Why Human Expertise is the New Scarcity in an AI-Driven Market

Recap of the Women in Product Management (WIPM) Session
February 1, 2026

The air at the Women in Product Management session on February 1 was charged with a single, pressing question: In a world where AI can synthesize a market report in seconds, what happens to the human expert?

Sneha Kapoor,Managing Partner for APAC and MEA for Kea Analyst Relations and Shashi Bellamkonda, Principal Research Director at Info-Tech Research Group, provided a definitive answer.

They argued that the rise of Large Language Models (LLMs) has actually created a "Credibility Paradox," making human analyst relations more valuable today than at any point in the last twenty years.

The Credibility Paradox: Why "Good Enough" is No Longer Enough

The session’s foundational insight centered on the gap between information and accountability. While AI systems are excellent for broad market research, they operate under a permanent shield of disclaimers.

For a CIO, saying "the analysts we trust recommended this" provides a level of professional safety that an AI output simply cannot replicate.

The Strategic Shift: From Marketing Execution to Product Substance

One of the most energetic portions of the discussion involved reframing where Analyst Relations (AR) lives within the organization. Kapoor articulated a sharp distinction: Marketing focuses on the execution—the "how to say it"—while AR informs the substance—the "what to say."

For product managers in the room, the takeaway was clear: AR should be viewed as a Product Development Loop. By engaging analysts early, teams can stress-test their roadmaps against market gaps that analysts see daily. This shifts the primary metric of success from "press mentions" to Strategy Influence, measuring how many core business decisions were refined based on analyst feedback.

Scaling AR: Information as the Universal Currency

A common point of friction discussed was the perceived high cost of entry for formal analyst programs. However, the speakers provided a tactical roadmap for scaling without massive budgets:

• Information Exchange: Analysts are hungry for unique data. Organizations can often secure briefings with firms like Gartner, Forrester, IDC, or Info-Tech Research Group without a paid subscription if they provide a clear, data-driven market narrative.
• The Advisory Tier: Formal relationships should be viewed as an investment in "Inquiries," one-on-one sessions used to validate GTM strategies before they are launched.

Closing the Sales Gap

Bellamkonda urged organizations to stop letting AR exist in a silo. By using AI to mine sales calls for analyst mentions and tracking the "Inclusion Rate" in buyer evaluations, firms can finally quantify the direct impact of AR on the revenue pipeline.

Sneha Kapoor highlighted a critical, often overlooked function of Analyst Relations: its role in internal enablement. Beyond influencing external buyers, Kapoor noted that leading Analyst Relations teams utilize their unique access to market intelligence to directly train and equip internal sales forces.

By translating complex analyst insights into actionable talk tracks, AR teams ensure that sales representatives are prepared to handle high-stakes procurement conversations where analyst credibility is the primary differentiator.

The Final Verdict: Analysts are the Source Code for AI

The session concluded with a look at the future of the intelligence hierarchy. It was noted that analysts are the primary source of the original, expert insight that eventually feeds the LLMs. Without the analyst, the AI has nothing of substance to distribute.

For companies looking to scale, the message was direct: Treat analysts as strategic partners, use them as a feedback loop for your roadmap, and recognize that in an automated world, authentic human credibility is your greatest force multiplier.