Artificial intelligence is increasingly determining how companies work, compete and grow. AI in companies is no longer just experiments conducted in the labs of IT departments – AI agents are becoming a permanent part of the business infrastructure. According to the latest KPMG AI Quarterly Pulse Survey, up to 82% of business leaders expect the competitive landscape of their industry to fundamentally change over the next 24 months. However, a key dilemma is emerging in the face of this transformation: are business boards ready to manage it effectively?
AI in companies – management competence vs. reality
Although artificial intelligence is becoming a major topic in boardrooms, only 8% of leaders say their organisation has real, meaningful AI knowledge among board members. Meanwhile, as many as 45% of respondents confirm that AI comes up as a topic at every board meeting.
This contrast – between declared commitment and actual competence – is a growing problem. AI is now entering areas that require a deep understanding of complex topics: data privacy, data quality, decision models, work automation or performance measurement in complex systems. Traditional management experience, based on finance, law or sales, may not be enough here.
AI is changing the rules of the game – not just technologically
Modern artificial intelligence is no longer just a tool to support selected processes. It is the architect of a new working model, operational strategy and, in the long term, a source of competitive advantage. Company leaders increasingly recognise that AI is forcing the transformation of entire business models: from the way teams operate, to decision paths, to the definition of success.
The question is no longer ‘will AI work’, but ‘how quickly can it be implemented and under what conditions’. At the same time, as many as 69% of leaders report concerns about data privacy and 56% cite data quality as a major concern. These are issues that have a direct impact on corporate reputation, regulatory risk and management accountability.
In this situation, technological competence among board members is no longer just an asset. They are becoming a necessity.
Who is implementing AI – and who is managing it?
KPMG’s research shows that 33% of organisations already have at least some type of AI agent deployed. This threefold increase in six months suggests that the technology has already passed the experimentation phase and is becoming an operational foundation. At the same time, more and more companies are planning to deploy more advanced agents, such as multi-agent systems or adaptive AI.
Meanwhile, only a handful of companies are creating management structures aligned with this change. Separate AI ethics boards, technology committees attached to the board, or the permanent presence of the Chief AI Officer at decision-making level are rare.
Most companies still treat AI as a project to be handled by the IT department or innovation team. As a result, decisions about fundamental changes in the way we work are often made without the involvement of those responsible for the strategy of the entire organisation.
A liability gap is emerging
As AI becomes a co-author of business decisions, the question arises: who is responsible for system errors? If an AI agent automatically rejects credit applications, misclassifies customers or suggests the wrong diagnosis, who should be held accountable – the programmer, the CIO or perhaps management after all?
Especially as organisations are now entering a phase of redefining the workforce. According to a KPMG survey, 87% of leaders believe AI agents will force a change in the way they measure employee performance, and 69% are implementing training strategies to improve the competence of teams to work with agents.
These are not ancillary activities – they are a paradigm shift in the management of the organisation. Its coordination cannot be ‘outsourced down’ the structures. It requires conscious leadership.
How can informed boards respond?
Some organisations are already attempting to catch up with the technological deficit. Boards are attending AI training, implementing internal AI management policies and creating reporting channels where IT leaders or Chief AI Officers have direct contact with the board.
There is also a growing phenomenon of ‘AI briefings’ – regular education and strategy sessions for board members to not only explain new technologies, but also to help assess risks and opportunities.
The next step is structural change. AI is becoming a permanent agenda item in board meetings, but only if it is combined with real impact on decision-making. Leaders who can ask the right questions – about the quality of data, the meaningfulness of ROI metrics, the ethical implications – are becoming crucial today.
Bold decisions require knowledge
Implementing AI is not just a technological issue. It is a process that changes the way a company operates from the inside out. It requires courage – to rethink the way we work – but also competence to turn that courage into effective decisions.
Too many companies delegate AI management to the operational level, assuming that it is enough to implement the system and observe the effects. Meanwhile, the organisations with the most to gain are those that treat AI as a strategic investment – and manage it as such.
This is not to say that every board member should be a machine learning engineer. But those who do not understand the basic implications of implementing AI will not be able to make sound decisions – either for today or for the future.
Artificial intelligence is changing the rules of the game faster than most management boards have managed to realise. Technological competence is becoming not only a competitive advantage, but also a prerequisite for responsible leadership. Companies that want to lead and not just keep up need to invest not only in AI, but also in themselves – as decision-making bodies.
