“Technology is transforming everything” has become a cliché. But behind the common phrase is a concrete thesis —with figures— that is starting to gain ground: between 2025 and 2035, ten technological platforms could generate between 6 and 8 trillion dollars, more than the combined GDP of Japan and Germany. The idea, formulated by Patricio Hunt in an opinion article published in Expansión, is that there isn’t just one revolution, but ten occurring simultaneously: artificial intelligence, robotics, autonomous vehicles, mixed reality, drones, satellites, humanoid robots, quantum computing, wearables, and brain-computer interfaces. The difference between getting ahead or going late, he argues, will be enormous.
The core argument boils down to two words: timing and infrastructure. The former determines who captures value (those who ride the wave; not those who watch it break). The latter requires looking less at standalone “gadgets” and more at platforms capable of attracting an ecosystem around them.
From the cliché to the numbers: 6–8 “trillions” in ten years
The alignment of these pieces is what draws attention. In the next decade, we will see the convergence of technological maturity, critical mass of data, decreasing costs of computing and sensors, and an investment appetite that, according to the author, is already evident on Wall Street, Silicon Valley, and . In this context, the ten technological platforms do not advance separately: they multiply each other. AI accelerates robot design; drones depend on edge computing and satellite connectivity; mixed reality and wearables push new interfaces; quantum computing promises to solve optimization problems that unlock currently unviable use cases.
The consequence: 6–8 trillion dollars between 2025 and 2035. This isn’t just an estimate of “benefits,” but of added economic value from platforms that scale (grow and attract ecosystems) when their combination of dedicated hardware, specialized software, and network capacity comes together.
The ten drivers, summarized briefly
1) Artificial Intelligence (AI). The first major “wave” visible now. Agents and models capable of acting on legacy systems (browsers, ERPs, workflows) already generate billions in productivity. Simultaneously, AI is embedding itself in almost everything else on this list.
2) Industrial robotics. After decades of incremental improvements, the combination of artificial vision, haptic grippers, AI for planning, and lower costs of actuators introduces a new generation of flexible and reprogrammable robots for production lines, logistics, or agriculture.
3) Autonomous vehicles. The second wave, along with virtual/a Augmented reality, which according to the author will “explode” between 2027 and 2032. Autonomy scales with cheaper sensors, more accurate maps, and models that generalize traffic conditions better.
4) Mixed reality (AR/VR). Moving beyond “headsets” for gaming, to integration in training, remote maintenance, telemedicine, or design. The key is productivity, not just technological demos.
5) Drones. Greater autonomy and safety; delivery services, infrastructure inspection, precision agriculture. They depend directly on embedded AI and satellite/5G networks.
6) Satellites. Constellations in low Earth orbit that reduce latency, lower bandwidth costs, and enable near-real-time operations (observation, rural connectivity, global IoT).
7) Humanoid robots. Still emerging, but with platform-like dynamics: if they can solve mobility, grasping, and safe interaction, they will take on tasks today reserved for humans in logistics, service, or maintenance.
8) Quantum computing. The horizon of the 2030s for many use cases, with specific windows earlier: materials chemistry, optimization, quantum machine learning. It does not replace classical AI, but complements it.
9) Wearables. From pedometers to clinically useful health sensors, with increased privacy and local processing. They drive new interfaces and biomarker monitoring.
10) Brain-Computer Interfaces (BCI). Still niche, but with potential in rehabilitation, assistive communication, and later, high-precision interfaces for critical professions.
“It’s not a revolution: it’s ten at once.” Why timing matters
The author’s operational thesis is that the return is not linear: those who invested early in the smartphone wave —another compounder platform— achieved returns up to 1,000% higher than latecomers. In this new cycle, we can distinguish waves:
- First wave: AI agents and industrial robotics (already monetizing).
- Second wave: autonomous vehicles and mixed reality (window 2027–2032).
- Third and fourth waves: quantum, humanoids, and BCI (deep disruptions already in the 2030s).
In each wave, the value capture rewards those who position themselves before the broad traction. That’s why, he emphasizes, it’s not just about jumping on “the wave”, but about anticipating it.
Focusing on platforms, not “gadgets”: the proof of the ecosystem
A compounder platform combines:
- Dedicated hardware (sensors, actuators, chips, devices).
- Specialized software (models, runtimes, SDKs, stacks).
- Potential ecosystem (developers, partners, marketplaces, standards).
The key question when evaluating an opportunity, according to Hunt, is not “Is it a good technology?”, but “Will it create an ecosystem or is it just a component?”. Platforms that bring in third parties tend to accelerate their own demand; isolated components do not.
From thesis to portfolio: a framework for asset allocation
The article suggests a framework of exposure that is not investment advice, but a guide for diversification:
- 60% in public markets (stocks and ETFs), to capture liquid value and platforms already in scale.
- 40% in private equity, where early-stage funding rounds reside and offer optionality over several years.
Within the public segment, a distribution by maturity is recommended:
- 50% in Tier 1: AI, robotics, drones.
- 35% in Tier 2: autonomous vehicles, AR/VR.
- 15% in Tier 3–4: quantum, humanoids, BCI.
The logic behind these percentages is straightforward: expose yourself to what is already gaining traction, maintain conviction in the next wave, and plant seeds— with smaller bets— in longer-term technologies.
Geography: platform advantage, not just technology
Another less-discussed point is the geographic factor. The advantage will not solely be technological, but also of the national ecosystem:
- USA leads in AI and quantum, with capital, talent, and regulation aimed at scaling.
- Asia — especially Japan, Korea, and China — dominates in robotics and advanced manufacturing.
- Europe offers regulation, standards, and the capacity to harmonize markets.
Countries that orchestrate platforms—with universities, incentives, industrial clusters, and pro-innovation regulation— will unlock disproportionate benefits. Remaining as late adopters reduces the option of being “price-takers” of disruptions designed elsewhere.
And Spain? Preparing is a strategy, not a slogan
For a country like Spain, the practical message is twofold: talent and platforms. Developing and attracting profiles in applied AI, automation, simulation, cybersecurity, data, and hardware will make a difference. Regarding platforms, it’s advisable to focus on verticals with critical mass (energy, agriculture, tourism, logistics, digital health), connecting technology centers, large companies, and startups with patient capital and public innovation procurement.
For companies, the winning position is not “wait and see.” It’s testing use cases with direct impact on revenues or costs, setting metrics and roadmaps for each wave, and seeding pilots for the next. For professionals, the advice is obvious: retrain and specialize in one of the ten platforms; the market will pay scarcity premiums to those who combine domain expertise with new tools.
Risks and realism: don’t confuse map with territory
Every growth thesis involves risks: interest rate cycles, geopolitical fragmentation, supply bottlenecks, bubbles in hot segments, regulation that foresees adoption, or simply poor execution. Therefore, rather than “bet everything” on a single technology, the suggested approach is a portfolio of platforms with discipline in allocation, rebalancing based on traction, and early cuts when signals are weak.
The core point remains: this isn’t a revolution; it’s ten simultaneously. And if returns are not linear, neither is the entry window.
Conclusion: choose the wave… and get on before it breaks
The upcoming decade promises the greatest wealth creation in modern history of technology, according to Hunt’s thesis. The key question is no longer whether the wave exists; it’s which wave you want to ride and with what plan. The map of platforms — AI, robotics, autonomous systems, mixed reality, drones, satellites, humanoids, quantum, wearables, BCI — offers various routes. But what it doesn’t offer is infinite time: each passing quarter, the author reminds us, more value is captured by those already positioned.
The future isn’t guessed; it’s built. And the time to do it — with judgment, metrics, and timing — is now.
Frequently Asked Questions
What technologies are part of the “wave” of 6–8 trillion dollars between 2025 and 2035?
Ten platforms that reinforce each other: AI, robotics, autonomous vehicles, mixed reality (AR/VR), drones, satellites, humanoid robots, quantum computing, wearables, and brain-computer interfaces (BCI). The thesis is that their interaction (hardware + software + ecosystem) creates most of the value.
What does investing in “compounder platforms” mean and how do you identify one?
A compounder platform combines dedicated hardware, specialized software, and ecosystem potential (third parties building on top). The key filtering question is: “Will it foster an ecosystem or is it just a component?”. Platforms that attract third parties tend to generate network effects.
What might a typical technological exposure allocation look like (not financial advice)?
A framework suggested by the author: 60% in public markets (stocks and ETFs) and 40% in private to capture early-stage growth. Within public markets: 50% in Tier 1 (AI, robotics, drones), 35% in Tier 2 (autonomous vehicles, AR/VR), and 15% in Tier 3–4 (quantum, humanoids, BCI).
What can professionals and companies do today to avoid falling behind?
Choose a priority wave, run pilots with metrics (cost savings, revenue impact, time-to-market), develop internal capabilities (data, applied AI, automation), and build alliances with startups and tech centers. For individuals: retrain and specialize in one of the ten platforms; the market will reward those who combine sector knowledge with new tools.