Imagine a scenario that becomes standard in global business in 2025. Inspired by the possibilities of generative AI, the CEO sets an ambitious goal to implement the technology.
Almost simultaneously, the CFO, reacting to market uncertainty, announces a recruitment freeze and cuts to development budgets. This is not fiction, but a daily reality for many IT leaders.
There is a global investment paradox. Analytics data shows that nearly 80 per cent of CEOs consider artificial intelligence to be a key competitive factor.
At the same time, in the same group, one in three managers is cutting staff and almost one in five is cutting spending on staff development. For CIOs, this means pursuing a strategic vision while cutting resources.
Successful IT leaders are already treating this not as a barrier, but as a complex strategic challenge that can be turned into an advantage.
Anatomy of a paradox: calculating at board level
Decisions to simultaneously invest in AI and cut staff costs are the result of cold business calculation. This way of thinking is primarily driven by the powerful pressure for a quick return on investment.
In a volatile environment, where long-term strategies are high risk, boards favour projects perceived as those that will bring immediate optimisation. The situation is complicated by differing perceptions of costs.
Investment in technology is often classed as a quantifiable expense that can be accurately modelled, while personnel costs are seen as fixed and less flexible, making them a prime target in savings processes.
Finally, all this leads to a natural focus on the technology itself, rather than on the whole implementation process, where user adaptation issues are seen as secondary challenges.
Risk analysis: the cost of AI implementations without a skills base
A purely technology-focused approach generates hidden debts that can significantly reduce or even nullify the return on investment. The most immediate threat is low ROI, where advanced systems are underutilised due to a lack of skills in the team, becoming digital ‘shelfware’ – expensive software lying on the shelf.
This phenomenon is often a symptom of deeper problems, such as adoption challenges. Teams that do not receive adequate preparation may resist new tools, leading to chaos and a drop in productivity during the transition period.
What’s more, a lack of knowledge about the limitations of AI increases a company’s exposure to operational errors when business decisions are made based on misinterpreted data. In the long term, such a situation leads to the loss of core competencies, as the most talented employees, looking for growth, leave for competitors that offer better prospects.
CIO playbook: tactics for implementing AI strategies under constraints
An effective CIO must act like a strategist who optimises available resources to achieve a goal. There are four proven tactics to deliver AI projects despite budget constraints.
Agile competence development (Agile Upskilling)
Instead of expensive, centralised training programmes, it is worth opting for an agile and decentralised approach. An effective method is to create internal guilds or ‘communities of practice’ that bring AI enthusiasts together and allow them to exchange knowledge. You should also make maximum use of the free, high-quality resources offered by technology providers and promote microteaching – short training sessions linked directly to tasks in ongoing projects.
Selecting tools for adoption
Not every AI initiative requires a team of experts. The key is to prioritise platforms with low-code/no-code interfaces that allow business employees to create simple solutions themselves. The easiest route to rapid adoption is to implement AI in tools that employees already know and use well on a daily basis, such as office suites, CRM systems or analytics platforms.
Using pilot projects to build a “business case”
Instead of asking for a large overall budget for competence development, it is much more effective to propose a small, closed pilot project. It is crucial to define hard, measurable indicators of success (KPIs) together with the business before the start. Positive results from such a pilot, backed up by numbers, become the strongest argument for further, larger investments – both in technology and in people.
Managing the narrative to minimise resistance
Effectively changing the narrative is a fundamental part of change management. In collaboration with HR and communications departments, AI should be consistently positioned as a tool that empowers rather than replaces employees. It is worth communicating it as a ‘co-pilot’ that automates repetitive tasks and allows people to focus on work that requires creativity. Promoting success stories internally builds trust and positive attitudes.
From paradox to competitive advantage
The role of the modern CIO is evolving into that of a business strategist who can navigate a constrained environment. The paradox of AI investment is not a problem to be solved, but a permanent part of business reality.
CIOs who effectively employ pragmatic tactics are not just delivering successful AI projects. Above all, they build resilience and agility into their organisations, turning budgetary constraints into real, hard-to-copy competitive advantages.
