Artificial intelligence is no longer a theoretical future scenario—it is actively changing how we discover drugs, shape care, and design entire healthcare systems. But at this crucial juncture, the challenge is not only technological: it is collaborative. Only through close cooperation between pharmaceutical companies, technology providers, regulatory authorities, payers, and healthcare organizations can the full potential of AI be realized.

At the Davos Roundtable 2026, "The Intelligent Healthcare System – Rethinking Pharmaceuticals and Healthcare for the Next Decade," we will discuss how AI shortens development cycles, enables personalized medicine, and transforms the economics of care – while addressing the structural, regulatory, and societal barriers that delay its adoption.

The development of new drugs is traditionally expensive, time-consuming, and risky. AI can accelerate these processes through deep learning models for molecular predictions, virtual screening, and generative chemistry. AI also enables the repositioning of existing drugs by analyzing data from pharmaceutical studies and scientific literature to discover new therapeutic applications. Fragmented data landscapes, regulatory hurdles, and a lack of interoperable platforms are slowing down implementation. Secure, shared data infrastructures and public-private partnerships allow AI to efficiently evaluate the efficacy and safety of molecules and bring them from research to market more quickly.

Precision medicine promises tailored therapies based on genomics, metabolic profiles, and lifestyle data. AI algorithms analyze multi-omics data, electronic health records, and wearables to identify the optimal therapy, minimize side effects, and improve treatment outcomes. Lack of data standards, digital skill gaps, and privacy concerns can lead to unequal healthcare outcomes. Interoperable, AI-driven infrastructures and clear privacy and governance frameworks ensure equitable access to personalized medicine. Scalable AI tools support medical staff while maintaining trust and transparency.

AI is revolutionizing clinical trials, medical imaging, and operational efficiency. Predictive models help identify suitable trial participants, predict patient outcomes, and minimize dropouts. In diagnostics, deep learning models enable more accurate and faster detection of diseases. AI-supported optimization of supply chains and processes significantly increases efficiency in pharmaceuticals and healthcare. Complex regulatory frameworks, isolated structures in institutions, and a shortage of skilled workers are slowing down implementation. Collaborative models between regulatory authorities, hospitals, and technology providers, supported by AI training and cross-sector initiatives, can overcome these barriers. Federated learning and privacy-friendly AI models enable the secure exchange of insights without compromising patient data.

The next ten years of healthcare innovation will not be determined by algorithms or computing power alone. They will depend on how well pharmaceutical companies, technology providers, policymakers, and patients work together. AI can only create real value if discovery, diagnostics, and care systems are integrated, ethically regulated, and accessible to all. At Merantix Momentum, we see every day that the best AI solutions emerge when different perspectives come together. For Davos 2026, our mission is clear: to transform complex AI challenges into measurable impact and make healthcare and the pharmaceutical industry more efficient, equitable, and intelligent.