Intelligence Is Now a Commodity. Are You Still Treating It Like Gold?

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The Tools Got Smarter. Did We? I’ve been saying it for years: information is a commodity. The idea that data is power? That ship sailed long ago. The real value lies in making sense of it, fast. And now, AI is turning even that into an on-demand service.

We’re witnessing a revolution in deep research tools, and OpenAI’s Deep Research is just one player in the game. Google’s Gemini Deep Search, xAI’s Grok Deep Search, Anthropic’s Claude’s Research Mode, Perplexity AI’s Pro Search, and others are all racing to redefine how we access intelligence.

"Our research department spent three months compiling that market analysis," a CEO told me during MWC recently.

I pulled out my phone and reproduced 80% of their findings in under five minutes using a combination of Gemini Deep Search and OpenAI's Deep Research, then pulling all together in a nice report using Claude.

His face went through the five stages of grief in real-time.

"When intelligence becomes a commodity, execution becomes the only true competitive advantage."

The Great Intelligence Collapse. From Information Scarcity to Intelligence Abundance

For centuries, intelligence was expensive. You hired specialists, funded research departments, or paid a premium for consultants. Now? The cost of intelligence is collapsing.

AI research agents don’t just skim the web; they refine queries, interpret full documents, cross-check sources, and generate structured reports in minutes.

These tools are the equivalent of a research department, but infinitely faster. And yet, while intelligence is becoming abundant, the way organizations process and act on it? Still painfully slow.

We're witnessing a revolution in deep research tools:

OpenAI’s Deep Research: Focuses on structured, citation-backed reports, great for in-depth corporate research.

Gemini Deep Search: Google’s take, leveraging its vast index and multimodal capabilities for deeper contextual understanding.

Grok Deep Search (xAI): Built with Elon Musk’s signature philosophy, prioritizing open, real-time, and less-censored insights.

Anthropic’s Claude Research Mode: Optimized for long-context understanding, ensuring nuanced, multi-layered analysis.

Perplexity AI Pro Search: Marketed as the “Google Killer,” it combines retrieval-augmented generation (RAG) with real-time browsing.

What This Means for You…

Decision-Making Just Got Faster → No more endless PDF reports or consulting decks. You can get a 30-page synthesis in minutes, not months.

The Expertise Gap is Shrinking → These tools give startups, SMEs, and individuals access to the same level of intelligence once reserved for Fortune 500s.

The Value of Experience Increases → If everyone has the same information, the differentiator isn’t what you know, it’s how you apply it.

The Tools Got Smarter. Did Organizations?

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The paradox is that as intelligence gets cheaper, most organizations remain structured around the assumption that it's scarce and expensive.

Two-thirds of enterprises now report significant AI investments with minimal operational impact. The technology works, the organizations don't.

Why? Because most companies deploy next-generation intelligence inside previous-generation organizational structures.

The Organizational Immunity Response

When AI enters traditional companies, the organization’s "immune system" activates to contain this powerful new technology.

Some lock AI away in innovation labs, treating it like a controlled experiment rather than a core business function. Others try to shoehorn it into old workflows, stripping away its real potential. And then there are the subtle saboteurs, middle managers who see AI as a threat rather than a tool and quietly undermine its adoption.

This explains why companies with identical AI technologies show wildly different results. The limiting factor isn't the tools used, it's organizational adaptation.

The Three Splits - Where Organizations Fail

A pattern emerges when examining how organizations adapt (or fail to adapt) to intelligence abundance. The cracks start to show in three places: authority, process, and knowledge.

First, there’s the authority problem, companies still act like AI is just an assistant, not a decision-maker. Instead of letting AI handle routine choices, they keep humans in the loop for every minor call, slowing everything down.

Then, the process problem, most businesses expect AI to fit into their existing workflows rather than redesigning workflows to leverage AI’s speed and efficiency. Old habits die hard, and clunky processes stay clunky, even with the best tools.

Finally, the knowledge problem, AI insights often get trapped at the top, when they should be flowing to the front lines. The people who need real-time intelligence the most are often the last to get it.

And the implications? Brutal.

Decision-making cycles that once dragged on for months are now happening in days. Yet some companies are still stuck in their old rhythms, taking forever to act on insights that are available in real time. If you're still running on month-long intelligence cycles, you're already behind.

The intelligence once locked away in Fortune 500 boardrooms is now at the fingertips of startups, SMEs, and even solo entrepreneurs. The playing field has leveled, but not everyone knows how to use it. The real differentiator isn’t what you know, it’s how fast you can turn that knowledge into action. Execution, not information, is what separates the winners from the also-rans.

When intelligence is abundant, the only sustainable advantage is execution velocity. Most companies will drown in AI-generated reports while a select few will transform those insights into action at unprecedented speed.

If your organization is still hoarding information, requiring multiple approvals for obvious decisions, or prioritizing perfect analysis over rapid experimentation... then AI research tools won't save you, they'll expose you.

Intelligence Is Now a Commodity. What can you do to rewrite the requirement?

Organizations need a complete rewiring, not just a software upgrade. Intelligence can’t be hoarded at the top. AI insights need to flow where work happens, empowering teams to make faster, smarter decisions.

Analytical tasks that AI can handle should be automated, leaving humans free to tackle creative and strategic challenges. Governance structures must shift, too, decision-makers should focus on exceptions, not micromanage every move. And above all, organizations must commit to continuous adaptation. AI won’t wait for them to catch up.

Moving Forward

The coming year will widen the gap between organizations that merely adopt AI research tools and those that adapt their structures to leverage them. The winners won't have better algorithms, they'll have more adaptive organizations.

What will you change first? Your AI procurement strategy or your organizational design?

Want to assess your organization's intelligence flow? Check out our AI Readiness tools.

If you want to know more about how Apiro Data can help your Digital Transformation, IoT and operational strategy.

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