Discover how AI is becoming your new colleague and transforming 80% of jobs

For the original Dutch Newsletter please find us at: Digibeter Substack

The rise of AI is changing our work. We have already discussed the changing role of the CIO (Part 1) and the impact on the work of employees (Part 2). In this newsletter, we zoom in further on the demands we can make on the knowledge, skills and “behavior” of our digital colleagues and how to work effectively with them.

AI’s new role as a digital employee

Generative AI and other forms of artificial intelligence are evolving into digital employees who can increasingly be carried and thus employed as human colleagues. There are different insights in research, but on average AI is expected to impact at least 80% of all jobs. The degree of impact depends on the amount of information processing work we do.

Especially in knowledge-intensive economies, this percentage can be high. After proper training, these AI systems can perform tasks previously done by humans, such as creating content independently, analyzing data and making decisions. In other words, AI makes its own action decisions. This means that AI is no longer just a tool, but will increasingly become an active participant in the business process.

Just as we place high demands on our physical employees, it seems logical to place high demands on these digital employees as well.

High standards for our digital employee

Just as we have high standards for our physical employees, we must also have strict criteria for our digital employee. These include:

Possessing the right competencies: A digital employee must be able to perform complex tasks with a high level of accuracy and efficiency, following the organization’s guidelines, templates and procedures. This includes analyzing large amounts of data, creating content that aligns with organizational tone, and making decisions. The knowledge competencies (data) of the digital employee must be closely aligned with the requirements of the organization’s process, culture and way of working. To achieve and maintain this, investments in education and training are necessary, with preference given to training by the direct physical colleagues with the same work from the process where the digital counterpart is deployed. They can provide the digital counterpart with the best digital knowledge and also best ensure that it remains appropriate.
Passen in het team en de cultuur: De digitale medewerker moet harmonieus integreren in het team en de heersende bedrijfscultuur. Fysieke collega’s dienen bereid te zijn om hun digitale collega’s te accepteren en effectief met hen samen te werken. Daarnaast moeten organisaties en medewerkers in staat zijn om de competenties van digitale collega’s adequaat te selecteren en te beoordelen. Onvoldoende competenties en kennis kunnen leiden tot onbetrouwbare output van (Gen)AI, wat weer kan resulteren in fouten, inefficiëntie en reputatieschade voor de organisatie.
Ethical standards: The digital employee, like a physical employee, must operate fairly, transparently and, as far as possible, free of bias (BIAS). It is essential that the digital employee be able to fully justify and explain decisions. This is critical to maintaining the trust of both the organization and other stakeholders. It also minimizes risks of discriminatory or unfair decisions due to unconscious bias. When “hiring” the digital colleague, the organization must ensure that there is no modern slavery, copyright infringement or other improper use of resources by the digital employee. It is important that the organization knows that no “click workers” are involved in the models and algorithms, and that the model is not fed with data that the organization does not support. It must be possible to control the input, processing and output of the digital worker.
Reliability: The digital worker must perform consistently and deliver predictable results to ensure reliable and consistent output. This is essential to maintaining the quality of operations and helps build and maintain trust in the technology used. Digital employees play a stable and supportive role in the organization.
Adaptability: The digital employee must be able to adapt to changing conditions, new information and evolving work processes. Like physical employees, digital employees must be agile and able to move with new situations and requirements within the organization.

Management and Assessment: Like physical employees, digital employees should receive regular feedback and be assessed to verify and optimize their performance.

Performance Monitoring: Digital employees must be open to performance monitoring and be adjusted based on results. It is essential that they consistently meet set standards and goals, especially after updates, to ensure efficiency. After all, just like physical employees, digital employees can suddenly have different thoughts after a very inspiring training session that may not align with how your organization views the world.
Feedback loops: As in the physical world, digital employees must open up to feedback mechanisms such as 360-degree feedback-like mechanisms. This allows the organization to adjust them and optimize their performance through input from stakeholders and ethical review committees.
Identity and Access Management: Just like our current employees, our digital counterparts may not simply perform every step of a process independently. It must therefore be monitored that AI systems do not start acting differently than how they were intended. Sometimes it is particularly good as here in the game AlphaGo but doing something totally new is not always desirable. It is therefore recommended that proper roles and rights separations be set up and checkpoints built in that involve physical employees. It also seems prudent that not every digital employee in the process is equal (the same model).
Audit and Transparency: Like physical employees in critical parts of work processes, digital employees must submit to regular audits to have their decisions and actions verified. It is critical that they be transparent about how they work and the judgment and decision-making that has been made. They must be able to explain themselves, Explainable AI. This can be done by, among other things, identifying the (most important) factors that influence a decision. But also by being able to explain their own operation and in language understandable to stakeholders involved in the process.

Dependence on digital colleagues

Besides specific demands on our (digital) colleagues regarding their function (knowledge and skills) and behavior, we do not want our employees to simply come from all over the world. Some cultural differences in management and output simply don’t work. Let’s reach out and look at our work as trainers and consultants. Those cultural differences that a trainer brings are not equally desirable in every situation. Moreover, we strive as much as possible to maintain sovereignty and certainly don’t want to give away our trade secrets. Cultural differences also make it less easy, in some cases, for employees to function within our norms and values.

Imagine if we decide to attract many employees from, say, Russia or America. If those countries recall their employees for political reasons (such as war), all work stops and all knowledge is lost. This also applies to our new digital employees. Therefore, we look for reliable, verifiable employees who meet all these requirements. In several cases, this will mean that in the first place we want to look at Dutch and European digital colleagues. If we look far outside Europe, we risk knowledge leaking away and investing in similar organizations in the Netherlands and Europe is not opportune. In an emergency, we then have no access to a digital employment agency for a good new digital colleague. This does not mean that we do not accept employees from outside the Netherlands or the EU at all. In some cases we need a high-quality knowledge worker from another country who can do something that is not (yet) possible here. But in general, we give priority to our own employees within the EU and the Netherlands, possibly with extra attention to their development.

Although we sometimes need to look outside the door for that one unique (digital) employee, it is not desirable to be completely dependent on external forces.

Conclusion

The integration of AI as a digital colleague offers immense potential, but also poses new challenges and requirements. As with our human employees, we must set high standards for the competencies, reliability, and ethical standards of our digital counterparts. It is essential that these systems be carefully trained and monitored so that they can integrate seamlessly into our teams and processes.

It is not only important that AI systems work effectively and efficiently, but also that they fit within the culture of the organization and operate ethically. Transparency, control and ethical considerations must be at the heart of implementing AI into our work processes. By investing in education and training, we can ensure that our digital colleagues are always up-to-date with the latest developments and best practices and can add great value.

However, we must also be careful about our reliance on digital collaborators from other regions to protect sovereignty and trade secrets. Therefore, it seems wise to prefer local and European solutions, while remaining open to unique expertise from outside the region when needed.

We would have liked to go more in-depth on the collaboration between the physical and digital employee in this newsletter but for the sake of newsletter length we will take it to the next one. So in the next edition, we will go deeper into the collaboration between physical and digital collaborators. We will discuss how to create synergy between humans and machines so that together we can build a more efficient and effective workplace. Keep following us for more insights and practical tips on this fascinating evolution in the world of work.

This text is automaticly transcribed by AI