There is a customer data “land grab” underway, and most grabbers have not recognized what the future value of the data will be, and what it would cost in terms of brand trust.
Across industries, companies are racing to acquire and monetize consumer data at a scale and speed that would have seemed dystopian a decade ago. For example, OpenAI reportedly paid $500 million for a gaming platform’s user data.
Major tech players are securing “first-party data” through mergers, acquisitions, and partnerships. Every fitness app, every EdTech learning platform, every employer dashboard is quietly converting human behavior into proprietary data assets. It may be your movements and keystrokes on the job, your child’s learning patterns, or your health choices. Personal data is being harvested at scale without compensation, meaningful consent, or reciprocal value exchange.
The prevailing assumption driving this behavior is straightforward: data is the “new oil”, and the more you control, the more powerful you become.
That assumption is incomplete. And for the companies that have built their competitive strategy around it, the reckoning is coming from two directions at once.
– To watch this as a 13-min video
– To listen as a podcast
– Subscribe to our FREE Newsletter
Contact: https://10plusbrand.com/contact/
Moore’s Law (the observation that computing power roughly doubles every two years as costs decline precipitously) has long been treated as a technology phenomenon, but it’s really an economic one.
NVIDIA’s Jensen Huang has described what he calls a “Hyper Moore’s Law” in which AI performance improvements are being driven not just by silicon chips, but by advances in software, algorithms, networking, and data center infrastructure, potentially doubling or tripling performance each year.
Speaking in 2025, he said that when AI technology’s cost drops by 100,000 times every ten years, and when a large language model that can memorize and generalize from all of the data of humanity, “it becomes a commodity everybody should squander.” (Talk recorded by 10 Plus Brand.)
On top of that, “human generated knowledge and human generated data would today be 99%, in about 10 years it will probably be 1%. The vast majority of human knowledge will be generated by AI. It will be AI generated data that the other AIs learn from… it’s going to be synthetic generated intelligence. [T]hat’s just intelligence, it is not a big deal, It’s just data…that the amount of AI generated knowledge is to be incredibly high,” said Jensen Huang.
He didn’t think data – synthetic or not – is a big deal, because he said AI (and data that feeds AI) is just a tool. Human “first principle thinking” and human intelligence will always be the controlling force behind AI. Note: Jensen Huang’s (over) optimism about AI-human symbiosis is not the point here.
What this trajectory means for the customer data land grab is something few strategists are currently pricing in: the data being seized today at enormous financial, ethical, and reputational cost, will be exponentially cheaper in fewer than 10 years.
The companies spending hundreds of millions now to “lock in” first-party data assets are, in many cases, acquiring today’s fake diamonds at the price of real diamonds.
To use the analogy offered by ad tech strategist Tom Triscari: there are data “landowners” and data “farmers.” But in my opinion, neither controls a permanently scarce resource.
If what the “land” (data) yields, and what the “farmers” (land grabbers) grow will be worth next to nothing in 10 years, is the damage to trust and loss of customers worth the cost today?
There is a second, more immediate cost that the data land grab is generating, one that compounds daily and cannot be reversed with a product update or a privacy policy rewrite: Trust.
Scholars Ulises Mejias and Nick Couldry, in their book Data Grab: The “New Colonialism” of Big Tech, frame the issue in terms of a power imbalance in how data is gathered, stored, and used. They argue that, like the colonial “land grabs” of centuries past, there is now a “data grab” in which personal information becomes the raw material for corporate profit without the knowledge or meaningful consent of the people generating it.
During colonialism, at least, the land was taken away, fairly or by brute force, with the KNOWLEDGE of those who previously owned it. Today, the vast majority of consumers whose data is being taken have no way to know.
Your own personal data is being extracted without your knowledge on a daily basis: websites, social media, and the apps on your smartphones, you name it.
For those data grabbers who use ill-gotten data to inflate their search rankings, does this data land grab give them true advantage?
Now, the good news is that AI, with an intelligence of its own, seems to outsmart those who don’t play fair and square.
AI search systems are beginning to synthesize trust indicators, including customer reviews, media sentiment, employee advocacy, authoritative and original publications, and executive reputation, into signals that may soon function as “trust scores” determining brand visibility and recommendation outcomes. The days are on the horizon when paid visibility no longer compensates for credibility deficits.
My own recent success in helping a true industry leader proved it: After rebranding “The Ivy Group” (whose previous name was “Ivy Commercial” for 25 years), we had to open a new Google Business Profile under the new name, starting from scratch and losing many Google reviews under the old name.
With few Google reviews under the new name, about 18 months after 10 Plus Brand launched TheIvyGroup.com, ChatGPT ranked it as Number One among boutique commercial real estate brokerage firms in Fremont, California, thanks to thought-leading blogs and case studies we helped develop and publish regularly, among other factors. AI is getting smarter: It knows that Google reviews can be manipulated. It looks at many factors to rank who is #1 among extreme competitors.
The lesson for leaders is not that reviews don’t matter — it is that authentic authority, built through consistent thought leadership, is now the currency AI systems trust most.
In other words: AI itself is becoming the mechanism by which data exploitation backfires. The same AI infrastructure that companies are racing to feed with seized data is building the reputational record that will determine which brands survive the next decade.
And consumers are beginning to understand this. The 2026 brand visibility landscape has shifted significantly. As Forbes recently noted, audiences are now evaluating brands through AI-curated summaries and reputational signals rather than traditional paid media.
At least for now, AI is smart enough not to discount the TRUST factor.
There is a direct and under-appreciated relationship between data ethics and brand equity, the perceived value customers assign to a brand based on accumulated experience and trust.
Brand equity is a compounding and foundational asset. Positive brand equity reduces customer acquisition costs, increases pricing power, attracts top talent, and (critically in the AI era) generates the organic, authentic signals that AI systems use to determine which brands deserve recommendation and which do not.
The companies winning the data land grab today by extraction or theft are quietly losing the brand equity war.
The companies that will win the next decade are those that recognize this: the most valuable data asset a company can hold is the TRUST that causes customers to willingly share their data, advocate for the brand, and create the authentic content ecosystem that AI systems reward.
By no means am I moralizing against data driven AI. We at 10 Plus Brand build your brand’s success by first building a brand architecture, the sure foundation for a brand’s long term profits.
For executives and founders navigating today’s fast-changing AI landscape, three reorientations are essential:
(1) Ask whether your way of collecting data is hurting your brand trust and equity. Keep in mind that the data you are acquiring today has a depreciating competitive half-life. The trust you are eroding today compounds over time against you. Put a number to the real value of customer trust, in addition to the present value of data. Use a brand audit to assess the above.
(2) Treat authentic brand narrative that truly delivers brand promises as an investment in your future. AI systems are increasingly the gatekeepers for brand awareness, operating on trust signals and consistent storytelling across owned and earned media. A fragmented or untrue brand narrative that doesn’t inspire trust will be penalized by the AI systems your customers are using to make decisions.
(3) Recognize that the long-term winners in the AI era will be the companies that have built customer relationships based on trust, not the ones that grabbed the most data. The next generation of winners will be the companies that designed their AI-powered experiences to serve humans rather than extract from them.
The short term value of data land grab that shows up on this year’s balance sheet today, does not erase the diminishing value of those assets tomorrow. Most importantly, the growing cost of the trust being sacrificed to acquire them is far more damaging in the long term.
Leaders who see both sides of that ledger are the ones who will build something that lasts.
To explore brand strategy, AI experience design, and thought leadership development, please visit our websites at:
– Subscribe to our FREE Newsletter
Contact: https://10plusbrand.com/contact/
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. She is known for this principle: “User experience is brand experience, and brand experience determines enterprise destiny.”
© Joanne Z. Tan, 2026. All rights reserved.