Could a digital twin make you into a 'superworker'?

Richard Skellett, chief analyst at technology consultancy Bloor Research, has developed a digital twin of himself—an AI-powered "Digital Richard" that replicates his knowledge, decision-making style, and problem-solving approach. This digital version, created using a combination of ChatGPT and a custom language model, processes Skellett’s meetings, calls, documents, and presentations, enabling him to consult it for business decisions and client interactions. The digital twin also assists with personal tasks, with certain tabs restricted to Skellett alone, while colleagues can access work-related information. Bloor Research has expanded the concept to its entire 50-person team across the UK, Europe, the US, and India, using digital twins to manage workloads and transitions more efficiently. For example, an analyst approaching retirement was able to phase out work gradually by delegating tasks to their digital twin, and a marketing team member’s AI replica covered responsibilities during maternity leave, eliminating the need for temporary hires. The company now offers a "Digital Me" to all new employees, and around 20 other firms are testing similar technology, with wider availability expected later this year. Industry experts, including Gartner analysts, anticipate that digital replicas of knowledge workers will become mainstream, paralleling AI trends in mimicking artists’ styles and tones. Meta’s reported development of an AI version of CEO Mark Zuckerberg further underscores the growing interest in digital twins. However, the technology raises significant questions about ownership, compensation, access rights, and accountability. Key concerns include whether employers or employees own the digital twin, if users should receive higher pay for increased productivity, who controls access to sensitive information, and who bears responsibility for errors made by the AI. While digital twins promise enhanced efficiency and continuity in the workplace, their successful adoption hinges on establishing clear governance frameworks, defining the autonomy of AI agents, and addressing ethical and legal implications. The balance between leveraging these tools for productivity and safeguarding individual rights remains a critical challenge as the technology evolves.