A "full stack" system integrating proprietary data, a specialized AI layer, and custom workflows is the only defensible moat against generalist large language models.
The ultimate goal of market intelligence technology is to create an "automated analyst" that can autonomously identify information gaps, source new data, and generate complex research reports.
Generative AI is a transformative gift for companies with unique data assets, clarifying the path to automating knowledge work, but a threat to those without a differentiated data strategy.
Aggressive M&A, such as the acquisition of Tegas, is a critical strategy for consolidating the market and acquiring the unique, high-value datasets necessary to train superior AI models.
The future source of alpha in investment research will shift from information discovery to the ability to ask better, more creative questions and analyze cross-industry impacts as AI handles the data synthesis.
Pre-founding
Kokko waited seven years before co-founding AlphaSense, initially assuming that legacy financial data terminal players would solve the information discovery problem he had identified.
Strategic Expansion
AlphaSense acquired Stream, the number two player in the expert transcript space, to begin generating its own proprietary content and compete in the market.
Market Consolidation
AlphaSense acquired Tegas, the market leader in expert transcripts, in a deal valued at almost $1 billion. Kokko identifies this as a key driver of the company's recent growth acceleration.
GenAI Adoption
Kokko describes the recent wave of generative AI as a "massive gift" that clarified the path to achieving the company's vision, while also viewing it as a threat that necessitated a strategic re-evaluation.
Recent Product Leadership
To drive growth, Kokko has taken on the role of head of product, increasing his direct reports to be closer to product decisions and oversee launches like the new "AI interviewer".
▶The 'Full Stack' Moat Against Horizontal AIApr 2026
Jack Kokko's core strategy revolves around building a defensible "full stack" system. He argues that while generalist LLMs are powerful, they lack the proprietary, trustworthy business and financial information that AlphaSense acquires and integrates, spending hundreds of millions annually on content. This vertical integration of data, a specialized AI/search layer, and workflow tools is positioned as the company's primary competitive advantage.
This strategy suggests that the long-term value in AI for business intelligence may not be in the base models themselves, but in the proprietary data used to ground them and the specialized workflows built on top, making unique data acquisition a critical battleground.
▶The Vision of the 'Automated Analyst'Apr 2026
A recurring theme is Kokko's long-term vision to create an "automated analyst." This involves systematically deconstructing the entire workflow of a research analyst and automating each component, from identifying information gaps to sourcing new data via AI-driven interviews and generating deep research reports in minutes instead of weeks. This vision frames AlphaSense not just as a search tool, but as a system capable of autonomous insight generation.
If successful, this vision could fundamentally disrupt the labor model of financial services and corporate strategy, shifting the value of human analysts from data collection and synthesis to higher-level strategic thinking and asking novel questions.
▶Growth Through Aggressive M&A and Content AcquisitionApr 2026
Kokko's narrative highlights an aggressive growth strategy fueled by major acquisitions, specifically Stream and Tegas. The nearly $1 billion deal for Tegas was a pivotal move to secure what he considered the market-leading library of expert transcripts, which became a key driver of accelerating revenue. This M&A activity is central to the company's strategy of owning proprietary content.
This focus on M&A indicates that the market for financial and business data is consolidating, and leadership may be determined by the ability to deploy significant capital to acquire unique, hard-to-replicate datasets.
▶Proprietary AI Development Beyond LLMsApr 2026
While embracing generative AI as a "gift," Kokko emphasizes that AlphaSense is not just a wrapper around third-party LLMs. The company is developing its own AI capabilities, such as the "AI interviewer" that can conduct expert calls and a legacy sentiment model that outperforms modern LLMs on specific tasks. This demonstrates a strategy of building specialized AI tools tailored to the unique demands of financial and market research.
This suggests a hybrid AI strategy is crucial; leveraging generalist models for their broad capabilities while investing in specialized, proprietary models trained on unique data to solve specific, high-value industry problems.