The idea of having a digital version of yourself handling tasks, making decisions, and even assisting in daily life is quickly moving from concept to reality. Known as “digital twins,” these AI-powered replicas are being developed to mirror an individual’s knowledge, communication style, and decision-making approach—raising the possibility of turning employees into so-called “superworkers.”
One such example comes from Richard Skellett, a senior analyst at Bloor Research, who has spent the past three years building an AI twin of himself. His digital counterpart, often referred to as “Digital Richard,” is designed to replicate how he thinks and works.
Unlike a standard chatbot, this AI model has been trained on Skellett’s professional data—including meetings, documents, calls, and presentations. It was further refined to reflect his analytical style, allowing it to assist with business decisions, client presentations, and internal queries.
The system operates through a text-based interface, where Skellett—or even colleagues—can ask questions and receive responses aligned with his expertise. It is also divided into sections, with certain areas such as personal or family matters restricted from workplace access.
Following its success, Bloor Research has expanded the concept across its workforce, creating similar digital twins for its team members across multiple countries. In some cases, the technology has already demonstrated practical benefits. Employees nearing retirement have been able to reduce workloads gradually, while others on leave have had their responsibilities partially handled through their digital counterparts.
The company now includes a “Digital Me” as part of its standard setup for new hires, and several other organizations are reportedly testing similar systems. Industry analysts at Gartner predict that digital replicas of knowledge workers could become mainstream in the near future, especially as artificial intelligence continues to evolve.
The concept is also gaining attention among major tech players. Reports suggest that Mark Zuckerberg’s company, Meta, is exploring the idea of AI versions of individuals, further fueling interest in the technology.
Proponents argue that digital twins can significantly enhance productivity. Josh Bersin, CEO of The Josh Bersin Company, has implemented similar tools within his organization. According to him, tasks that once required meetings or lengthy communication can now be handled through quick interactions with an AI twin.
Bersin describes this shift as the rise of the “superworker,” where individuals are empowered to achieve more with the help of AI. These digital assistants can operate continuously, respond instantly, and provide insights without the constraints of time or energy.
However, despite the clear advantages, the growing use of digital twins raises complex questions about ownership, ethics, and employment rights.
One major concern is who actually owns the digital twin. While Skellett believes individuals should retain ownership and potentially earn from its use, others argue that since the data used to train these models often belongs to the employer, the company may have a stronger claim.
Another issue is compensation. If an employee’s digital twin increases productivity, should they receive higher pay? Some companies are already shifting toward performance-based compensation models, where earnings are linked to outcomes rather than hours worked.
Privacy and control also remain key concerns. Experts warn that training AI systems on personal work data—such as emails and meetings—could blur the boundaries between professional and personal information.
Kaelyn Lowmaster notes that while the benefits are promising, the risks cannot be ignored. She emphasizes the need for proper governance, clear rules on data usage, and safeguards to ensure individuals retain control over their identity and digital representation.
Legal experts are also grappling with how existing employment laws apply to this emerging technology. Anjali Malik from Bellevue Law points out that digital twins touch on fundamental issues such as consent, data ownership, and the substitution of human labor.
Similarly, Chloe Themistocleous of Eversheds Sutherland believes that clearer legal frameworks will be needed to manage risks for both employers and employees. Without proper regulation, disputes could arise over accountability—particularly if a digital twin makes a mistake.
Another potential challenge is long-term relevance. If an employee leaves a company, their digital twin may gradually lose value as it becomes outdated, raising questions about its continued use.
As businesses continue experimenting with AI-driven digital twins, the technology’s future will likely depend on how these ethical, legal, and economic issues are addressed.
For now, the concept of becoming a “superworker” through AI remains both an exciting opportunity and a complex challenge—one that could reshape the nature of work in the years ahead.
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