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  • 📘 How to get “AI Aggregator” ready

📘 How to get “AI Aggregator” ready

Can “their AI” find your teaser data?

Hi, and happy Tuesday.


Since the early 2000s, having a website hasn’t been enough. You have to rank on search engines. Otherwise, you simply disappear into the digital ether. History might be about to repeat itself, but with an AI twist.

💡By the end of this post, you’ll understand why “AI aggregator” readiness is becoming a necessity — where success no longer depends on who visits your website, but on whether “their AI” can find and understand your data on your products and services.

IN THE NEWS

✨ Gemini 2.5 Pro was released last week and, in benchmarks (and actual usage) is considered the smartest model available. To get the most out of it, load as much information as you can on your problem. Try it at https://aistudio.google.com

🖼️ OpenAI has added image generation to the free 4o model that makes it dramatically easier to get good images with simple prompts. This may be the end of stock image services. Learn More or try it at ChatGPT.com (login and select 4o). Here’s what I got for this prompt:

Create a patent drawing of a corporate innovation leader engaging in blue sky thinking.

IN THE SPOTLIGHT

Imagine you’re visiting a decades-old market intelligence firm’s HQ in London. The building’s basement once roared with printing presses churning thousands of paper reports each month. Fast-forward to today: that same company, Mintel, thrives on internet-based research services. But the next leap—in generative AI—is already transforming how data flows to clients.

In a recent conversation with Jason, Head of Innovation at Mintel, we heard first-hand how Mintel jumped on the internet era—and is now eyeing AI aggregators as the next technology wave.

The Aggregator Wave Is Coming

There’s a parallel to the “search engine era” that started in the 2000s and continues to this day. You have to optimize for Google to pull relevant page titles and page summaries as teasers that drive click-throughs to your website. Today, aggregator AIs could become the new gatekeepers.

If ChatGPT or Copilot is pulling data from various providers on-demand to answer a question, don’t you want to provide these AIs with teaser data, so users click through to discover your full dataset, and related products/services?

“We went from big printing presses to internet delivery, and that was transformational. Now with AI, it feels like the opportunity is similar—except it’s happening even faster.”

 â€”Jason

The tension? Many of us still think about “getting people to our website.” But in a future aggregator scenario, your user might never see your site. They’ll simply tell their AI what they need, and the AI will fetch content from multiple services behind the scenes. In this scenario, the key is your organization having a service that the AI can choose to fetch content from.

On the one hand, leaders see this as a huge opportunity to delight customers with frictionless data access. On the other hand, they worry about:

  • Security: Is your proprietary info going to get “scraped for free” by an AI?

  • Loss of brand control: When aggregator AIs present your data, will they get it right?

  • Integration headaches (Do you wait for aggregator “plugin” standards, or build your own now?).

Yet as Jason points out:

“We have gigabytes of data, but you need an expert to interpret it. AI can unlock all that, helping people skip the friction of learning yet another tool. We’re building an ‘AI search API’ so aggregator platforms can talk directly to us.”

—Jason

The GPT Store in ChatGPT, with tools embedded in them for accessing services, presents one implementation of the “AI Aggregator” concept. It has, though, not gained popularity.

Just as smartphones existed before the iPhone, the aggregator wave feels inevitable, once the right form-factor is developed. The question is, how do you prepare?

Are You “Aggregator Ready”?

Like Mintel in the 1990s—when they pivoted from paper reports to internet delivery—today’s innovators must structure and protect their data so it’s easy for AI assistants to find it and produce trusted insights.

Jason refers to this as the dream of “effortless access,” where users get instantly relevant answers and never have to learn complicated dashboards. But behind the scenes, you need robust gating, licensing, and secure APIs, so your proprietary knowledge doesn’t get mishandled or misrepresented.

“Clients want less friction. They shouldn’t need to learn 50 different tools. Instead, they ask their AI, which then queries Mintel’s data. That’s why we’re investing heavily in building out these interfaces.”

—Jason

It’s reminiscent of how media companies once hesitated to open their archives to Google—but those who jumped in carefully gained tremendous reach. Here, the stakes are higher. The AI doesn’t just link to content; it summarizes, synthesizes, and interprets it. Ensuring correctness and brand accuracy demands an intentional “aggregator readiness” approach.

How To Get “AI Aggregator” Ready

  1. Identify Unique Data & Expertise
    Map out what’s truly proprietary—consumer surveys, specialized manufacturing specs, or unique market analysis. That’s your gold.

  2. Establish Secure, Well‐Structured Access
    Create an API that returns data in structured formats. Gate it so only authorized (or subscribed) AI services can call it.

  3. Create ‘AI‐Friendly’ Bundles
    Offer short summaries, strong metadata, or specialized “function calls,” so aggregator AIs don’t hallucinate or dilute your brand.

  4. Form Partnerships or Plugins
    Consider building a GPT, Agent, Gem or other official integration with ChatGPT, Microsoft Copilot or Gemini. This is how you get discovered by user “copilots.”

  5. Monitor & Evaluate
    Continually test outputs from ChatGPT or other aggregators for accuracy. Use feedback loops to refine your data formats, guardrails, and commercial terms.

Reply to this email if you want to compare notes or discuss how your team might pilot an aggregator plugin approach. Happy to share templates and ideas

Where could AI Aggregators plug into your work?

If you want help identifying data that could be a useful honey trap for aggregator AIs, try this prompt:

My company - <company name> - is considering making our data and content available to aggregator AIs, such as ChatGPT, as tools in GPTs. This is so aggregator AIs can be teased with useful data to answer queries, while providing users with reason to explore our full dataset or products/services, available exclusively through us. Help me brainstorm 10 potential scenarios in which clients or partners might want to query our data. Focus in particular on <work area> scenarios. For each scenario, provide the cutoff for paywalling data.

Here’s highlights of what I got when I provided our company (PreScouter) and <work area> = company growth:

1. Emerging Market Trends for Strategic Planning

  • Scenario: A strategy leader queries, “What are the top 3 trends in sustainable packaging for 2025?”

  • Free Tease: High-level summary of 1 trend with a relevant stat or quote.

  • Paywall Trigger: Access to all trends, supporting data (patent activity, funding, adoption curve), and actionable recommendations.

2. Competitive Intelligence

  • Scenario: A growth lead asks, “How is Company X approaching AI in drug discovery?”

  • Free Tease: Mention one recent partnership or product development.

  • Paywall Trigger: Full competitive analysis including timelines, SWOT, partner landscape, and technical approach.

3. Tech Scouting for M&A or Partnerships

  • Scenario: An innovation VP searches, “What startups are disrupting cell-free protein synthesis?”

  • Free Tease: List 1–2 startups with one-line summaries.

  • Paywall Trigger: Full list with maturity stage, funding, tech differentiators, and contact intros.

4. Supplier or Manufacturing Innovation Discovery

  • Scenario: Ops team searches, “What’s the latest in biodegradable adhesives for packaging?”

  • Free Tease: Name of 1 novel material and supplier.

  • Paywall Trigger: Full supplier shortlist with tech specs, readiness levels, and performance benchmarks.

5. Regulatory Trend Monitoring for New Market Entry

  • Scenario: A business unit queries, “What regulatory changes are upcoming in APAC for ingestible biosensors?”

  • Free Tease: Mention of 1 policy change or pilot program.

  • Paywall Trigger: Country-by-country breakdown, timelines, and market entry recommendations.

So good, it makes me want to rethink our AI strategy!

Enjoyed this issue? Please pass it along to someone who’d benefit.

Best,

Dino

From Our Interview Series with Jason Thomson

🎯 What You’ll Learn:

  • The critical lessons from Mintel’s jump from paper to online

  • Why rapid tech adoption drives massive competitive advantage

  • How you can apply these same principles to harness AI

🎯 What You’ll Learn:

  • Where AI slots into Mintel’s data and content workflow

  • Why “tacit knowledge” still gives people an unbeatable edge

  • How to find the right balance between AI automation and human insight

🎯 What You’ll Learn:

  • Why AI-to-AI communication might redefine business relationships

  • How leading firms plan to connect data and content with AI platforms

  • The real steps to prepare your company for the next AI revolution

My Interview Notes

I came up with 7 proven frameworks straight from my chat with Jason at Mintel for adopting Generative AI:

  1. Paper → Digital → AI: Don’t fear the wave—ride it.

  2. Value Chain Insertion: Let AI handle the heavy lifting, step by step.

  3. 80–20 Inversion: AI does the busywork. You focus on relationships.

  4. Soft-Launch → Hard-Launch: Empower small teams, then train everyone.

  5. Dedicated AI Teams: Test, refine, measure results.

  6. “Your AI, My AI, Client AI”: Expect bigger ecosystems ahead.

  7. Rapid Experimentation: Weekly breakthroughs = weekly iterations.

60 SECOND HIGHLIGHTS (SHORTS)