Deep tech merges cutting-edge science, engineering, and artificial intelligence—and is helping to reshape industries at an unprecedented pace. Unlike conventional software startups, deep tech companies tackle fundamental challenges in AI, biotechnology, quantum computing, and robotics, often requiring years of research and development (R&D) before commercialization. As we move through 2025, the rise of deep tech is fueled by advances in computational power, breakthroughs in synthetic biology, and the maturation of quantum algorithms. In this blog, learn more about the growth and history of deep tech.

The Rise of Deep Tech

Deep tech is not a new phenomenon, but its acceleration over the past decade has been increasing. According to a 2023 report by Boston Consulting Group (BCG), deep tech startups have claimed a 20% share of venture capital funding, up 10% from a decade before.[1] Unlike the dot-com boom, which was driven by software and internet services, deep tech is rooted in scientific discovery, its impact can be more profound but also may require longer development cycles.

The History of Deep Tech

The term “deep tech” gained prominence in the mid-2010s, as venture capital firms like DCVC, Lux Capital, and Founders Fund began backing companies working on AI, quantum physics, and genetic engineering. Originally coined to categorize “startups in the life sciences, energy, clean technology, computer sciences, materials, and chemical sectors”[2], today, deep tech is no longer confined to labs—it’s entering mainstream industries, from healthcare to logistics, and infiltrating every aspect of our day to day lives.

Deep Tech Sub-Categories

Deep spans multiple industries that benefit from the highly sophisticated technology rooted in advanced scientific principles. The most commonly referenced industries include AI, biotech and genetic engineering, quantum computing, and robotics and humanoid automation.

AI

AI is a dominant force in deep tech, with applications spanning autonomous systems, drug discovery, and real-time language translation. OpenAI, a pioneer in large language models (LLMs), has continued pushing boundaries with GPT-4.1, released in April 2025.[3] Featuring “major gains” in coding and instruction following, GPT 4.1 notably has a refreshed knowledge cutoff of June 2024. Many AI models are limited on real-time data due to the rigorous training each model needs to go through before deployment. With new AI models constantly being trained and released by industry leaders, AI is growing at a rapid pace.

Other AI leaders, such as DeepMind (Google), Anthropic, and Mistral AI, are advancing agentic AI—systems that can autonomously execute complex tasks, from coding to scientific research. According to a March 2025 McKinsey report, AI adoption in enterprises has grown from 50% in 2020 to over 78% in 2024 through July.[4]

Challenges and Ethical Considerations

Despite its promise, AI faces hurdles like:

• Regulatory scrutiny: The EU AI Act (2025) imposes strict transparency requirements on high-risk AI applications.[5]
• Compute costs: Training advanced AI models can require millions of dollars in GPU/TPU resources, raising concerns about monopolization by tech giants.
• Bias and safety: Instances of AI hallucinations and misuse persist, prompting calls for alignment research and decentralized AI governance.

Biotech and Genetic Engineering

One of the loftiest deep tech endeavors is de-extinction—bringing back extinct species using genetic engineering. Colossal Biosciences, founded by Ben Lamm and George Church, aims to resurrect the woolly mammoth by 2027 using CRISPR and stem cell technologies. The company successfully completed the first de-extinction in October 2024 by bringing back dire wolf puppies – extinct for over 10,000 years.[6]

Beyond de-extinction, synthetic biology is helping revolutionize medicine, agriculture, and materials science:

• CRISPR 3.0: Next-gen gene editing can allow for ultra-precise DNA modifications with reduced off-target effects.
• Lab-grown organs: Companies like Frontier Bio are 3D-printing blood vessels and engineered tissues with the goal to revolutionize organ donation.
• Biofuels: Startups such as Zymergen engineer microbes to produce sustainable alternatives to petroleum.

Quantum Computing

Quantum computing, once a theoretical curiosity, is now nearing practical utility. PsiQuantum, a Silicon Valley-based startup, is building a fault-tolerant, photonic quantum computer and aims to achieve 1 million qubits by 2027. Unlike competitors relying on superconducting qubits (like IBM and Google), PsiQuantum’s approach leverages silicon photonics, which could enable room-temperature operation.

Meanwhile, IBM’s Quantum Heron (2024) and Google’s 70-qubit processor have demonstrated error-corrected computations, bringing quantum advantage (where quantum computers outperform classical ones) closer to reality.

Industry Applications

• Drug discovery: Quantum simulations can model molecular interactions in hours instead of years.
• Cryptography: Post-quantum encryption standards (NIST’s CRYSTALS-Kyber) are being deployed to counter quantum hacking.
• Logistics optimization: Companies like Volkswagen use quantum algorithms to optimize traffic flow and EV battery chemistry.

Robotics and Humanoid Automation

Robotics is undergoing a paradigm shift—from single-task industrial arms to general-purpose humanoids. Figure AI, backed by OpenAI, Microsoft, and Jeff Bezos, is developing Figure 01, a bipedal robot designed for warehouse and household tasks. In 2025, the company announced a partnership with BMW to deploy robots in automotive assembly lines.

Industry Applications

• Manufacturing and Logistics: Robotics can be used in automated production and supply chain management, helping labor shortages by utilizing robots for mundane, repetitive tasks.
• Healthcare: Companies like Neuralink are using humanoid robotics for surgical applications for complex procedures like brain surgery.
• Retail and Customer Service: Retail companies and hospitality agencies like hotels are using humanoid robots for room service delivery, automated check ins, and assisting with multilingual support.

Final Thoughts

As 2025 unfolds, deep tech stands at an inflection point. AI is becoming commonplace, biotech is rewriting life itself, quantum computing is breaking computational barriers, and robotics is redefining labor. Companies like OpenAI, Colossal Biosciences, PsiQuantum, and Figure AI exemplify the bold vision helping to drive this sector. The potential use cases for deep tech could be abound and it will be intriguing to see how the sector progresses over the next few years.

Want to learn more about key industries to keep an eye on? Check out the following blogs to learn more:

• Beyond Bitcoin: Evolution of Cryptocurrency
• The AI Wave: The History and Growth of the Semiconductor Industry
• The Final Frontier: The History and Growth of Space
• Printing the Future: The Landscape of 3D Printing
• The Biotechnology Revolution: Driving Advancements in Precision Medicine

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[1] https://www.bcg.com/press/21november2023-deep-tech-claims-20-percent-venture-capital-surging-two-fold-in-past-decade

[2] https://reap.mit.edu/assets/What_is_Deep_Tech_MIT_2023.pdf

[3] https://www.theverge.com/news/647896/openai-chatgpt-gpt-4-1-mini-nano-launch-availability

[4] https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai

[5] https://www.softwareimprovementgroup.com/eu-ai-act-summary

[6] https://time.com/7274542/colossal-dire-wolf/

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