The AI-plus era: The best is yet to come

This next phase of AI disruption isn’t about chatbots or text generation; it’s about AI reshaping entire scientific and industrial landscapes. We are entering the era of Frontier AI, where the intersection of AI and core scientific fields will drive the next wave of innovation. This will be the AI-Plus era.
AI + Biology: Rewriting life’s code
If you thought AI’s impact on technology was groundbreaking, its role in biology could be even bigger. AI is revolutionising biology, transforming our ability to decode, understand, and engineer biological systems. On February 19, scientists unveiled Evo2, the most powerful AI model ever created for biology. Trained on 128,000 genomes span ning the entire tree of life, Evo2 can write entire chromosomes and small genomes from scratch. More importantly, it can interpret complex DNA sequences, including ‘non-coding’ genetic regions that have long baffled scientists but are crucial for understanding disease. Scientists are exploring its use in designing microbes to break down pollutants and produce biofuels.
Meanwhile, DeepMind’s groundbreaking AI system, AlphaFold, has revolutionised drug discovery by accurately predicting protein structures. Understanding protein structure is fundamental to understanding biological function and developing new drugs. AlphaFold has dramatically accelerated drug discovery, enabling researchers to identify potential drug targets and design new therapies much faster than traditional methods.
This fusion of AI and biology has the potential to engineer synthetic life forms, optimise bio-based materials, and tackle diseases once deemed untreatable. However, ethical concerns around gene editing and data privacy must be carefully managed to ensure responsible innovation.
AI + Chemistry/Physics: Transforming material science and beyond
AI is making equally groundbreaking advances in chemistry and physics, transforming the way we discover and apply new materials. Modern technologies rely on inorganic crystals, which must be both innovative and stable to drive progress. DeepMind’s GNoME project has discovered 2.2 million new crystals, including 380,000 stable materials, which could enable superconductors, high-performance batteries, and quantum materials.
Why does this matter? Because material science is the backbone of technological advancement. The right materials can lead to safer, more efficient energy storage, stronger and lighter structures, and entirely new classes of electronics. For example, a research team at Peking University has reportedly developed a 2D transistor that claims to have shattered chip performance limits and can operate 40% faster than Intel and TSMC’s cutting-edge 3-nanometre silicon chips, while consuming 10% less energy. If true, this is a great example of how countries can disrupt the race to semiconductor leadership by changing the rules of competition.
AI + Maths: The dawn of quantum computing and mathematical discovery
The fusion of AI and mathematics is opening up entirely new frontiers. One of the most exciting is the intersection of AI and quantum computing. AI algorithms are being used to optimise quantum circuits, develop new quantum algorithms, and even design new quantum hardware. This synergy has the potential to unlock the immense computational power of quantum computers, enabling us to solve problems that are currently intractable for classical computers.
Furthermore, AI is aiding mathematical discoveries, identifying patterns in vast datasets, generating hypotheses, and accelerating research in fields like number theory and optimisation. This collaboration between AI and mathematics has the potential to accelerate progress in fields such as cryptography, optimisation, and number theory.
The era of frontier AI: Just the beginning
What we’ve seen is just the start – AI is redefining industries, economies, and scientific exploration. The AI-Plus era is about more than just algorithms; it’s about fundamentally reimagining how we discover, build, and innovate. This is an industrial revolution powered by data and algorithms.
The big question: Are we ready?
AI’s transformation is inevitable – the real question is whether we are prepared to harness its full potential. Balancing AI regulation, ethics, and talent development while making bold investments in AI-driven R&D will be crucial.
India must take decisive action to stay ahead. This requires fostering a culture of innovation and risk-taking, where big bets are placed on unlocking new capabilities. While some initiatives may fail, even a 10% success rate could dramatically alter India’s technological and developmental trajectory.
The AI-Plus strategy is already in play, offering a rare opportunity to leap ahead. India’s disruption strategy hinges on building a foundation of world-class R&D. This has to be Job #1 for the nation, as the future won’t be shaped by past success or the protection of legacy, but by those who are unburdened by it – willing to take bold risks and drive disruption.