Jack Kokko

Co-founder and CEO of AlphaSense

Mentions

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Key positions and views

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.

Podcast consensus on Kokko

Points of consensus

▶Both sources emphasize Jack Kokko's vision of building an "automated analyst" by systematically breaking down and automating every step of a research professional's workflow.Apr 2026

▶Kokko consistently argues across both appearances that AlphaSense's key differentiator is its "full stack" approach, combining proprietary data (especially from expert transcripts) with a specialized AI layer, which generalist LLMs lack.Apr 2026

▶The strategic importance of acquiring Tegas is a central point in both discussions, highlighting it as the market leader in expert transcripts and a key driver of AlphaSense's recent growth acceleration.Apr 2026

▶Kokko repeatedly highlights the development and deployment of a proprietary "AI interviewer" as a transformative technology for generating new, unique data and conducting automated channel checks.Apr 2026

Points of debate

▶There is a subtle tension between the claim that AlphaSense's core product does not need significant modification for different customer segments (corporates vs. financial services) and the statement that the company uses different LLMs for these same segments due to stylistic preferences.Apr 2026

▶Kokko's initial seven-year hesitation before founding AlphaSense, based on the assumption that legacy players would solve the problem, contrasts with his current aggressive, hands-on leadership style, where he has taken on the role of head of product to accelerate growth.Apr 2026

▶While Kokko asserts that AlphaSense has good gross margins, he also acknowledges the company invests "hundreds of millions a year" into its value proposition, primarily on content, suggesting a highly capital-intensive model that could present its own challenges.Apr 2026

▶Kokko describes the generative AI wave as both a "massive gift" that clarified the company's vision and a significant "threat" that required every software company to fundamentally re-evaluate its strategy, indicating a dual-edged perception of the technology's impact.Apr 2026

Key themes

▶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.

Source episodes

Sentiment over time

Not enough data for timeline

Changes over time

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.

Suggested prompts

How sustainable is AlphaSense's capital-intensive strategy of acquiring proprietary data through multi-hundred-million-dollar M&A deals? &nearr;What are the primary technological and ethical hurdles for Jack Kokko's vision of a fully "automated analyst" that can proactively source and synthesize information? &nearr;How does AlphaSense's "full stack" approach defend against potential disruption from major technology players (e.g., Google, Microsoft) integrating advanced AI into their own data and enterprise search products? &nearr;As AI tools like AlphaSense become ubiquitous, how will the role and skill set of a successful financial analyst evolve, according to Jack Kokko's predictions? &nearr;

Key concepts

AlphaSense 2 ep Automated Analyst 2 ep Proprietary Data 2 ep AI Interviewer 2 ep Tegas Acquisition 2 ep Generative AI 2 ep Expert Transcripts 2 ep Full Stack System 1 ep Large Language Models (LLMs) 2 ep M&A Strategy 2 ep

Notable quotes

“what we really are trying to do is kind of a lot of the workflow vision is, you know, what ties together is like building an automated analyst. Automating every step of an analyst workflow systematically breaking that workflow down into its component steps and finding the ways to automate each one of them”

Jack Kokko · AI, Moats, & the Future of Market Intelligence: A Fireside Chat with AlphaSense

“where we've taken a very different approach from the rest of the market is that we are building a full stack system where we invest heavily in the data and content... And then the search and AI brain on top of that. And then the workflows...”

Jack Kokko · AI, Moats, & the Future of Market Intelligence: A Fireside Chat with AlphaSense

“Our deep research, we hear from clients that work that they used to have a team doing for a month researching a new market... That month's worth of work for a team could now be done potentially in ten minutes by the machine...”

Jack Kokko · AI, Moats, & the Future of Market Intelligence: A Fireside Chat with AlphaSense

“our system can figure that out, that this is a problem. Let's find the right experts in our network. Let's go and bring back the information. And hours later, it can provide really high confidence information on this thing that people don't have to be scrambling around anymore.”

Jack Kokko · Jack Kokko - Building the Google of Finance at AlphaSense (EP.461)

Report last updated: Apr 21, 2026

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