Anna Savage, CHRO at Form3, explores how machine learning is helping to rewrite the seniority dynamic and provide learning opportunities for all.
As artificial intelligence becomes embedded across all areas of business operations, from finance teams and product development to HR and marketing, there are still concerns that it is eroding employees’ ability to think independently and turning normal working practices on their head.
While these concerns may be justified, we are past the point of no return on AI, and it would be foolish to bury one’s head in the sand and pretend these developments are not happening.
Any firm wanting to implement AI properly needs a company-wide strategy that considers the impact on workplace dynamics and outputs. However, nearly half of organisations do not consult HR leads when building an AI strategy, according to research from IBM. This risks ignoring the very real impact that AI has on workplace dynamics, thereby limiting companies’ opportunities to really capture the benefits.
In fact, AI can offer enormous benefits to the way in which teams interact with one another, offering savvy junior employees a chance to get ahead and work more closely with their seniors.
Shaking up the dynamic
This is specifically because AI is increasingly flipping the seniority dynamic – junior and younger staff members are becoming the AI champions, overturning the traditional dynamic where experience sits only at the top. This does not mean that traditional experience is becoming irrelevant, but rather it challenges the assumption that the most senior person in the room must be the most knowledgeable by default.
An employee may be ‘junior’ in the organisational hierarchy, but more experienced than their senior colleagues in applying technology and AI to tasks to produce the best outcomes. The challenge here is ensuring that workplace culture and working practices can recognise this contribution – and encourage it – without insisting that an employee needs a management title to have their skills acknowledged and shared with colleagues.
In practice, this means that team members need a space wherein they can examine existing processes, spot where AI and automation can improve them and then feed back their findings. This requires managers to do more than just invite suggestions. A clear route needs to be established through which these AI champions can propose to showcase their skills or initiate a small trial, with the suggestion assessed on merit, not position. Contributions need to be assessed on how these employees develop and share expertise with the team, not just on the benefits they deliver themselves.
"Senior leaders need to participate as learners, rather than merely sponsoring the programme."
In the case of ideas not being taken forward, managers should clearly communicate why this is the case. Not doing so risks staff feeling that sharing their ideas is pointless. Choosing not to automate a task – and being able to understand why and what this means for the business – can be just as valuable as understanding the areas where AI is useful.
In terms of practical ways to implement this knowledge sharing, pairing AI-confident employees with experienced senior colleagues to find ways around a real business problem can create a clear space for collaboration. Within these dynamics, senior leaders need to participate as learners, rather than merely sponsoring the programme.
This also gives senior leaders a dedicated opportunity to share their own knowledge and lived professional experience with junior members.
For example, a junior employee could explain how an AI process can speed up decision-making internally, while a more senior member is able to explain how this supports the commercial ambitions of the business. This turns the dynamic from ‘who knows more’ to one based on mutual learning opportunities.
For these sorts of initiatives to be successful, all staff members must understand the why – discussions of how AI learning will impact roles, workloads and development need to happen out in the open.
"Seniority should provide accountability, without creating a monopoly on knowledge."
HR teams can also ensure that initiatives such as practical demonstrations, peer nominations or even workplace benefits to reward staff for making the whole team more ‘AI-versed,’ not just themselves.
Due to its ability to make the working day more efficient, AI learning needs to be directly blended into the daily activities of teams, with reverse mentoring becoming part and parcel of this. This way, teams can see how shared learning and developed AI literacy directly benefits them on a day-to-day basis
Ultimately, opportunities to become an AI champion must be open to all ages and levels of seniority, with equal access to tools and opportunity.
Experimentation with guardrails
When encouraging AI use within a company, clear lines in the sand are essential. Teams cannot just be told to “go and experiment”. A recent CIPD case study revealed that a lack of designated oversight on safe and strategic use of AI led to uncertainty and uneven uptake.
To ensure this is not the case in their own organisation, HR and workplace development leaders need to work closely with IT teams, security and relevant specialists to ensure that approved tools and practices are clearly communicated to employees. Employees of all levels should also be encouraged to share scenarios of where AI didn’t work, as this shifts the focus to responsible learning rather than creating a pressurised environment where success is the required outcome.
By encouraging teams to also apply their own critical thinking to how they use AI, CHROs can expect to see growing employee confidence in AI-enabled decisions.
The way forward
Ultimately, this is not about replacing one hierarchy with another or suggesting that AI expertise is a substitute for decades of professional experience. Instead, it is about HR leaders creating a space in which employees can contribute new approaches while remaining open to challenge, whatever their job title.
The best AI champions are those helping colleagues make better decisions about when and how to use AI tools. In response, seniority should provide accountability, without creating a monopoly on knowledge.
