If Industry Analysts Disappeared Tomorrow, Could AI Fill the Gap?

Why AI Cannot Replace Analyst Relations- But Can Make It Better 

AI can carry more of the information burden. It cannot manufacture independent market perspective, build trusted relationships, or assume accountability for a recommendation.

AI is forcing business leaders, industry analysts, and Analyst Relations teams to reconsider how market intelligence is created and applied. The question is no longer whether AI should be used. It should.

The more important question is where AI creates genuine advantage, and where relying on it too heavily could separate companies from the people, original insight, and outside perspective they need to compete.

If Industry Analysts Disappeared, Could AI Fill the Gap?

Technology companies would still have sales data, customer interviews, competitive research, product reviews, and enormous amounts of public information. AI could compare vendors, explain categories, assemble shortlists, and recommend products based on stated requirements.

But something essential would be missing: an independent group continually speaking with buyers and vendors, testing company claims, and identifying patterns across the broader market.

Every company sees the market through the boundaries of its own experience. It rarely hears from buyers who never considered it, eliminated it early, misunderstood its positioning, or chose another category entirely.

Industry analysts occupy a different position. Through research, inquiries, briefings, advisory work, and buyer conversations, they recognize patterns no individual vendor can see from inside its own organization. They may discover that buyers distrust a common claim, require evidence vendors are not providing, or define a problem differently from the companies attempting to solve it.

Without that external perspective, companies risk becoming highly efficient at analyzing, and reinforcing their own assumptions.

AI Depends on Original Human Insight

Analyst research, market evaluations, category definitions, and independent points of view create original information that AI can organize and connect.

If analysts stopped producing that work, AI would not simply take over from the same foundation. That foundation would gradually shrink. Public information could become increasingly dominated by promotional content, vendor claims, and material generated from previous AI summaries.

Visibility could begin to look like credibility.

AI can organize information, compare claims, monitor competitors, summarize research, and surface possible patterns. These capabilities can make analysts and AR professionals significantly more effective.

But AI cannot interpret information it never receives. It cannot earn the trust that causes a buyer or executive to disclose what is truly influencing a decision. It may identify a pattern, but an experienced person must still determine whether that pattern is meaningful, misleading, or incomplete.

Why Analyst Relations Remains Essential

Access to analyst feedback does not automatically tell a company what to do with it.

A repeated question could indicate unclear positioning, insufficient evidence, changing buyer priorities, a new research direction, or simply a standard question being asked of every vendor.

Senior AR professionals understand the analysts, the company’s history, and what was said, or left unsaid, during an interaction. They interpret feedback in context, prepare executives, manage trusted relationships, and translate relevant intelligence into practical business decisions.

AI can support that work. It should not own it.

How a Personal Question Helped Shape Forward

For me, this was never merely theoretical.

My husband, Gary, has spent more than 30 years in Analyst Relations. When he was laid off and spent five months searching for his next opportunity, we repeatedly encountered an unsettling question: Could AI replace experienced AR professionals?

The possibility was frightening - professionally and personally. But searching for an honest answer led us somewhere more constructive.

Gary understood how scattered research, interaction histories, analyst feedback, internal documents, and institutional memory affect AR teams. Drawing on more than two decades of experience building businesses, sales systems, and growth strategies, I saw the operating and technology challenge underneath it.

We originally expected to build Forward together. When Gary accepted a professional opportunity that was too important for our family to decline, Forward had to become larger than either of us. It needed a system that could help experienced practitioners work from a stronger foundation without removing human judgment, relationships, or accountability.

That principle shaped Forward’s senior-only delivery model and its interconnected intelligence ecosystem: the Forward Intelligence Library, AI-Enabled Intelligence Knowledge Base, and Sales Engine. Together, they connect thought leadership, market intelligence, practitioner expertise, and audience insight in a system designed to become more valuable over time.

The Forward Intelligence Library extends that purpose to the broader AR community. It gives analysts, AR practitioners, executives, and cross-functional leaders a permanent, AI-searchable home for practical knowledge and informed perspectives. Valuable ideas, and the professionals behind them, should remain discoverable instead of disappearing in a social feed or aging unnoticed in a forgotten blog archive.

The Future Is AI-Enabled and Human-Led

AI will increasingly handle routine collection, summarization, comparison, and first-pass analysis. That should allow analysts and AR professionals to spend more time creating original insight, interpreting market signals, advising leaders, and strengthening trusted relationships.

The wrong question is: “What can AI replace?”

The better question is: “How can AI help experienced people see more, connect more, and apply their judgment where it matters most?”

AI will not make analysts unnecessary. It will make original insight more important. It will not make experienced AR professionals unnecessary. Used responsibly, it will help them deliver more connected, consistent, and valuable counsel.

The future of Analyst Relations should not be AI-directed. It should be AI-enabled and human-led.