AI-first is not a strategy. It’s how the next generation of pharmaceuticals will operate

An Expert View from Ramji Vasudevan, head of life sciences, Altimetrik.

Two years might not sound like much in pharmaceutical terms, but the boardroom conversations I’m having today would be unrecognizable to the ones I was having back then. Back then, we used to spend hours debating slide decks about the next therapeutic breakthrough. Now, the question is stark and immediate: Will we steer the ship in this AI wave or get swept under its wake? Some of the sharper pharma executives I know have started to call this moment the Intelligence economy. They’re not wrong.

The strategic inflection point

Heading up Altimetrik’s Life Sciences division has given me a front-row seat to witness AI adoption evolve from experimental curiosity to competitive necessity. McKinsey reports that 72% of enterprises now deploy AI, with half implementing it across multiple functions. But here’s what caught my attention - only 1% of CEOs say their firms have mastered the technology. But here’s what caught my attention - only 1% of CEOs say their firms have mastered the technology.

This gap represents the biggest strategic opportunity for pharmaceutical companies in our generation. While competitors are still running AI pilots and testing proof-of-concepts in isolated R&D labs, the pharmaceutical companies that will matter tomorrow are making a strategic choice about how deeply AI integrates into their operations. Some organisations are taking an enhancement approach; strategically embedding AI into existing workflows to amplify current capabilities in drug development, manufacturing and commercial operations. Others are redesigning core processes around intelligent systems that learn, adapt and accelerate innovation across the entire value chain. Both paths can work, but the key is committing to AI as a strategic foundation rather than treating it as an optional add-on.

At Altimetrik, we have transformed ourselves into an AI-First organisation. Not because it is trendy, but because it was inevitable in an industry facing rising R&D costs and increasing regulatory scrutiny.

Beyond digital: The intelligence imperative

After spending a decade guiding pharmaceutical companies through digital transformation, I've realized that digital maturity without AI is like constructing a state-of-the-art laboratory, but forgetting to use it to accelerate the discovery of life-saving compounds. The infrastructure is there, but the therapeutic breakthroughs never arrive.

It’s clear that business transformation is still needed with AI as a critical element. For example, a common scenario I see in pharmaceutical manufacturing is when drug test results are shared via email attachments and PDFs between contract manufacturers and testing laboratories. These documents often contain handwritten notes that get scanned into PDFs.

Then someone else has to manually type out the handwritten notes to enter them into their own system. It’s slow and prone to errors.

Rather than attempting wholesale digital transformation, focus on bolt-on solutions that don’t require overhauling entire systems. The document processing example above, for instance, doesn’t need any fundamental new system. It can be a bolt-on utilizing the advantages of AI.

Merck & Co (NYSE: MRK) and McKinsey co-developed a platform that generates clinical study reports. It reduced the time to produce a first draft from 180 hours to 80 hours while cutting the number of errors in half. It’s a clear opportunity for AI augmentation without requiring complete infrastructure replacement.

This realization pushed us to create ALTI Lab, our internal AI innovation engine. Unlike traditional centers of excellence that focus on governance and best practices, ALTI Lab operates more like what I call a "pharmaceutical innovation accelerator". It’s where we run rapid experiments across the full spectrum of pharmaceutical operations – from drug discovery and clinical development to manufacturing optimization, supply chain intelligence and commercial analytics. We benchmark different models and develop accelerators that actually work in real world pharmaceutical environments, whether that’s a research lab, a manufacturing facility or a commercial team. The results speak volumes: we've reduced time-to-value for AI initiatives by over 30% which means we’re getting meaningful results faster than we ever thought possible. This means pharmaceutical companies can identify viable therapeutics faster than traditional methods ever allowed.

The leadership challenge: culture over technology in pharma

The most profound insight from our AI-First journey has nothing to do with algorithms or computing power. It’s about people and culture within the unique constraints of pharmaceutical operations. BCG research reveals that employees using generative AI save at least five hours weekly, redirecting that time toward complex, high-value work. But, realizing this potential isn’t just about deploying new tools; it means completely reimagining how drug development is done while maintaining rigorous safety and compliance standards.

At Altimetrik, we've restructured roles, retrained our people and rebuilt entire teams around AI-enhanced capabilities. Research scientists designing compounds can now design entire architectures. Clinical researchers are predicting drug efficacy and safety profiles almost as fast as they can think of the questions.

This transformation revealed a critical leadership principle: pharmaceutical professionals are often more prepared for AI adoption than their leaders assumed they would be. A McKinsey study found that employees are often more ready for AI than leaders realize. This is fundamentally a leadership moment. Effective leadership in the age of AI-driven pharma means understanding and integrating AI into the core of how we develop drugs, ensure patient safety and navigate regulatory pathways.

The competitive edge of intelligence

Gartner predicts that by 2026, over 80% of enterprises will deploy generative AI. This statistic should alarm every pharma CEO, not because AI adoption is accelerating, but because it signals the commoditization of basic AI capabilities. Our approach centers on what I call "end-to-end pharmaceutical intelligence" the ability to quickly prototype AI solutions across any part of the AI value chain, validate what works in clinical settings and real operational environments and then scale those solutions globally. This might mean accelerating drug discovery in research labs, optimizing yield and quality in manufacturing facilities, enhancing patient engagement in commercial operations or streamlining regulatory processes across multiple markets. The competitive advantage lies in speed of implementation and breadth of application across all pharmaceutical functions.

The next transformative wave is already building momentum in pharmaceuticals. 2025 brings the emergence of agentic AI systems that can execute complex, multi-step drug development projects with minimal human oversight while maintaining regulatory compliance. While traditional AI assistants operate reactively, waiting for explicit instructions, these advanced agents demonstrate proactive intelligence across all pharmaceutical operations. In research, they identify promising drug targets and optimize clinical trials designs. In manufacturing, they predict equipment failures and automatically adjust production parameters to maintain quality. And, within commercial environments, they anticipate market shifts, identify new patient populations and optimize pricing strategies.

The leadership call to action

To my fellow pharma leaders, the choice is binary: lead the Intelligence Economy or be disrupted by biotech startups that are AI-native from day one. The pharmaceutical industry faces unprecedented challenges – patent cliffs losing billions in revenue, R&D costs escalating and increasing pressure for personalized medicine and real-world evidence. AI isn't just an opportunity; it's the strategic capability that will determine which pharmaceutical companies thrive in the next decade.