The obsession with locking in first-party data has swept across every sector. OpenAI reportedly paid $500 million for a gaming platform’s user data. Major tech players are securing data assets through mergers, acquisitions, and platform capture — all built on the premise that data scarcity equals competitive power. But two converging forces are dismantling that premise simultaneously: the economics of Moore’s Law, and the rising intelligence of AI systems that now evaluate brand credibility on far deeper terms than data volume.
NVIDIA’s founder Jensen Huang has observed that AI technology’s cost drops 100,000 times every ten years. Within a decade, AI-generated synthetic data will represent the vast majority of what other AI systems learn from — reducing human-generated data to roughly 1% of the total.
Joanne Z. Tan points out that companies spending hundreds of millions today to seize consumer data are, by this logic, paying real diamond prices today, for fake diamond when AI and data soon become very cheap commodity to be squandered.
And the data ethics dimension compounds this further. Scholars Ulises Mejias and Nick Couldry, in their book “Data Grab: The New Colonialism of Big Tech”, argue that today’s data grab or data extraction mirrors the colonial land grabs of centuries past — personal information converted into corporate profit without the knowledge or consent of those generating it. During historical colonialism, at least, those dispossessed knew something was being taken. Today’s consumers largely do not.
The strategic irony business leaders cannot afford to ignore is that AI itself is becoming the mechanism by which data exploitation backfires. AI search systems are evolving to synthesize trust signals — customer reviews, media sentiment, original thought leadership, high-authority content, employee advocacy, and executive reputation — into what may soon function as “trust scores” that determine brand visibility and recommendation outcomes more powerfully than paid media or manipulated review counts ever could. Data ethics, in other words, is no longer a compliance question. It is a brand equity question with direct consequences for how AI ranks, recommends, and surfaces your company to the customers you need most.
A recent case study from 10 Plus Brand’s own client work illustrates this clearly. After rebranding The Ivy Group — which had operated as “Ivy Commercial” for 25 years — the firm had to build a new Google Business Profile from scratch, starting with few reviews under the new name. Approximately 18 months after 10 Plus Brand Team launched the new website, TheIvyGroup.com, with consistent thought-leading blogs and case studies published regularly, ChatGPT ranked it as the number one boutique commercial real estate brokerage firm in Fremont, California, among fierce competitors. AI looked past the absence of reviews and recognized genuine authority. The companies that will win the next decade are not those that grabbed the most first-party data — they are the ones that built the trust signals AI systems are already learning to reward.
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Joanne Z. Tan is the Founder and CEO of 10 Plus Brand, Inc. and the creator of AIXD.world — AI Experience Design. A globally recognized brand strategist, thought leadership coach, and startup mentor based in Silicon Valley, Joanne works with founders, CEOs, and C-suite executives to build brands that lead markets, command premium positioning, and endure. Joanne is known for this principle: “User experience is brand experience, and brand experience determines enterprise destiny.”
© Joanne Z. Tan, 2026. All rights reserved.
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