Just as Irish businesses are getting used to one big change in workforce management – hybrid working – along comes another, in the form of artificial intelligence (AI).
AI agents may be filling in for some of the more mundane roles but they still need management – though, granted, not in the traditional, chat-over-coffee sense. Their arrival on the scene also has implications for the way in which humans progress in the workforce.
“Career progression is no longer linear but rather tied to skills acquisition,” says Paula McLoughlin, chief strategy officer and partner at EY Ireland. “While moving through the ranks remains the primary model of career progression, we increasingly see employers supporting their teams to avail of secondments, sideways moves and opportunities to work on programmes and innovation, building skills and capability internally for both the organisation and the individual.”
That doesn’t just put pressure on the worker to evolve, it also behoves the employer to work on ensuring their staff can trust them. Tough questions are going to be asked of employees, and they need to know their bosses have their best interests at heart.”
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People are more likely to make lateral or backward moves when they have psychological safety, a financial buffer and a clear future path, says McLoughlin.
“Enablers include protected exploration routes such as secondments, project rotations and temporary assignments, which provide ‘safe to try’ options. These mechanisms are widely used by large Irish banks, multinational tech companies, and government departments, and they have been shown to deliver strong outputs and improve wellbeing.”
McLoughlin recommends that employers take an active role in aiding their staff on the upskilling journey.
“Another key enabler is real investment in retooling and reskilling for mobility; funded learning, micro-credentials and internal academies help reduce the fear of losing expertise when switching areas,” she says.
“Social and managerial sponsorship also plays a critical role; when managers publicly validate non-linear moves as strategic, employees feel empowered to innovate and experiment.”
This attitude shift is a necessary one, says Laoise Mullane, director and AI adoption lead at PwC Ireland, as the nature of work as we know it is fundamentally changing.
“Agentic AI isn’t just a technological change; it is a reconfiguration of how work is done. The biggest value from AI does not come from iterative changes to current processes, but through reimagining operating models and redesigning processes entirely,” she says.
“Given this fundamental shift and opportunity, it is expected that the role of the manager is evolving and will continue to evolve significantly. Rather than simply overseeing tasks and processes, managers are increasingly required to orchestrate the collaboration between human team members and AI systems.”
That means that what work is must change. So too must the way those doing the work are managed. Work needs to be designed around outcomes so those in charge know what is best handled by employees and what can be delegated to AI.
“Recognising the capabilities that are uniquely human is becoming increasingly important and should be protected,” says Mullane.
“The increasing implementation and adoption of AI assistants, AI agents and automated tools arguably places a greater value on human skills such as emotional intelligence, ethical judgment, resilience, creativity and integrative thinking.”
For managers, this means they have a key role to play in supporting staff through a rapidly evolving working landscape.
While the potential benefits to the workplace are significant, it’s still going to involve a lot of work. Managers will need to blend their people skills with the ability to manage an assortment of AI tools of differing complexity and purpose. All the while they must be there to guide staff through these changes.
“Leaders must anticipate and mitigate risks such as skill erosion from overreliance, bias in decision making, accountability gaps and data privacy vulnerabilities. Bringing multiple and diverse perspectives into the discussion, before AI is deployed, is a key step for early identification of potential unintended consequences,” says Mullane.
“The responsible management of these risks requires embedding transparent and ethical AI principles and guardrails, maintaining human oversight for critical decisions and investing in continuous upskilling to build AI literacy at every level. Clear and transparent communication, robust governance frameworks and a focus on uniquely human strengths are essential to ensure AI augments rather than diminishes human potential.”
At the core of this change is recognising why all of these changes are occurring. Businesses aren’t implementing AI because it’s in vogue – or, at least, they shouldn’t be – but because they have identified areas in which it can add value.
“This is the Rubicon that needs to be crossed in terms of people’s use of AI in organisations and what it can do for that business,” says Conor McCarthy, head of people and change at KPMG.
“The AI conversation needs to move on from just trial, adoption and productivity. For example, we can measure the adoption of any tool and talk about use cases anecdotally, but can the manager or management team identify the business performance metrics that are ultimately being addressed and improved by virtue of the AI?”
Answering that question accurately and adequately involves hard thinking and also clearly defined metrics. Still, that’s the level managers need to reach in order for AI to have any kind of credible impact, which in turn can help with staff buy-in.
“People can then be directed to understand ‘the why’ of AI use in the business. Their ability to adapt and think critically is the follow-on development challenge, but these are addressable through coaching and mentoring in the traditional sense,” says McCarthy.
