The STOXX Thematic indices are designed to reflect how technological innovation is reshaping markets, moving beyond traditional sector classifications to capture developments across areas such as artificial intelligence (AI), defense and quantum computing. A key component of this approach is the use of patent‑based data and advanced taxonomy frameworks, including inputs from EconSight.
To explore how these datasets are structured and continuously refined, we spoke with Kai Gramke, Managing Director at EconSight.
Gramke also discussed with us how they partner with scientists to enhance patent classifications. His insights underscore how patent analysis, AI, expert curation and strategic insight can intersect to provide investors with a forward-looking lens on scientific progress, and ultimately help build smart equity indices that better reflect real-world technological advances.
Kai, how has the classification of technologies you cover evolved since we spoke last year?
“We have significantly expanded both the breadth and depth of our technology coverage. Our taxonomy now includes more than 15,000 technologies, providing near-comprehensive coverage across innovation domains.
At the same time, we’ve fundamentally refined our methodology. Our classification system combines expert curation with advanced AI, merging human intelligence with machine scalability. The result is a distinctive hybrid taxonomy — patent-grounded at its core, and market-oriented at the surface.”
Which technological segments are undergoing the most significant advances? Can you provide examples?
“Three overarching themes have dominated in recent years: digitalization, sustainability and security. More specifically, over the past 12 months, we’ve observed notable shifts within these themes:
- Security has expanded beyond the primary focus of cybersecurity to encompass broader defense technologies, increasingly driven by digital capabilities.
- AI is moving toward “Physical AI,” where algorithms interact directly with the physical world.
- Space technologies are gaining rapid momentum, spanning areas such as orbital data infrastructure, quantum communication and advanced manufacturing for space environments.
These developments are highly interconnected. Defense technologies, for example, are becoming increasingly digital, with AI playing a central role and driving growth in dual-use technologies.”
For the recently launched iShares Quantum Computing ETF from BlackRock, you’ve gone beyond patents and incorporated information from company websites and annual reports. How does that work?
“We have built a comprehensive database of corporate documents that can be queried for specific technologies. However, unlike traditional methods, this is not based on simple keyword searches. Instead, we use AI models to identify true technological concepts, taking into account context, relevance and strategic intent. We apply the same approach to company websites. This allows us to determine which companies, beyond pure-play firms like IonQ or Rigetti, are meaningfully engaged in key technologies.
Not all technology exposure is equal. We use a multi-dimensional scoring system to assess how deeply a technology is embedded in a company’s operations and strategy. This is reflected in scores that range from “Basic Awareness” to “Central Aspect of Business Strategy.” Scores can be calculated separately for patents, reports and websites, or combined into a single aggregated metric. The weighting of each component can also be customized depending on the use case. This leads to more robust, transparent and future-oriented indices that better reflect real technological leadership.”
With themes such as quantum computing and AI evolving so quickly, how do you ensure your taxonomy keeps pace?
“We continuously monitor technological developments at a granular level, particularly within sub-technologies, where most innovation occurs. While core themes like AI and quantum computing have been tracked for years, we regularly reassess which sub-segments are becoming truly relevant. Our strength lies in this ability to differentiate and refine.
Importantly, our taxonomy is not a rigid product — it serves as a starting point for bespoke solutions. Each ETF or client mandate is tailored, more like a curated process than a standardized offering. We like to think of this in terms of a gourmet restaurant, where the chef ensures that each ingredient fits and preferences are discussed in advance, rather than a buffet where everything ends up jumbled on your plate.”
What role do partnerships and external expertise play in your process?
“Collaboration is central to our approach. As an example, for the iShares Quantum Computing ETF we partnered with QuantumBasel, which contributed both subject-matter expertise and analytical tools for evaluating company disclosures. At EconSight, it’s not just any AI identifying technologies; we work closely with scientific and industry partners to ensure that our classifications are robust, transparent and explainable.
We also actively contribute to global standards. For instance, we co-developed the new Green Taxonomy for the World Intellectual Property Organisation (WIPO), and our definition of generative AI has evolved into a widely adopted global standard.”