Deep tech, characterized by its focus on breakthrough technologies grounded in scientific discovery, has the unique potential to create entirely new categories by redefining problems, solutions, and markets. Deep tech often tackles challenges considered insurmountable with existing technologies. For example, quantum computing enables solutions in cryptography or materials discovery that classical computing cannot achieve. Technologies like AI, robotics, and brain-computer interfaces introduce capabilities that were previously unimaginable, leading to new use cases and categories. AI-generated art has created a category for computational creativity platforms.
Deep tech often cuts across traditional industry silos, creating hybrid categories. AgTech merges agriculture and technology with innovations like vertical farming or biopharma and tech convergence in precision medicine or drug design using AI. New deep tech categories often spawn ecosystems of complementary products, services, and applications. For instance, electric vehicles (EVs) didn’t just create the EV category; they also spurred charging networks, battery recycling markets, and advanced materials.
Deep-tech innovations often lack immediate market fit because they address challenges that existing industries are not equipped to solve or are unaware of. Focusing on category-making is a transformative strategy for deep-tech ventures. Rather than retrofitting existing markets, this approach emphasizes creating a new conceptual and practical space for a technology to thrive. Category-making involves defining a new market or domain where your innovation becomes the standard or baseline. Instead of competing in established markets, the deep-tech venture positions its innovation as a solution to problems that have never been addressed or even recognized.
The story of autonomous cars illustrates how deep-tech innovation can evolve from being a technological breakthrough to a solution for broader societal problems like road accidents. Autonomous cars owe their existence to advancements in a combination of deep-tech domains. These technologies were developed independently for various purposes, such as robotics, space exploration, and telecommunications, but their convergence made autonomous driving possible.
The shift to addressing road accidents happened because of how innovators framed and marketed the value proposition of autonomous cars. Early advocates of autonomous vehicles emphasized that human error accounts for over 90% of traffic accidents. Autonomous systems, being free from distractions, fatigue, and impaired judgment, could dramatically reduce this statistic. By focusing on this problem, the technology gained societal and regulatory attention as a solution to a significant global issue. With autonomous driving prototypes, engineers realized that the technology could predict and avoid dangerous situations (e.g., sudden braking or lane changes) far more effectively than humans.
The autonomous car category expanded from "self-driving" to being synonymous with broader societal improvements such as:
Road Safety: Eliminating human error as a root cause of accidents.
Traffic Efficiency: Smarter driving reduces congestion and emissions.
Accessibility: Autonomous vehicles offer mobility to individuals unable to drive (e.g., elderly or disabled).
Autonomous vehicles didn’t create the “car” market; they redefined it by introducing safety and automation as the most critical differentiators. Road accidents and fatalities resonated with policymakers, consumers, and regulators, making it a powerful anchor for the new category. By presenting autonomy as a tool to reduce road deaths, deep-tech companies aligned their technology with global goals like the UN's Vision Zero initiative.
Key Lessons from Autonomous Cars
Deep-Tech Enables Solutions, but Framing Creates Markets The technological capability of driving without human input would remain a novelty unless tied to a compelling use case like solving road accidents.
Problem-Solving Creates Trust and Demand By showing measurable improvements in safety, companies turned skeptics into advocates. Public understanding and regulatory support followed.
Category Ownership Requires Problem Ownership AV companies positioned themselves not just as "technology companies" but as leaders in the fight against road accidents, owning the narrative of a safer future.
