Trust runs everything. It’s what makes a stranger feel safe getting into a car, what makes a patient let an aide into their home, what makes a company hire a worker they’ve never physically met. Take trust out of those moments and the whole thing falls apart.

Right now, that trust is getting harder to be confident in. Some industries are running on almost none of it. And fixing that is going to take everyone caring about it the same way—every role, every industry, every side of every relationship.

How Business Treat Trust

Most businesses in practice verify trust only once. At hire, a background check runs—typically a look at criminal history, maybe one other verification of some sort. The candidate passes. The job begins. Trust is given.

That was the whole model. A single moment, a single lens. Identity wasn’t confirmed in any real way. Credentials weren’t validated. The picture of who someone was checked one time.

That approach always had gaps. It just had fewer consequences when fraud was harder to pull off. The background check aged more slowly. The risks were more predictable. The gaps were easy to ignore.

Some industries got forced to confront this faster. Gig platforms, pushed by regulators and the scale of their workforces, started building more continuous and more complete verification earlier than most. But even that didn’t close the problem. Fraud kept growing, the tools for deception got better, and the gap between when trust was established and when it was assumed became exactly what bad actors learned to find and use.

Every industry is heading toward the same reckoning. The point-in-time, criminal-history-only model was never fully adequate for anyone.

The War on Trust

Here’s what the gap looks like when someone finds it.

In 2024, a fraud operation used over 2,000 stolen identities to create verified gig driver accounts. The identities passed background checks. The accounts looked legitimate. The operators then rented those accounts to people who had never been screened. One person ran this scheme for nearly two years and made close to $800,000 before anyone caught it.

The platform hadn’t failed to verify those workers. It had verified them… once, at the start. After that, the accounts were treated as permanently trustworthy. The fraud lived entirely in the gap between when trust was established and when it was assumed.

That gap is getting more expensive everywhere. An engineering firm lost $25 million because of a single video call in which every person on screen was an AI-generated deepfake of a real colleague. An employee approved fifteen wire transfers, and they weren’t exactly careless. The call just  looked exactly like every call before it.

These aren’t isolated incidents. They’re what happens when the tools for deceiving people get cheap and the infrastructure for maintaining trust stays frozen at hire. Deepfake attacks grew 880% in 2024. Employment scam losses reported to the FBI grew 276% in a single year.

The point-in-time model was always a gap. Fraud is just making it impossible to look away from.

What “Universal” Actually Means

Making trust universal means making it work for everyone, across the full length of every relationship.

Both parts of that matter equally.

Everyone means workers and the people they serve. The customer at the door, the patient in the home, the client on the job site. When trust is maintained on one side of a relationship and assumed on the other, it isn’t really trust. Universal means the worker carries credibility that’s current and recognized. The customer knows that credibility has been kept up, not just established once. Everyone in the relationship gets something real.

Across the full length means trust that doesn’t expire at hire. A worker verified at onboarding and never checked again isn’t a trusted worker… they’re a worker who passed a test a year ago. A lot can change in a year. Credentials lapse. Circumstances shift. The relationship between a worker and the people they serve is continuous. The trust behind it should be too.

In the industries where this matters most (like healthcare, gig work, and staffing) the trust between two people in a room is the actual product. When that trust is current and real, something shifts. Workers build credibility that follows them and means something. Customers stop hoping they’re safe and actually are. Employers make better decisions because their view of their workforce reflects reality, not a snapshot from months ago.

Trust maintained over time produces outcomes that a single background check never can. That’s what universal means in practice.

What This Moment Is Demanding

The fraud environment is moving faster than most organizations have kept up with.

AI tools that can impersonate a colleague on a video call, generate fake credentials, or clone a voice from a few seconds of audio are available to anyone with an internet connection.

Every organization that depends on trust between people is carrying some version of that gap. The question is how wide it is and what happens when someone finds it.

Trust has to be treated as infrastructure. That means verification that extends past hire, identity that gets re-checked when it matters, and credentials monitored and kept current.

The organizations that have done this report more beneficial outcomes than fewer fraud incidents. They report that workers stay longer, customers trust the service more, workforce decisions improve because the data is current.

Trust, maintained continuously, generates returns that a single background check at hire never could.

For a long time, verifying trust once at the start of a relationship was enough.

The world has changed around that assumption. The tools for deceiving people are better. The workforce is more distributed. The relationships that run on trust happen at higher volume, between more strangers, with less oversight than before.

Making trust universal means building infrastructure that carries it forward. This is everyone’s problem now.

That problem is what Yardstik is built to solve. The future of trust between people depends on infrastructure that’s as universal and continuous as the relationships it protects.