What if You Become a Team or an Entire Company? The Promise of Digital Twins in the Transformation of Working Life
The future of work may not be about replacing humans with machines, but multiplying human capacity through digital twins that work simultaneously across multiple tasks. This transformation promises unprecedented productivity gains, but raises profound questions about compensation, ownership, and labour rights when one worker can do the work of five.
Text Martti Asikainen, 1.12.2025 | Photo by Adobe Stock Photos
Imagine a working day where you participate in a strategic negotiation in Helsinki whilst your digital twin analyses market data in Stockholm, another reviews customer feedback and responds to urgent emails, and a third monitors an international meeting and takes notes. All of this happens simultaneously, and each of your twins operates with your style, preferences, and expertise. This is not science fiction, but the promise of digital twins that will transform working life.
This vision is based on the idea that AI assistants are evolving from their current state towards increasingly autonomous and personalised systems. The next leap in labour productivity will likely come not from automation or robotics, but from the integration of digital twins into working life. When an individual employee can mobilise entire fleets of twins for different purposes—complete with AI agents, preferences, and operational methods—traditional models of organising work will inevitably need to be reassessed. Recent research also provides evidence of similar shifts in productivity dynamics (Agrawal et al. 2023; Wu & Sundararajan 2025).
Idea of Digital Twin Attracts Criticism
A digital twin is a virtual copy of a physical entity or product that is connected to the real object through a data link (Semeraro et al. 2021). The most accurate representation of the physical product is created by utilising complex physical models, data from the product’s sensors, and other relevant information (Schleich et al. 2017; Tao et al. 2017). It is a continuously updating digital system and model based on real-world data that can specialise in a particular subject and be assigned specific tasks (see Abdelrahman et al. 2025).
When discussing a human digital twin, the objective is a transformation that improves decision-making, processes, and productivity by integrating the physical person with the digital world. This notion reflects academic perspectives on human-centred digital twins, which emphasise adaptive, continuously updating representations of human expertise (see Asad et al. 2023; Lin et al. 2024). However, current technology does not yet enable fully autonomous agents that adopt personal styles at the scale described here.
Twinning a physical system with a functional replica is not a new phenomenon – the practice traces its roots back over 50 years to the space sector. The advancement of digitalisation has opened up new opportunities to utilise data, deepen understanding, and improve situational awareness of physical systems’ performance. Growing interest in the concept has led to numerous definitions of digital twins, which are used to structure the discussion and distinguish between different types of implementations. (Boyes & Watson 2022)
Despite this, the ideational shift alone has already attracted considerable criticism and speculation regarding structural transformation in the labour market. Many are pondering how the framework of human capital theory will change when an individual’s productivity potential is no longer limited to cognitive and physical capabilities but extends to digital twin complements. At the same time, organisations must reassess resource allocation in a situation where one employee’s twin group produces value equivalent to the work input of five people.
When One Employee Does the Work of Five
The practical application of digital twins is already evident particularly in consulting, education, research, and design, where experts utilise various tools and AI agents simultaneously. Early research already shows that AI-based twins can take on multiple tasks in parallel, effectively multiplying an individual’s work input (Chan et al. 2025; Wu & Sundararajan 2025). One can draft a report, another participate in a meeting and transcribe discussions, and a third analyse large data sets. The next natural step towards such systems is closer integration of these tools across different platforms and personalisation.
From an economic perspective, the proliferation of digital twins would create an entirely new model of value creation, where the marginal cost of productivity approaches zero as it scales. Economic modelling also demonstrates that AI-based twin systems have the potential to push the marginal costs of additional work tasks towards zero (Wu & Sundararajan 2025). This challenges conceptions of traditional compensation structures, as it becomes unclear whether remuneration should then be proportioned to the value produced, time spent, or resource allocation.
Moreover, the ownership relationship of the twin infrastructure would become a key factor in determining bargaining position. Case studies show that when AI systems mediate or augment labour, typically ownership determines bargaining power and role (Malik & Brem 2020). This also raises the question of how income distribution policy and social security systems should be structured in a situation where a small proportion of workers produces exponentially more value than before, but a large part of the population may be left entirely outside the new production model.
Traditional progressive taxation is based on the idea that income growth correlates linearly with an increase in workload or expertise. In the world of digital twins, this relationship would break down when an individual’s income-generating capacity could multiply without a corresponding increase in effort. This would also challenge the traditional role of trade unions, as collective bargaining power has historically been based on limiting the supply of labour—but how is it possible to negotiate if the supply of labour is, technically speaking, virtually unlimited?
The Paradigm Shift in Recruitment
The arrival of digital twins in working life would also revolutionise traditional models of recruitment and career planning, as a job applicant would bring not only their own expertise and experience, but an entire digital team—a curated group of specialised assistants trained to support their work. A job applicant’s value would then increasingly be determined by their ability to orchestrate and lead this team composed of humans and AI twins.
With this change, recruiters would also need to assess not only the applicant’s personal expertise, but also the quality, diversity, and integration of their digital tools. This shift aligns with early frameworks positioning digital twins as collaborators that influence how human skill is evaluated (Agrawal et al. 2023). Questions such as what kinds of AI assistants do you have available for analytics, marketing, and data processing, or how do you manage the coordination of multiple digital assistants, would become part of the normal interview process.
But what weight should be given to the applicant’s own expertise if efficiency were actually based on the capability of their agents and digital twins? This might completely change our understanding of competence and value creation in an organisation. At the same time, we would have to consider what it means to collaborate if one’s closest colleague were another person’s digital twin. When would we encounter the real human being, and would it really even matter if the AI is also capable of performing the task flawlessly?
At the same time, leadership would also be significantly democratised. Early experiments with AI-partnered workflows suggest that individuals already act as leaders of multiple autonomous agents (Chan et al. 2025), supporting the idea of distributed leadership. When every employee leads their own digital team, hierarchical organisational structures flatten and blur, and decision-making is distributed more widely. The traditional model of one leader and many subordinates could be replaced by a network-like structure where everyone is both the leader of their digital assistants and a collaborator with other digital teams. Leadership skills would then become a universal competence rather than a role tied to hierarchy.
Who Would Bear Responsibility for the Twin
Research on digital twins also raises significant ethical and legal questions. Researchers have for some time emphasised unresolved accountability issues concerning particularly privacy, autonomy, and the delegation of decision-making to twins (Naudet 2021; Davila-Gonzalez & Martin 2024). When a twin makes decisions or produces content in the name of its physical counterpart, who would bear responsibility for possible errors or damages? Traditional employment law is built on the assumption that the employee themselves performs their work tasks, which might no longer hold true when part of the work is delegated to digital assistants.
The question of confidentiality and data security would become particularly challenging. If a digital twin handled sensitive customer data or trade secrets, how would one ensure that data does not leak or fall into the wrong hands? Or that the twin does not compromise data by handling it carelessly? Organisations would need to develop entirely new data security protocols that would account for both the human propensity to err or succumb to carelessness, and AI activity in the work environment.
The question of copyright and intellectual property rights would also become more complex. If a digital twin created an innovation, invention, or creative work, who would own the rights—the employee from whom the twin was made, the employer who owns the twin, or perhaps the twin’s developer or maintainer? Our legislation does not recognise AI as a legal subject, but practical situations may force us to consider these questions from entirely new perspectives as well.
Less Work, More Value
Despite the challenges, the integration of digital twins could also offer significant opportunities for building a more humane working life. Worker-centric twin research also provides such indications by proposing digital twins as tools for reducing cognitive load and improving well-being (Davila-Gonzalez & Martin 2024). If an employee could delegate routine tasks and time-consuming processes to their digital assistants, they would have more space for creativity, strategic thinking, and human interaction.
In practice, this could mean significant improvements in work-life balance. A parent could participate in their child’s day care in the middle of the working day whilst their digital twin simultaneously handled a routine meeting. A creative worker could focus better on the creative state and innovation in demanding tasks whilst their twin took care of emails and schedule coordination. The risk of burnout could also decrease when people would not need to do everything themselves.
Paradoxically, one can thus observe that technology with the potential to multiply productivity could also lead to a situation where people work less but produce more value—and above all, find their work more meaningful. Digital twins could handle what can be automated, leaving humans with the tasks that make work rewarding: problem-solving, creativity, strategic thinking, and meaningful human relationships.
This would require, however, a change in attitude. Employers would need to abandon presence requirements and time-bound work, and evaluate performance based on actual value creation, not working hours. At the same time, employees would need to learn new skills. Several reviews note that effective use of human digital twins would require new competencies in collaboration, interpretation, and oversight alike (see Lin et al. 2024). In other words, employees would need to learn about leading digital teams, the ability to communicate with AI, and critical evaluation skills and AI literacy.
The digital twin revolution is ultimately a question of whether we build systems that concentrate power and wealth or democratise productivity and liberate human intellectual capital for more meaningful work. These questions demand answers not only from oligarchs and technocrats, but also from workers, leaders, policymakers, and citizens. The future of work is being written now, and each of us has a view on how it should unfold.
References
Abdelrahman, M., Macatulad, E., Lei, B., Quintana, M., Miller, C. & Biljecki, F. (2025). What is a Digital Twin anyway? Deriving the definition for the built environment from over 15,000 scientific publications. Building and Environment, 274, Article 112748. https://doi.org/10.1016/j.buildenv.2025.112748
Agrawal, A., Thiel, R., Jain, P., Singh, V., & Fischer, M. (2023). Digital twin: Where do humans fit in? arXiv:2301.03040.
Asad, U., Khan, M., et al. (2023). Human-centric digital twins in industry: A comprehensive review of enabling technologies and implementation strategies. Sensors, 23, 3938.
Boyes, H. & Watson, T. (2022). Digital twins: An analysis framework and open issues. Computers in Industry, 143, 103763. https://doi.org/10.1016/j.compind.2022.103763
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Schleich, B., Anwer, N., Mathieu, L., and Wartzack, S. (2017). Shaping the digital twin for design and production engineering. CIRP Annals, 66(1), 141–144. doi: 10.1016/j.cirp.2017.04.040.
Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., and Sui, F. (2017). Digital twin-driven product design, manufacturing and service with big data. The International Journal of Advanced Manufacturing Technology, 94(9-12), 3563–3576. doi: 10.1007/s00170-017-0233-1
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Martti Asikainen
Communications Lead
Finnish AI Region
+358 44 920 7374
martti.asikainen@haaga-helia.fi
This article has been published as part of Haaga-Helia’s AI and Equality in Work Communities project, which promotes the equal and ethical use of artificial intelligence in expert and knowledge work in a sustainable and inclusive manner. The project’s main funder is the Finnish Work Environment Fund.
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