AI is like many technologies that once had the potential to radically transform the way businesses operate: too much emphasis on technology can lead to too little attention being paid to the cultural and leadership issues that are a prerequisite for organizational change. It’s an old adage that’s still relevant today: “We should not expect an application to work in environments for which its assumptions are not valid“.
The result: projects that are disconnected from the field, users who resist and, in the end, less added value than expected ([FR] How to make your investments in AI projects profitable and Generative AI in the workplace: revolution or illusion?).
AI beyond the hype
When it comes to AI, blissful optimists are no more right than stubborn pessimists: AI is neither a miracle solution nor a threat. Everything depends on how we decide to design and use it (Is technology really evil?).
It redistributes roles, automates tasks and creates new opportunities for those who know how to seize them. The challenge for managers is therefore not to blindly adopt AI without any guidelines, but to understand how it can be a lever for increasing human capabilities.
The main key challenge therefore lies in raising the skills and maturity of teams. Too often, AI is a subject reserved for technical experts, whereasit needs to be understood and mastered by everyone if it is really to bear fruit. This requires concrete learning in the context of day-to-day work, field experimentation and feedback ([FR] We don’t need better AI, but a better understanding of AI).
More innovation, less control
Historically, change management has been dictated by control and risk management, which is a brake on innovation in general and disruptive innovation such as AI in particular. It calls for more agile leadership that can experiment and adapt quickly.
Instead of measuring performance by the usual indicators such as cost and headcount reductions, we need to assess the capacity for innovation, the business impact of initiatives and the quality of the employee experience (How to reinvent work and professions in the age of AI) and Productivity: what if quality was the new quantity?).
Businesses will have to move away from an obsession with reporting, and adopt ways of operating in which AI becomes a creative lever rather than a mere optimization tool (AI in the workplace: going beyond augmentation to actually transform).
This may involve automating administrative tasks to free up time for more strategic thinking, creating experimentation areas for risk-free testing of tools and practices, and developing a culture of continuous feedback to quickly adjust practices.
Taking employees into account from the outset
Taking employees into account from the outset
AI, like any other technology, will not be adopted if it is imposed vertically in a directive manner. If employees are not involved in its deployment, it will be perceived as a constraint rather than an opportunity (Change and transformation need a new approach)
But we still see too many AI projects led by CIOs from an essentially technical angle, without any dialogue with the business, which is not very effective, generates frustration and even leads to “shadow AI”, with all the risks that this entails (Half of workers use unauthorized AI at work and don’t want to quit).
An approach based on co-construction will therefore help to identify relevant uses and minimize resistance to change.
Towards a culture of trust and autonomy
With AI, systematic control is becoming, if not obsolete, at least complicated and counterproductive. Successful businesses will increasingly be those that empower their teams and practice trust-based management. Managers benefit from taking on the role of facilitator, supporting experimentation and skills development, rather than micro-manager.
Whatever the case, in a world where AI will automate many tasks and boost the individual capabilities of employees, the role of the manager will tend to become more and more human-centered and less and less technical.
AI as a tool for professional fulfillment
Many businesses see technology simply as a tool for optimizing costs and reducing headcount, which, as we’ve seen, limits its potential and generates frustration and even fear. On the contrary, AI must be seen as a factor in the evolution of skills and a means of freeing up time for higher value-added tasks.
AI ethics will be a key issue. We need to ensure that it doesn’t create new forms of inequality, doesn’t automate existing biases, and communicates widely, transparently and reassuringly on the subject.
These are issues that need to be addressed right from the project design phase.
Bottom line
The transformation of organizations cannot be driven by technology alone. AI is a gas pedal of change, but it will never replace strong human leadership, or even accommodate inadequate governance. For AI to really serve to create value, it is essential to trust users and involve them in the project at a very early stage. Users must see AI as a partner, not as a factor eroding their skills and employability, or even replacing them.
Image: AI adoption by wenich_mit via Shutterstock
