Digital twinning

A Contractual Blind Spot In our primary research for the Fusion Work™ White Paper, which will land on the desk of Lee Barron MP later this year, senior HR leaders have told us candidly: “We have no idea how to contract for this.”

Digital twinning is the perfect example. Suppose you have an employee, a skilled HR advisor, an experienced sales consultant, or a senior engineer. Their experience, instinct, and ‘flair’ are captured through AI tools, chat logs, decision trees, recorded calls and used to train models that automate large parts of their job. When that employee leaves, or is made redundant, what happens to their digital twin?

If their insight lives on inside a system that continues to generate value, does the employee have the right to claim royalties? The right to delete? The right to know?

Today, no standard employment contract addresses this. Our research uncovered that not a single HRD we interviewed could say they were ready for this new grey area.

GDPR was not built for this

GDPR, powerful as it is, was designed for static personal data not for the dynamic, machine-learning era. It can handle your name, your address, your photos. But your decision logic, professional style and unique problem-solving approach? Those are new frontiers.

If an AI is trained on your performance, from your tone in client emails to the negotiation patterns you use to close a sale and then that data is baked into an AI model that lives on your employer’s server… does the ‘right to delete’ apply? Lawyers say: not yet clear. But the implications are massive.

Redundancy in the age of AI: Legal or a loophole?

This question is no longer theoretical. In the US, we’ve seen tech giants like Microsoft restructure teams, replacing entire layers of HR advisors with generative AI tools.

In the UK, employment law traditionally protects workers through fair redundancy processes. A job disappears? Redundancy is valid.

But what happens when the tasks stay and are simply moved to a machine? Is the job truly redundant?

Outcome vs. Process: A new contractual language

For centuries, employment contracts have paid humans for their time not for their outcomes.

The 40-hour week. The hourly wage. The overtime clause. All built for a time-based economy. AI changes that. Machines do process. Humans deliver outcomes.

Increasingly, the only defensible human role will be to oversee, guide, check, and deliver results that a machine can’t. This means we urgently need a new contract language. One that moves away from ‘tasks and hours’ towards outcomes and value.

The case for ongoing royalties

Artists have faced this for decades. A song they write earns royalties every time it plays. A painting sells again and again.

But for knowledge workers, no such precedent exists… yet.

Imagine this: A sales director trains an AI to pitch like them. Their conversational patterns, their charm, their winning lines all immortalised in code. For the next five years, that AI closes deals worth millions. The human is long gone. Should they get a cut? Or is their IP the company’s forever?

Today’s contracts are silent. But the next generation of workers may demand royalties for the enduring ‘flair’ their unique training gives an AI twin.

What should HR be doing?

So what does this mean for HR and people leaders?

1. Build AI clauses into contracts now.

2. Start outcome-based job design.

3. Prepare for legal battles.

4. Upskill your HR team.

5. Engage your workforce in the governance.

What should workers be asking for?

For employees, the ask is simple and radical. Insist on clarity:

  • How will your work be used to train AI?
  • Demand opt-out rights or royalties.
  • Push for outcome-based pay.
  • Ask for re-skilling.

A final word: The future is fusion

At Bloor Research, we’ve spent the past two years mapping what we call Fusion Work™ the integration of human talent with digital twins, bots and AI at scale.

The old model of fixed jobs, fixed hours and fixed tasks is dying.

What’s replacing it is mutable: people + machines, tasks + oversight, human outcomes + machine outputs. But the legal frameworks, HR policies and contracts must catch up, fast. Otherwise, we’re sleepwalking into a world where the machines know exactly what they owe us, but we have no idea what we’re owed in return. This isn’t about fear. It’s about foresight.