Humanoid robots are moving from research labs toward commercial deployment. AI is helping design new medicines and materials. Quantum computing continues its march toward practical applications. And some of AI's most influential pioneers are turning their attention toward biology, energy, healthcare and scientific discovery. 

As Alphabet's chief strategist working with moonshots including Waymo, DeepMind, Wing and Verily, I spent years inside companies attempting to build things that had never existed before. One lesson became increasingly clear to me: technological capability alone doesn't determine which breakthroughs ultimately matter. 

We tend to look at these developments separately, but they are telling us something much bigger. We are entering a new phase of innovation in which AI is no longer necessarily the destination. Increasingly, it is the catalyst. 

That creates a very different challenge for business. What matters isn't just what technology can do, but what we choose to do with it. 

AI is also accelerating abilities while technologies progress alongside it. Capabilities that once required extraordinary amounts of capital, specialized expertise, or time are becoming increasingly accessible. But making it easier to build doesn't automatically make us better at deciding what is worth building. 

That may become the defining innovation challenge of the next decade. 

The humanoid robot isn't the moonshot 

Consider the excitement around humanoid robots, as increasingly sophisticated machines capable of performing physical tasks once reserved for humans. 

That's only the technological story. 

The more interesting consideration is what becomes possible when increasingly capable robotics converges with AI, computer vision, new materials, cheaper sensors, and deep knowledge of real-world systems. The breakthrough technology matters, but the consequential innovation comes from seeing the system around the technology. 

We are entering an era of convergence 

AI isn't advancing alone. Robotics can translate digital intelligence into physical capability. Synthetic biology can turn computation into new biological possibilities. Quantum computing may eventually make previously impossible calculations feasible. Advanced materials can change what we're physically capable of producing. AI increasingly acts as an accelerant across all of them. 

The result is an expanding possibility space. The next generation of transformative companies won't necessarily be defined by owning the most powerful AI model. They'll be defined by their ability to see opportunities created between technologies, industries, systems and people that previously operated separately. 

Human ingenuity is also part of this equation. The world's knowledge about consequential problems isn't concentrated inside technology companies or research laboratories. It is distributed across industries, communities, institutions, professions and geographies:

• A manufacturing engineer understands inefficiencies embedded in physical systems that don't appear in a dataset. 
• A farmer understands constraints in a food system that an AI engineer may never encounter. 
• A nurse sees breakdowns in healthcare delivery invisible from a corporate strategy room. 
• A scientist working in one discipline may recognize an application for a technology invented in another. 

For most of history, much of that knowledge has been difficult to connect to the technologies, capital and capabilities required to act on it. That is beginning to change. 

In my new book, Invent Now: The Next Leap in Moonshots, I argue that one of the greatest innovation opportunities ahead lies in combining emerging technologies with this globally distributed, largely untapped human ingenuity. 

AI doesn't just give existing technology companies more power. Potentially, it gives far more people the ability to turn what they know into what can be built. 

From technological breakthroughs to ecosystem-scale moonshots 

This requires expanding how we think about moonshots. 

Instead of questioning what extraordinary technology can we create, we can consider: 

• What extraordinary outcome could now become possible? 
• What happens when AI, robotics, biology, advanced computing, and human expertise are brought together around food systems, healthcare, manufacturing, education, energy or infrastructure? 

Those are not simply technology problems. They are ecosystem problems. Solving them requires seeing beyond a single product, company, technology or industry. 

For business leaders, investors and entrepreneurs, this changes what innovation leadership looks like. The advantage will belong to those who can see what others don't: overlooked problems, underused assets, unexpected combinations of technologies, disconnected ecosystems and human ingenuity that has never before had the tools to act at scale. 

AI may dramatically expand what we are capable of building, but it cannot decide the ambition of what we choose to build. That's still ours. 

And that may be where the next generation of moonshots begins.

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