Humanity is not operating at its peak potential. Miessler believes AI will reveal how much 'slack' exists by solving problems previously thought to be at our limits, simply by connecting disparate, long-forgotten knowledge from fields like medical research and asking the right questions.
AI models will quickly automate the majority of expert work, but they will struggle with the final, most complex 25%. For a long time, human expertise will be essential for this 'last mile,' making it the ultimate bottleneck and source of economic value.
While AI's impact on business is significant, the ultimate catalyst for market euphoria will be its application in healthcare. When AI-driven drug discovery makes 'living forever' a tangible possibility, it will unlock an unprecedented level of investor optimism.
AI models will produce a few stunning, one-off results in fields like materials science. These isolated successes will trigger an overstated hype cycle proclaiming 'science is solved,' masking the longer, more understated trend of AI's true, profound, and incremental impact on scientific discovery.
AI is developing spatial reasoning that approaches human levels. This will enable it to solve novel physics problems, leading to breakthroughs that create entirely new classes of technology, much like discoveries in the 1940s led to GPS and cell phones.
The main barrier to AI's impact is not its technical flaws but the fact that most organizations don't understand what it can actually do. Advanced features like 'deep research' and reasoning models remain unused by over 95% of professionals, leaving immense potential and competitive advantage untapped.
The internet leveled the playing field by making information accessible. AI will do the same for intelligence, making expertise a commodity. The new human differentiator will be the creativity and ability to define and solve novel, previously un-articulable problems.
The perceived limits of today's AI are not inherent to the models themselves but to our failure to build the right "agentic scaffold" around them. There's a "model capability overhang" where much more potential can be unlocked with better prompting, context engineering, and tool integrations.
While AI-driven efficiency is valuable, Mistral's CEO argues the technology's most profound impact will be accelerating fundamental R&D. By helping overcome physical constraints in fields like semiconductor manufacturing or nuclear fusion, AI unlocks entirely new technological progress and growth—a far greater prize than simple process optimization.
AI isn't just an incremental improvement; it's a reinvention of the computer. This new paradigm makes previously intractable problems—from curing cancer to eliminating fraud—solvable. This opens up an unprecedented wave of entrepreneurial opportunity to rebuild everything.
Contrary to fears of displacement, AI tools like 'AI co-scientists' amplify human ingenuity. By solving foundational problems (like protein folding) and automating tedious tasks, AI enables more researchers, even junior ones, to tackle more complex, high-level scientific challenges, accelerating discovery.