Seema Alexander recently asked me a question I’ve heard dozens of times—on investor calls and in client demos, as the founder and CEO of Enquire.AI, a conversational expert insights platform.

“Will human expertise still matter now that AI can do everything?”

My honest answer?

It depends—but mostly, yes, especially when the ground is shifting beneath us.

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Yes, we’re hurtling toward artificial general intelligence (AGI).

LLMs can now draft strategy memos, decode balance sheets, and even simulate geopolitical forecasts.

However, they still fail in one crucial domain: volatile environments.

Think:

  • Emerging markets

  • Election cycles

  • Regulatory Landscape

  • War zones

These are not stable ecosystems.

They’re what scholars call “wicked learning environments.” And in those, pattern recognition isn’t enough.

You need wisdom.

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This is the DIKW hierarchy, coined by Russell Ackoff (1989), and it remains valid today.

  • Data → raw symbols

  • Information → organized data

  • Knowledge → actionable understanding

  • Wisdom → sound judgment in uncertain conditions

AI excels at the first three. Those layers are becoming fully commodified.

But wisdom?

That’s still solely human. And in a world of unstructured, fast-moving decisions, it’s also the most valuable.

Why Scraping Doesn’t Scale

Legacy investment research platforms bet big on aggregation:

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“Scrape every earnings call, every market move, every press release. Summarize it. Sell access.”

That worked—ten years ago. It was also not easy and cheap.

But today? LLMs do it in seconds. You don’t need to pay $25K/year for a glorified summary engine.

You can’t forecast tomorrow’s oil shock—or interpret the nuanced tone of a new Indian central banker—by compressing yesterday’s PDFs.

That’s where both data aggregators and traditional consultancies fall short. They offer scale or expertise—but not both, and certainly not in real time.

The future belongs to hybrid systems built on conversational insight, where AI and human intelligence work symbiotically. You ask, adapt, iterate. The model learns. The expert refines. And your thinking compounds.

This is how ideas go from question to clarity—not through scraping, but through collaboration.

The next frontier in research is conversational insight.

You should be able to talk to your data.

Ask questions. Get stitched, cited, and real-time answers from AI and experts.

That’s where the human/machine loop thrives.

At Enquire AI, we don’t believe in replacing experts or ignoring open-source intelligence.

We believe in augmenting them.

Our AI handles 95% of the grunt work: searching, filtering, organizing, and context-matching.

But that final mile? It is provided by verified, contextual, and experienced experts.

A few weeks ago, a buy-side analyst on our platform asked:

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“How will new U.S. tariffs affect BYD and NIO’s Southeast Asia strategy?”

Within 30 minutes, they received:

  • Prior commentary from a retired Chinese Ministry of Commerce official

  • Input from a U.S. trade lawyer and EV supply chain analyst

  • Macro perspective with historical patterns—sourced, cited, and synthesized

That’s not just AI. That’s Centaur Intelligence.

The winners aren’t those who fear AI, or blindly trust it.

The winners are those with wisdom, who:

  • Know what question to ask

  • Know when to ask

  • Know whom to trust

Wisdom doesn’t scale through scraping.

It scales through the symbiotic learning process of the expert, data, and AI.