What is an AI digital twin like Digital Richard?

An AI digital twin is a digital replica of an employee, trained on their work data to mimic their knowledge, thinking, and problem-solving abilities to assist in business decisions and tasks.

How are companies like Bloor Research using digital twins?

Companies are using digital twins to enhance employee productivity, manage phased retirements, and cover workloads during employee leave, reducing the need for temporary staff and boosting overall output.

What are the main concerns regarding AI digital twins?

Key concerns include who owns the AI digital twin, how employees should be compensated for increased output, who has access to personal data within the twin, and who is responsible for any mistakes made by the AI.

Home / Technology / Your AI Twin: Work Smarter, Not Harder

Your AI Twin: Work Smarter, Not Harder

17 Apr

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Summary

AI digital twins mimic employee knowledge and work styles.
Companies offer digital twins to boost productivity and flexibility.
Ownership, pay, and data access are key legal and ethical questions.

Richard Skellett has developed an AI twin, dubbed "Digital Richard," by training a language model on all his work-related data. This digital replica assists him in business decisions and client presentations, functioning as an extension of his analytical capabilities. Bloor Research has since expanded this concept, creating "Digital Me" twins for its 50-strong team across the UK, Europe, US, and India.

These digital replicas offer significant benefits, enabling phased retirement and covering workloads during employee leave, thereby reducing the need for temporary hires. The technology is being tested by over 20 companies and will be widely available soon, with Gartner predicting mainstream adoption of digital replicas for knowledge workers. Meta's development of an AI version of Mark Zuckerberg is also expected to fuel interest.

However, the rise of digital twins raises critical ethical and legal questions. Issues of ownership—whether the employer or employee owns the twin—and appropriate compensation for increased output are paramount. Access control and responsibility for AI errors are also key concerns, with experts like Kaelyn Lowmaster from Gartner emphasizing the need for strong governance.