Business Management

Artificial intelligence and leadership: how AI is revolutionising the organisation and the role of CEOs

The adoption of AI requires senior management to rethink processes, skills and governance in order to transform technological efficiency into human and business value

by Gianni Rusconi

 (AdobeStock)

5' min read

Translated by AI
Versione italiana

5' min read

Translated by AI
Versione italiana

Many organisations are entering a new phase in their digital transformation journey: after years in which the focus was on experimenting with the most innovative technologies, artificial intelligence now represents a new, broader and more complex challenge, which features prominently on the agenda of senior management and has a direct impact on leadership and the organisation of work. The report “2026 View from the C-Suite”, based on a sample of over 2,500 companies worldwide and produced by LHH, an Adecco Group company specialising in HR consultancy services, reveals that almost one in two executives (49 per cent, to be precise) cite AI and generative tools as their top professional development priority (and the main skills gap to be addressed), and that defining responsibilities regarding artificial intelligence, effective decision-making and strategic clarity feature among managerial priorities for the coming years. The challenge for business leaders therefore lies not only in adopting new technological solutions but also (if not above all) in the ability to convert the operational efficiency generated by increased automation into added value for people and for the business.

This is by no means a foregone conclusion, even if it is a view shared by many, and Deborah Buttignol, Managing Partner at LHH Executive Search, also subscribes to this line of thinking, who argues that the real issue surrounding the pervasive use of AI is, in fact, organisational in nature and linked to companies’ ability to rethink the way they work.

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The paradox of freed-up time. The other side of automation

The impact of artificial intelligence varies significantly depending on the business function: customer service, administrative back-office functions, reporting activities, as well as software development and, more generally, repetitive processes are among the areas where automation powered by algorithms and LLM models is producing the most noticeable results. And although several international studies suggest that up to 40 per cent of tasks could be automated in the coming years, freeing up time and resources is not (often) synonymous with generating greater value or launching new initiatives on skills or talent development. ‘We have more scope for interaction with both candidates and clients, and more time is devoted to building relationships and decision-making because it is no longer necessary to manually analyse large amounts of data. The point, however – Buttignol continues – is to understand how this time is reinvested within the organisation: if processes are not redesigned, there is a risk that the workload will simply increase.”

There are less obvious effects brought about by digital transformation and by AI in particular, and one of these is a substantial increase in the volume of information that needs to be interpreted. ‘Artificial intelligence,’ the manager points out, ‘generates a huge volume of data and insights that need to be processed by people. We need to consider that not only are we doing more, thereby increasing productivity, but we are also doing more by thinking more, which places a much greater cognitive burden on us.’ There is also an often underestimated but increasingly significant psychological dimension, linked to constant access to systems capable of generating answers and to the sense of inadequacy felt by those who perceive themselves as not being up to the task of dealing with new technologies. ‘It creates – as Buttignol points out – almost a form of competition and rivalry with artificial intelligence, because there is a feeling that it knows more than we do, and this dynamic can generate frustration, pressure and a sense of inadequacy, especially among those who are more performance-oriented.’

The CEO’s changing role: from decision-maker to architect of change

Another important issue to focus on, according to the manager, is the cross-functional nature of artificial intelligence, given that we are dealing with a technology that can no longer be regarded as a matter confined solely to IT departments. Responsibility for this transformation is, in fact, inevitably extending to senior management, and this trend is also reflected in the evolution of organisational structures, with the Chief Information Officer now a permanent fixture in the C-suite and in the strategic decision-making processes of many companies, reporting directly to the Chief Executive Officer. In turn, the role of the organisation’s top executive is undergoing a major transformation. “The CEO,” Buttignol emphasises, “is called upon daily to make decisions concerning the reorganisation of the company and must understand which tools to use and how to integrate them. Today, there is increasing talk of leaders as system architects – figures tasked with designing hybrid architectures and steering the transformation in a balanced way.” The challenge, in other words, is to prevent innovation from creating new inefficiencies: if the acceleration of one business function leaves the rest of the organisation stagnant, there is a risk of simply shifting the bottleneck elsewhere.

The other trend set to have a profound impact on businesses and management concerns the gradual simplification of hierarchical structures. The availability of advanced analytical and decision-support tools also enables middle management and younger staff to take on responsibilities that previously required greater experience, and whilst this dynamic can certainly become a competitive advantage, it simultaneously demands new leadership skills. ‘We talk about “flattening” – explains the Managing Partner of LHH – because decision-making processes are faster and organisations are becoming flatter and leaner. There is a major issue of middle management being squeezed out, and those who know how to use the new tools will go much further, whilst those who resist change risk being left behind. And this applies at all levels, not just to young managers: even CEOs must evolve, precisely because the redesign of work within a company must start at the top.”

It’s not a question of size, but of managerial maturity

One of the most widespread beliefs is that the AI-driven transformation process mainly concerns large multinational companies with substantial financial resources, whilst the reality is far more complex. “I wouldn’t frame this in terms of company size; I’d frame it in terms of managerial maturity. Organisations,” continues Buttignol, “that possess critical thinking, decision-making capabilities, good governance and widespread leadership can navigate this journey regardless of their size.” This refers (in)directly to medium-sized Italian companies, which can benefit from greater organisational agility to make the process of change even faster. The reality, however, remains very uneven – “very patchy”, to use the words of the LHH manager – and whilst there are companies, even small ones, that have already made giant strides, others have not even got started yet. What is certain, Buttignol adds, “is that we are facing a transformation that will have profound and progressive impacts, one that requires the courage to tackle it, because there is no going back.”

Where should we begin this major endeavour to rethink models and processes? LHH’s approach in this regard is clear: to establish system governance, understanding what to integrate and where to invest, whilst avoiding the waste of resources on technologies that do not generate value. It is no coincidence that the concept of ‘augmented performance’ is based on the integration of human capabilities, data and automation; often, this does not involve large-scale transformational projects but rather targeted and incremental interventions, in which AI can become a tool for increasing so-called ‘value density’, that is, the ability to concentrate and make the most of available data to improve decision-making. ‘Very often,’ concluded Buttignol on this point, ‘companies already possess a vast amount of information on customers and markets but are unable to make the most of it. The aim is not to do more, but to extract more value from the information they already have.’

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