AI is solving medical problems at unthinkable speeds, but it’s not just the pharma industry that should prepare, writes Paul Armstrong
Sure you may use ChatGPT to dot your i’s and cross your t’s, but generative AI is also rewriting the very process of discovery in local labs. The recent AI-driven breakthrough in superbug research is more than just a win for science – it signals a fundamental shift in how industries can, and will, operate. A problem that took microbiologists a decade to solve was cracked in 48 hours by Google’s ‘co-scientist’ AI. That pace of progress is not an outlier, it is the beginning of a new reality where AI-led breakthroughs will happen faster than businesses, governments and markets can react.
Medical and scientific research has traditionally followed a predictable cycle. Research teams formulate hypotheses, test theories, run experiments and refine their findings over many years. The AI-driven model tears that structure apart. The speed at which AI can generate new hypotheses and test them means that industries built around long R&D timelines are now at risk of being outpaced. Drug development, healthcare and pharmaceuticals will feel the impact first, but the shockwaves will extend far beyond the life sciences. Every business, whether it directly engages with AI or not, will be touched by the ripple effects of accelerated scientific discovery. Need a real world example? Think about the secondary effects that GLP-1 drugs like Ozempic are having already and we’re only just starting to scratch the surface.
A shift of this magnitude will change the way businesses operate, even in sectors that have nothing to do with AI or medical research. Companies have long relied on actuarial models, workforce health projections and traditional supply chain resilience to guide strategy. None of those assumptions hold if breakthroughs in longevity, disease prevention and real-time health monitoring start arriving overnight. The economic impact will be vast, from corporate insurance models being rewritten to the way companies plan for employee productivity and retirement.
The ripple effects: HR, insurance, trade
Longevity research powered by AI will force businesses to rethink how they manage their workforce in the near future. The traditional concept of career spans, retirement ages and long-term workforce planning will be thrown into question if AI – as is predicted – accelerates breakthroughs in life extension, disease prevention or just in giving more accurate knowledge of your impending doom(!). Employees will likely be at least somewhat healthier for longer, requiring companies to rethink everything from pension structures to talent retention. If retirement age extends by another decade due to AI-led health advancements, that will have profound implications on workforce dynamics, productivity and financial planning.
The insurance sector will need to move fast to keep up with AI-driven medical advancements. Actuarial models are built on historical data, but AI is rapidly reshaping the future of human health. Faster drug discoveries, personalised medicine and new treatments for chronic illnesses will likely make traditional risk calculations obsolete or become a risk for the companies that continue to use them. Insurers that fail to adapt could be caught with outdated models that no longer reflect real-world risks, leading to massive pricing errors and financial exposure. Companies that rely on long-term healthcare costs as a business risk factor may also need to adjust strategies in real time.
Global supply chains will not be immune to these shifts. A world where pandemics are solved in days rather than years will change the calculus for international trade, production and medical logistics. AI-driven health breakthroughs will influence everything from raw material demand for pharmaceuticals to the infrastructure needed for vaccine distribution. Supply chains that have spent years optimising for resilience may need to pivot to speed, ensuring they can move as quickly as the scientific discoveries that will soon shape them.
Corporate investment strategies must evolve to match the speed of AI-driven innovation. Venture capitalists and institutional investors have long assessed companies based on traditional R&D cycles. That model will really come under strain now as AI can, seemingly, cut years of at least some research down to weeks. The value of biotech firms, pharmaceutical startups and deep tech companies will shift rapidly as AI speeds up the path to market. Investors that fail to develop real-time AI foresight will risk backing companies that become obsolete before their products even launch.
The pace of AI-driven discovery is not just a challenge for industries directly tied to research and development. Businesses that fail to anticipate the next wave of AI-driven medical and scientific breakthroughs will be caught unprepared. Companies must begin developing AI-informed foresight teams that track how AI-led discoveries will affect their industries, even if they are not actively investing in AI themselves.
So, how can businesses prepare?
Leadership teams will need to change how they plan for disruption. AI-driven breakthroughs do not just change industries – they change the fundamental assumptions those industries are built on. Businesses that still rely on five-year and 10-year planning cycles will struggle in a world where AI compresses those timeframes. Leaders must shift from static strategic planning to real-time adaptability, ensuring that their companies can pivot the moment a breakthrough alters the playing field.
Ethical concerns will remain part of the discussion, but it is increasingly likely thanks to a certain fake-tanned force that the pace of AI progress is not being slowed where it matters – namely Silicon Valley or China. The real challenge for businesses is not deciding whether AI should be used – it is figuring out how to keep up with the consequences of AI-led discoveries that will reshape markets whether companies are ready or not. Regulators will move to impose AI-specific transparency rules, particularly around medical and scientific claims, but legislation will always lag behind technology. Businesses that rely on regulatory clarity before adapting to AI-driven discovery will find themselves permanently behind the curve.
So what to do? Although huge leaps have slowed, scientific breakthroughs have always been disruptive, and the current speed of AI-led innovation presents businesses with a new kind of challenge. Unlike past disruptions, which played out over decades, AI-driven advancements will increasingly unfold in mere months, forcing entire industries to react at a pace they are nowhere near accustomed to. Waiting to see how AI will affect an industry is not going to be the best option for the vast majority of eyeballs reading this now. Companies that act now and get ahead of this by developing strategies to monitor, assess and respond to AI-led discoveries will be the ones that define the next era of their industries. Develop a quarterly or at least a six-month review of what’s been released and see what’s coming – foresight, as well as partnerships, will be key here. A lot won’t be public or easily accessible, but the knowledge of what’s coming, or at least being thought about, will mean the difference from merging or being acquired for some.
The future will not be shaped by the companies that adopt AI. It’s increasingly clear that the companies that are prepared for what AI discovers next will shape more futures, not the ones who wait for the memo.
Paul Armstrong is founder of TBD Group, TBD+ and author of Disruptive Technologies