16% preparedness for large-scale AI integration. This underscores the need for systemic infrastructure improvements and cross-sector collaboration, especially in India.

Regulating AI: A Global Imperative

Governments are catching up. The United States has issued executive orders on AI regulation, while the European Union has enacted the world’s first comprehensive AI legislation. The United Nations recently passed a resolution titled “Governing AI for Humanity,” highlighting the need for ethical and equitable deployment.

As AI becomes ubiquitous, governance frameworks must evolve to ensure safety, fairness, and accountability, especially in sensitive domains like healthcare.

Emerging Frontiers: Robotics, Autonomous Systems & AI-Generated Media

AI’s impact isn’t limited to software. It extends into physical automation:

• Humanoid Robots like Elon Musk’s Optimus Gen 2 can perform intricate motor tasks, potentially taking over repetitive clinical tasks.
• Autonomous Vehicles are already operating as “robotaxis” in the US, using 360° world-model scanning, a concept that could soon translate to smart ambulances or logistics in healthcare.
• AI-Powered Infrastructure: In fulfilment centres, shelves now move to workers. Imagine a hospital where diagnostic units move to the patient — a revolutionary shift in patient-centric design.

Furthermore, AI now has the capability to generate videos from text, with companies investing millions into text-to-video engines. Soon, entire medical education modules, patient explainer videos, or even public health campaigns could be produced with minimal human input.

India’s Opportunity and the Way Forward

India stands at a pivotal point. With the right blend of policy, innovation, and investment, we can lead the world in democratising AI in healthcare. But to do so, we need to:

• Digitise healthcare infrastructure rapidly.
• Train clinicians in AI adoption and prompt engineering.
• Encourage public-private partnerships.
• Establish concrete ethical guidelines that protect patient rights and data.
• Build indigenous AI models tailored to India’s unique healthcare challenges.

Also read: Reinventing R&D Spaces: The Role of Design in India’s Life Sciences Revolution

Ask Better Questions, Embrace the Future

In the AI era, the ability to ask the right questions will be more valuable than ever. As we integrate AI into healthcare, our collective focus must be on leveraging its full potential while maintaining compassion, safety, and trust.

Because, in the very near future, those who use AI will replace those who don’t.

Views expressed by Dr. Adapa Karthik, IAS, Secretary, Government of Punjab, at the 14th Elets Healthcare Innovation Summit & Awards.

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