How Investors Can Improve at Expert Calls and AI with AlphaSense's Ryan Fennerty

Why It Matters

Integrating AI into expert‑call workflows boosts research efficiency and helps investors maintain an analytical edge in an increasingly data‑driven market.

Key Takeaways

• Frame calls around clear investment hypotheses
• Use AI to triage and summarize expert transcripts
• Cross‑validate insights to avoid echo‑chamber bias
• Blend real‑time AI alerts with long‑term research
• Develop data‑literacy and prompt‑engineering skills

Pulse Analysis

Investors have long relied on expert calls to fill information gaps, but the process often suffers from unstructured note‑taking and confirmation bias. By anchoring each interview to a specific hypothesis, fund managers can ask targeted questions, screen participants more effectively, and compare responses against a broader data set. This disciplined approach reduces echo‑chamber effects and ensures that insights are actionable rather than anecdotal.

Artificial intelligence now amplifies these gains by instantly converting spoken interviews into searchable transcripts, flagging key themes, and surfacing contradictions across multiple sources. AI‑driven synthesis accelerates earnings forecasts, allowing analysts to move from hours of manual review to minutes of insight extraction. Moreover, AI tools can cross‑reference expert commentary with internal datasets, uncovering differentiated investment theses that would be difficult to spot through human effort alone.

The rise of AI also reshapes the investor’s skill set. Professionals must become fluent in prompt engineering, data‑literacy, and bias detection across both human and algorithmic inputs. Real‑time AI alerts enable continuous portfolio monitoring, while advanced models help flag potential fraud or data anomalies. As AI democratizes access to research capabilities, the competitive advantage shifts toward those who can blend technology with rigorous fundamental analysis, ensuring robust, future‑proof investment strategies.

Original Description

Host Andrew Walker speaks with Ryan Fennerty of AlphaSense about how investors can improve their use of expert calls and AI tools. Ryan shares practical ways to run better expert interviews, avoid bias, and extract deeper insight from operators. The conversation examines how AI is reshaping research workflows, accelerating earnings analysis, strengthening conviction, and enabling faster synthesis across expert transcripts and internal data. They also address portfolio monitoring, differentiated views, and the evolving skill set required for investors in an AI-driven landscape.

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[00:00:00] Introduction and sponsor message

[00:05:37] Framing expert calls around hypotheses

[00:07:32] Transcripts versus live expert calls

[00:12:36] Echo chambers and bias risks

[00:16:37] Managing investor bias in calls

[00:20:53] Expert bias and triangulation

[00:23:26] Improving expert screening process

[00:26:08] Real-time versus long-term insights

[00:29:20] Note-taking and AI synthesis

[00:31:51] AI’s biggest investing advantage

[00:36:31] Differentiated views in AI era

[00:41:17] Does AI commoditize research edge?

[00:45:18] AI expanding opportunity funnel

[00:49:32] Evolving skill sets for investors

[00:51:30] AI in portfolio monitoring

[00:54:17] Bias across AI data sources

[00:56:31] AI transforming expert networks

[01:00:17] Corporate use of expert insights

[01:02:36] AI, fraud detection, and limits

[01:05:47] Future of fundamental investing

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Production and editing by The Podcast Consultant - https://thepodcastconsultant.com/