In the boardroom, we call it risk management. In HR, resilience. In marketing, futureproofing. What we all really want is accurate predictions on when what is going to change, and solutions on how to delay – or ideally, prevent – the impact of those predictions.
When the advice to quell this fear-fuelled need for predictions is “you can’t prevent it, you have to adapt to it”; we, however, refuse to accept it.
Instead, we lay the responsibility for adaptation at someone else’s feet, or we launch initiatives to figure out how to be the one company that withstands the storm and remain “resilient” while others experience ruin. Or we create and try to enforce preventative rules that simply result in busy work we can use to make ourselves feel more in control. All this is merely masking our ongoing search for an answer that will better align with how we thought/hoped/planned things would be in our future.
To effectively respond to looming change (with the added threat of mass layoffs due to advancements in artificial intelligence), knowledge workers – and their employers – don’t need more predictions on what exactly will happen over the next two years as AI wrecks well-laid plans like coffee spilled over last-minute homework. They (we) need to buckle down and get to work. Different work.
Refocus training and development
If most knowledge workers are going to be managing AI agents in the near future, the skills they need to develop now isn’t coding. As the strength of AI – generative and agentic – lies in “doing”, we need to strengthen our human workforce on the part that AI is predicted to always need support; original, complex and organic thinking.
Training and professional development plans for knowledge-based workforces must – across all employment levels – incorporate critical thinking, ethical reasoning and clear communication. Not just a company-wide townhall simply mentioning the broad topics, and also not a postgraduate degree in any of it. Just something that will equip a wide base of employees with the basics of these skills so they can focus on honing the skills as quickly as possible.
The development of these skills might be slightly less urgent for manual labour workforces, but even in the trades the AI spill is starting to soak the edges of tertiary education, product design, quality assurance and logistics.
Adapt policy making processes
With a cohort of employees equipped to think beyond: “How can I use AI to work less?” or “How can I rig the system so AI doesn’t take my job?”, the focus can turn to creating policies that enable a new way of work rather than policies that force a specific way of work.
Policies across recruitment and reward, IT equipment and software, digital security, intellectual property, marketing, procurement and project management all need to be reviewed to balance real-time risks and opportunities.
Even the process of creating, implementing and reviewing policies needs an overhaul. It needs to be fast and fluid with latest updates available in real-time. This speed will create an enormous problem as human behaviour in the workplace is guided by culture – the way we do things around here.
Start before anybody’s ready
Culture doesn’t shift because policies or technologies do. It takes time. Even under ideal circumstances and with the support of the most influential change champions, change in human behaviour takes time.
Perhaps that’s one of the things we fear most: being forced to change before we’re ready, risking being exposed as not being as awesome as others (or ourselves) thought we were. Perhaps “losing face” by admitting that we are part of the learning curve rather than ahead of it is going to be the biggest leadership challenge in this era.
Progress, however, does not care about egos and comfortable timelines. It happens whether we’re ready or not. The longer we wait to start experimenting with reinventing ourselves and our workforces, the fewer the options we’ll have for keeping the doors open.
