Why Selling Data Will Bite You Back - Xist4

January 15, 2026

Why Selling Data Will Bite You Back

What GM's Data Drama Can Teach Tech Firms

Imagine you buy a car—a brand new, shiny, top-spec bit of engineering. You drive it, live in it (if you're in London traffic), and it quietly hoovers up your location. That’s fair… sort of. But then imagine that same data gets flipped to a broker, passed to an insurer, and suddenly your premium jumps—with no explanation.

That’s what landed General Motors in hot water. The FTC just settled its headline-making case against the automotive giant, banning GM from selling geolocation data to third parties. The ruling says a lot about where privacy expectations are heading. But it also speaks volumes about data trust, consumer loyalty, and operational risk—especially if you're a tech-led scale-up building systems and experiences atop data stacks.

I’m not here to lecture on car companies. I’m here to unpack what this means for companies hiring in BI, data, cloud and beyond. Because make no mistake—data strategy is hiring strategy. And this GM episode? It’s a cautionary tale wrapped in leather seats.

Privacy is a product feature, not a compliance chore

Let’s start with the obvious. In 2024, privacy is no longer a checkbox—it’s a competitive differentiator. Customers won’t just leave when you misuse their data. They'll slag you off in Slack threads, Slack channels, maybe even slap you with a class action lawsuit. Fun.

That means how your data team operates—what’s tracked, where it’s stored, who can see it, and how transparent you are—matters more than ever. Here’s where recruitment comes in:

  • Are you hiring data professionals who know privacy legislation (and care)? You don’t just want SQL maestros. You want ethically minded data people who ask "should we?" not just "can we?"
  • Are your BI hires equipped to support privacy-by-design? Modern dashboards must balance insight with anonymisation and access control. That's a hiring spec, not just a dev ticket.
  • Infrastructure and cloud engineers have to embed security principles from day one. No point buying a Fort Knox firewall if your S3 buckets are wide open.

Privacy isn’t the Data Protection Officer’s job. It’s a mission that cuts across engineering, product, legal, marketing—and yes, recruitment.

Dodging the data trust trap

Brands lose trust faster than a LinkedIn InMail gets ignored. And once trust is compromised? You’re spending thousands on PR firms trying to stitch it back together.

GM got snagged because they seemingly told drivers they weren’t collecting location data… and then did it anyway. That’s the worst kind of shady. And trust me, candidates talk. Engineers gossip. And smart people don’t want to work for companies that play fast and loose with data.

If you’re scaling a product—especially in fintech, greentech or health—then:

  • Your trust score impacts your employer brand. A dodgy track record doesn’t just lose customers. It scares away A-grade engineers and product brainiacs.
  • Trust is dynamic. Every shortcut an early hire takes with data config, access, or routing is a potential future headline. And a future FTC slap.

Want a talent moat? Build a trust moat.

Engineering culture is ethical culture

Let’s talk culture. Not foosball-table-and-oat-latte culture. I mean real culture—the invisible code that dictates how decisions are made when nobody’s watching.

If you’re building a data-rich platform (which, let’s be honest, everyone is), you must instill a culture where questions like:

  • “Why are we collecting this data?”
  • “Who gets to access it?”
  • “Would a user be cool with this?”

are not seen as time-wasting faff, but signs of maturity. And the people who embed those questions in your org? Your early data hires. Your lead engineers. Your tech leads.

Get this wrong, and you’ll build a team that sees data as oil to be extracted, not a responsibility to be stewarded. Get it right, and you’ll have a product that users trust, investors believe in, and regulators leave alone.

The hiring litmus test: ask this one question

So here’s a simple hiring tip for anyone scaling a data-driven team:

Ask: “Tell me about a time you said no to a data request.”

You’ll separate the conscientious from the cowboy pretty quickly. If someone has never questioned a data pull, pipeline, or marketing access request? They’re either brand new or dangerously naive.

The best candidates know that every data decision has downstream consequences. Like getting sued. Or killing customer trust. Or completely tanking your IPO prospects. You know, minor stuff.

Conclusion: Trust is the ultimate product feature

GM just learned something the hard way—mishandling user data is very, very expensive. Not just in fines and legal wrangling, but in brand damage, customer churn, and team morale.

If you’re scaling a tech-led business, you ignore data ethics at your peril. From how you structure your team, to the attitudes you hire for, to the systems you build—trust has to be engineered. Not just hoped for.

And remember: what you do today with user data might not be illegal yet… but give it 18 months, and regulators will have receipts.

So be smart. Build right. Hire better.

And don’t be the next headline.



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