DeepTech Patents Challenge Traditional Legal Order
The global shift toward DeepTech, sectors built on intensive research such as artificial intelligence, semiconductors, and biotechnology, is exposing the limits of patent systems designed for an earlier era. As innovation cycles accelerate and inventions increasingly span multiple disciplines, the legal frameworks governing intellectual property are struggling to remain commercially practical and technologically informed.
Why DeepTech Changes the Value of Patents
For years, the technology sector was dominated by software services and outsourcing. That landscape has shifted. A growing number of startups and research-driven companies now operate in artificial intelligence, semiconductors, robotics, biotechnology, clean energy, electric vehicles, advanced materials, and space technology. These sectors fall under the broad label of DeepTech. What unites them is their reliance on intensive research, engineering, and long development cycles. Unlike traditional technology businesses, DeepTech companies typically spend years developing technology before commercial scaling begins.
This transformation has quietly altered the role of patents. A decade ago, many startups viewed patents as optional or defensive filings. Today, patents are increasingly tied to fundraising, licensing discussions, collaborations, and investor confidence. In sectors like semiconductors or biotechnology, companies are often valued not only for their products, but for the technology they can protect.
How DeepTech Strains Existing Patent Frameworks
Patent laws were framed during a period when inventions were mostly mechanical, industrial, or pharmaceutical. Innovation cycles were slower, and technologies remained commercially useful for longer periods. DeepTech innovation moves differently. Products evolve quickly, systems are updated continuously, and many inventions combine multiple disciplines at once.
The semiconductor sector illustrates this clearly. Modern semiconductor innovation extends beyond chip design. It involves fabrication processes, embedded systems, cooling techniques, materials engineering, and software integration working together within the same product ecosystem.
Clean energy presents a similar picture. Companies file patents around battery chemistry, hydrogen fuel systems, energy storage technologies, and smart infrastructure solutions. Businesses build entire portfolios around different layers of the same technology rather than relying on a single patent.
What Happens When AI Contributes to Invention?
Artificial intelligence adds another dimension. AI systems are now used in predictive analytics, industrial automation, drug discovery, design optimisation, and manufacturing processes. Human involvement remains central, but machines increasingly contribute to the innovation process itself.
This raises difficult questions. If an AI system plays a significant role in developing an invention, who should be considered the inventor? Existing patent laws were drafted around the concept of human inventorship, and many jurisdictions are still struggling to address AI-assisted innovation.
India has already seen early signs of this debate. The Indian Patent Office refused Dr Stephen Thaler a patent application related to an AI system called Device for the Autonomous Bootstrapping of Unified Sentience (DABUS). The office maintained that only natural persons can be recognised as inventors under the Patents Act. Legally, the position aligns with the present framework. Still, the case highlighted a broader concern: technology is evolving much faster than the laws interpreting it.
What Challenges Do Biotechnology and Software Present?
Biotechnology creates its own set of challenges. Innovations involving biologics, genetic engineering, diagnostics, and bioinformatics raise questions around disclosure standards, enablement, and patent eligibility. Scientific advancement frequently moves ahead of legal interpretation, creating uncertainty for both innovators and investors.
Software-related inventions remain another major issue. Most modern DeepTech products, whether robotics platforms, connected medical devices, autonomous systems, or advanced manufacturing technologies, rely heavily on software-driven operations.
Under Section 3(k) of India's Patents Act, 1970,