Venture capital spending is now overwhelmingly skewed toward artificial intelligence. In 2024 and 2025, global investors deployed between $110 billion and $130 billion into AI startups — roughly 15 times more than the $7–8 billion invested in robotics. The distribution mirrors a market where the AI leaders have already emerged, while robotics remains early in its industrial adoption cycle.
The imbalance is striking. AI investment today is concentrated among three dominant players which together control most of the compute, model access, and distribution infrastructure in the field. Meanwhile, robotics has absorbed a fraction of that capital but is beginning to convert AI’s algorithms into measurable output in logistics, manufacturing, and healthcare.
Recent usage data suggests that enthusiasm for general-purpose AI tools is flattening. According to TechCrunch, ChatGPT’s mobile-app downloads fell 8 percent month-over-month, and user time declined 22 percent between July and October 2025. Business Insider reported a 40 percent traffic drop for the AI-coding platform Lovable. These trends indicate a maturing market: the experimentation phase is ending, and investors are starting to look for real-world deployment opportunities.
The Three Winners in AI
After two years of record funding, the concentration of value in foundation models is clear:
OpenAI — backed by Microsoft; dominates commercial APIs and enterprise distribution.
Anthropic — backed by Amazon and Google; focused on alignment, compliance, and reliability for large customers.
Gemini (Google DeepMind) — integrated across Google’s search, productivity, and cloud ecosystem.
Together these firms capture the vast majority of capital inflows, training resources, and developer mindshare. The hundreds of smaller startups built around rented GPU capacity and API-based models now face margin compression and slower growth. As compute costs rise, secondary players are being priced out of the market.
Where Capital Is Still Under-Allocated
In contrast, robotics has received just one dollar for every fifteen invested in AI, despite addressing far broader categories of economic work.
Global robotics venture funding totaled about $7 billion in 2024, with a similar run-rate in 2025. Yet major rounds over the past 18 months show increasing investor conviction in physical automation:
Figure AI — Series C > $1B · Sep 2025 · Humanoid robots for logistics and manufacturing · Lead: Parkway Venture Capital (Reuters)
UBTECH Robotics — Up to $1B (Strategic Financing Credit Line) Sep 2025 Expansion of humanoid robot production and market presence, particularly in the Middle East. Infini Capital (Robot Report)
Apptronik — $350M · Feb 2025 · “Apollo” humanoid for warehouse automation · Lead: B Capital (Axios)
The Bot Company — $150M · Mar 2025 · Consumer and industrial robots · Lead: Greenoaks (Tech.eu)
ForSight Robotics — $125M · Jun 2025 · Ophthalmic surgical robots · Lead: Eclipse (Business Wire)
Capstan Medical — $110M · Dec 2024 · Cardiac-surgery robots · Lead: Eclipse (Capstan)
Dexory — $100M · Oct 2025 · Autonomous warehouse-scanning robots · Lead: Eurazeo Growth (AutomatedWarehouse)
Collaborative Robotics — $100 million · Apr 2024 · Mobile robots for logistics · Lead: General Catalyst (General Catalyst)
CaPow — Series A ($15M) · Mar 2025 · Wireless power for mobile robots · Lead: Toyota Ventures (PR)
Slip Robotics — $28M · Dec 2024 · Automated loading systems · Lead: DCVC (SLIP)
Remedy Robotics — Seed · Oct 2025 · AI-guided interventional surgery robots · Lead: DCVC (DCVC)
Grid Aero — $6M · Aug 2025 · Autonomous cargo aircraft · Lead: Calibrate (sUAS)
Together these rounds represent roughly $2.5 billion in new capital — small compared with AI’s inflows, but growing as investors look for durable, asset-based applications.
Tesla and the Risk of Optimus
Tesla’s Optimus humanoid robot program has become a defining wildcard in the sector. The company claims that its humanoid platform will eventually handle repetitive manufacturing and warehouse tasks, leveraging the same full self-driving (FSD) neural architecture that powers its vehicles.
While the company’s demonstrations have shown meaningful progress — particularly in motor control and object manipulation — the technical and financial risks remain substantial.
Unlike the transition from internal combustion to electric vehicles, humanoid robotics requires Tesla to operate in a field with high mechanical complexity, uncertain safety regulation, and extended R&D timelines. Analysts have also questioned the capital allocation strategy: if the Optimus program continues to consume resources without short-term revenue contribution, it could dilute focus from Tesla’s core automotive margins.
From an investor perspective, Optimus is a high-beta bet — potentially transformative if successful, but structurally expensive and several years from commercial viability. If it fails to achieve reliability or cost targets, it could undermine the broader case for humanoid robotics. For now, it remains more of a strategic option than a proven business line.
Why Robotics Is Next
AI has largely automated the creative and analytical layer of work — language, design, and software generation. What remains are the physical processes that underpin most of global GDP: production, logistics, construction, and healthcare.
Robotics bridges this gap. Advances in sensors, actuators, and AI-driven control systems now allow machines to operate in variable, unstructured environments. Costs are falling, and adoption is rising due to chronic labor shortages and reshoring of production.
For investors, the pattern is familiar: computation drives software, and software eventually drives automation. AI has reached the saturation point of its digital phase; robotics represents the implementation phase that follows.
Conclusion
The AI market has matured into a three-player structure commanding most of the capital and compute resources. New funding rounds are yielding diminishing returns, and consumer adoption metrics are flattening.
Robotics, by contrast, remains fragmented, under-invested, and closely tied to measurable productivity gains. It is where AI’s computational advances will translate into real economic impact.
For venture capital, the math is clear. In 2024, for every $15 invested in AI, only $1 went to robotics. That imbalance is unlikely to persist. As AI consolidates and the search for applied productivity intensifies, capital will move toward the next frontier: intelligent machines that perform work, not just describe it.
And this is why I, together with a very talented team of roboticists and clinicians, am working on Imagine Health.