The rise of artificial intelligence is transforming the way we approach scientific discovery. In particular, generative AI is emerging as a powerful tool to accelerate breakthroughs, uncover hidden insights, and expand the frontiers of human knowledge. As an article from the World Economic Forum highlights, “AI for scientific discovery” is recognised as one of the top 10 emerging technologies of 2024. But what does this really mean and how will it impact the future of science and business?
One of the key benefits of generative AI is its ability to dramatically accelerate the pace of discovery. By mining vast troves of scientific literature, generating novel hypotheses, and identifying promising avenues for experimentation, AI is helping researchers make breakthroughs faster than ever before. As one technologist notes, “AI assists researchers by rapidly processing large volumes of data, identifying patterns and insights that might be missed by humans, and suggesting new hypotheses to explore.” This increased efficiency could lead to an explosion of new findings across all scientific disciplines.
But generative AI isn’t just about speed — it’s also expanding the very boundaries of scientific inquiry. As a technology that can function as a “generalist”, AI has the unique ability to make connections across specialised fields and uncover insights at the intersection of disciplines. Recent research demonstrates this potential, using generative AI to create an “ontological knowledge graph” from 1,000 scientific papers. The resulting map reveals surprising parallels, like structural similarities between biological materials and Beethoven’s 9th Symphony. By illuminating these hidden relationships, AI could inspire entirely new directions for interdisciplinary research and innovation.
Perhaps most intriguingly, generative AI can help expand the hypothesis space beyond the limits of human intuition and bias. As another technologist explains, “AI’s ability to generate hypotheses that humans might not consider can lead to truly novel advancements.” IBM’s new AI-Hilbert system takes this even further, aiming to automatically generate mathematical models that bridge gaps between theory and empirical data. As IBM states, “rather than relying solely on human imagination and serendipity to create candidate theories, AI-Hilbert directly generates new theories on demand.” Such AI-generated theories could push science in completely unexpected directions.
One area where generative AI is already having a major impact is drug discovery. By rapidly designing novel molecular structures optimised against specific diseases, AI is helping pharma companies dramatically accelerate the development of new treatments. Companies like Sakana.AI are creating “AI scientists” to fully automate the hypothesis generation, experimentation, and analysis pipeline. As they explain, aim is “a research assistant that can automatically mine literature, devise experiments, physically perform them using lab automation, and iterate 24/7 until a new scientific discovery is made.” Such a tireless and creative AI researcher could utterly transform the pace of medical breakthroughs.
So, what does all this mean for the future? In the coming years, I believe we’ll see the emergence of AI-augmented science as the new normal. Discovery will accelerate as researchers increasingly collaborate with AI to mine insights, generate hypotheses, and identify promising experiments to run. Scientific knowledge itself will evolve, as AI uncovers hidden connections between disparate fields and ideas. And the lab of the future will be a place where robotic AI systems tirelessly optimise and test new theories, working in tandem with their human counterparts.
For businesses, this AI-powered future of science holds immense opportunity — but also challenges. Companies that embrace AI-augmented R&D could dramatically accelerate product innovation and gain a significant competitive edge. From materials science to biotech to chemical engineering, the potential for AI-driven breakthroughs is immense. But firms will also need to rethink traditional approaches to research management, IP protection, and scientific talent acquisition. How do you hire for creative insight in an age of AI-generated hypotheses? How do you protect inventions when discovery is automated? Leaders will need to grapple with these questions.
Ultimately, the rise of generative AI in science represents both a tremendous opportunity and a great responsibility. The opportunity is to expand the boundaries of human knowledge and accelerate innovation for the betterment of humanity. But the responsibility is to proactively address the societal implications and ensure that AI remains a positive force for scientific progress. As we stand on the cusp of this new age of discovery, it will be up to researchers, entrepreneurs, and policymakers alike to strike the right balance and unlock the full potential of AI-augmented science. The future is wide open — it’s up to us to decide what we’ll discover.
Consider these strategic insights:
- Embrace AI-augmented R&D: Investigate opportunities to leverage generative AI to accelerate product innovation, optimise designs, and uncover breakthrough ideas in your industry vertical.
- Explore novel material innovations: As generative AI helps invent new materials with remarkable properties, look for opportunities to be an early adopter and capture market share with differentiated products.
- Rethink IP strategy for AI-generated inventions: Re-evaluate your approach to protecting intellectual property as AI contributes more heavily to new discoveries. Consider new models like defensive publication.
- Build cross-disciplinary innovation teams: Assemble small teams that combine deep experts with polymaths to mimic AI’s ability to draw novel connections across fields. Foster a culture of recombinant innovation.
- Develop an AI science talent strategy: As AI increasingly autogenerates hypotheses and runs experiments, shift your hiring to focus on creatives who can imagine novel applications and business models around new discoveries.
Signals from the future:
Emerging trends that are likely to drive changes to the way we live, work and do business.
- ‘We need to start moving people and key infrastructure away from our coasts,’ warns climate scientist — Irish Independent — Innovative coastal infrastructure solutions needed to combat rising sea levels in Ireland, urging collaboration between academia and industry for sustainable development amidst climate change challenges.
- Space mining startup AstroForge aims to launch historic asteroid-landing mission in 2025 — Space.com — Unlocking the potential of asteroid mining for sustainable resource extraction through private missions beyond Earth’s orbit.
- Knightscope autonomous robot deployed in Atlanta to detect threats — Interesting Engineering — Innovative autonomous surveillance robot deployed in Atlanta to combat crime, garnering cautious optimism and community support for enhanced public safety measures.
- Breakthrough in Sustainable Protein Production: Transforming Industrial Waste into Future Food — Impact Lab — Innovative method converts industrial waste into sustainable protein using salt-tolerant yeast, offering potential for food, feed, and fuel applications with environmental benefits.
Deep strategy:
Longer form articles rich with insights:
- Keep Strategy Simple — Harvard Business Review — Simplify strategic planning by focusing on business-level strategies, keeping formulation separate from execution for better organisational coherence and effectiveness.
- Is Your Organisational Transformation Veering Off Course? — Harvard Business Review — Monitoring and addressing emotional energy within teams can signal and prevent obstacles in organisational transformations, leading to successful change initiatives.
- The energy transition: Where are we, really? — McKinsey — In the European Union and the United States, renewable energy generation technologies, such as solar PV, onshore and offshore wind, and battery energy storage systems (BESS), have experienced rapid development, driven by supportive policies and increasing private sector investment.
- Dual transformation: Optimising the core and building new businesses — McKinsey — In this article, we outline the opportunities for leaders to realise disproportionate value for sustainable growth and describe the competitive advantages that can result from simultaneously undertaking a transformation and building new business. This approach is particularly effective when the core business or market is facing rapid decline or other significant challenges that demand immediate attention, or when there is limited cash flow to support growth and innovation initiatives.
Business at the point of impact:
Emerging issues and technology trends can change the way we work and do business.
- A board-level view of cyber resilience — McKinsey — In this interview, McKinsey’s Sean Brown speaks with Vinnie Liu, the cofounder and CEO of the cybersecurity firm Bishop Fox, and McKinsey cyber-resilience experts Justin Greis and Daniel Wallance about how boards of directors should approach oversight of cybersecurity.
- How Kroger Is Using Data And AI To Drive Innovation In The Grocery Industry — Forbes — CIO Network — Unlocking customer-centric innovation through data-driven strategies, AI optimization, and streamlined experiences in the retail industry.
- Readying business for the age of AI — MIT Technology Review — Leveraging AI in business operations requires a strategic approach, addressing data challenges, talent shortages, and ethical considerations for successful implementation.
- Approaching generative AI with a beginner’s mindset — McKinsey — Shih speaks with McKinsey senior partner Lareina Yee about the transformative power of gen AI to help accelerate workflows, the importance of change management, and the top questions business leaders are asking about AI adoption.
- Where Will Artificial Intelligence Take Us In The Future? — Forbes — AI’s future evolution may lead to AGI and quantum AI, impacting healthcare, climate management, societal regulations, economic systems, and space exploration.
- CIOs and IT leaders must be bold to gain advantage with genAI — Healthcare IT news — Embracing generative AI is crucial for CIOs to stay competitive. Aligning technology with business goals, improving data quality, and addressing talent shortages are key.
