The training wheels are coming off artificial intelligence (AI) in the workplace and with that comes its own set of opportunities and challenges.
With businesses and organisations moving from pilots to full deployment, the focus now is on how to integrate it responsibly and in a way that benefits workers.
“We are clearly seeing organisations move beyond pilots and proof of concept into real, defined production use cases,” says Neil Bowden, director of data analytics and AI at Dell Technologies Ireland. “AI is now embedded in day-to-day cybersecurity operations, helping detect threats in real time, in IT environments where it predicts system failures before they happen, and in customer service where it can summarise interactions and reduce administrative burden.”
While adoption is becoming commonplace, there are divides in the level of usage between large enterprises and SMEs.
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“The most popular uses of AI are for business administrative processes, followed by marketing and sales, ICT services and innovation activity,” says Erik O’Donovan, head of digital economy policy at Ibec.
“Last year, more than 20 per cent of enterprises overall indicated that they used AI in some capacity. There are, however, AI divides by firm size. Nearly 58 per cent of large firms use AI, versus nearly 29 per cent of medium and 17 per cent of small firms.”
Resourcing is understandably at play here as smaller companies simply aren’t as up to speed as larger enterprises with AI.
“Recent Ibec research highlights an AI preparedness gap between large and SME firms and a need to direct some National Training Fund towards AI skills and preparedness for business.”
That need to focus on helping smaller companies get up to speed only becomes more apparent with the technology becoming integrated into workflows throughout industry.
“Advanced AI – generative, agentic, physical – is being embedded across almost every sector, if you look at the organisations that are genuinely pulling ahead,” says Liam Connolly, AI and data lead at Accenture in Ireland.
“What Accenture’s research shows is that the companies who’ve moved beyond pilots to rewire how their business actually operates are already seeing measurable financial separation from their peers.”
Connolly says the financial sector has been among the most active in embracing AI to improve efficiency.
“In financial services, AI is streamlining KYC [know your customer] onboarding, compressing what was once a weeks-long process of document verification, risk scoring and compliance checks into hours.”
This strive for efficiency brings with it concerns about the impact on workers but, if used wisely, AI should be a tool to assist staff rather than replace them.
“As AI adoption increases, the value of the innately human skill set has skyrocketed. From our conversations with members, we are hearing that high performance is also about advancing skills. AI literacy will move from a professional ‘nice-to-have’ to a non-negotiable baseline,” says Síofra MacDonald, HR strategy executive at Ibec. “Today, AI is stripping away the administrative burden of that work, with the potential to give leaders some much-needed capacity.”
Connolly holds a similar view and believes that AI should prove to only enhance the importance of human workers.
“As AI scales, distinctly human capabilities become more valuable, not less. The skills we’re seeing grow in importance are ones rooted in what humans uniquely bring: empathy, critical thinking and storytelling.”
Of course, the roll-out goes beyond the importance of AI’s impact on workers but on all stakeholders.
“Responsible AI simply means it is produced and used in structured ways that safeguard health, safety and fundamental rights. This builds trust in AI, mitigates risks and supports compliance,” says O’Donovan.
Bowden says responsible AI fundamentally comes down to control, transparency and proportionality. This, according to Connolly, means that a responsible approach to AI should be the norm.
“Responsible AI by design is the answer. It means governance isn’t a layer you add at the end of a project – it’s built into how AI is conceived, designed and deployed from day one.”
Even the most ethically planned and executed AI strategy is going to cause some concern with workers. Change is scary by its very nature, so addressing workforce anxiety is critical during deployment.
“The bedrock of employee reassurance during an AI transition is clarity. When navigating organisational change, many leaders communicate that they are adopting AI without fully understanding, or explaining, how it will fundamentally alter the workflow and workforce,” says MacDonald.
Bowden says one of the best ways to gain buy-in is to give staff more reason to feel valued during deployment.
“The most effective step is visible investment in people alongside technology. When employees are given practical, hands-on experience with AI tools in their own roles and provided with the skills to use it effectively, uncertainty reduces.”
With this approach, the practical benefits of AI in the workplace will only increase. A workforce that recognises the benefits will be more likely to engage with new practices enthusiastically.
“AI is already part of everyday work in areas where scale and speed matter. In Ireland, organisations like An Post are using AI to help manage large volumes of customer queries, so frontline staff can focus on more complex cases rather than routine requests,” says Kieran McCorry, national technology officer for Microsoft in Ireland.
That type of impact demonstrates how businesses need to view AI deployments. This is not simply a matter of automation but a redesign of work itself, with AI being used as an assistant to workers.
Combining strong governance with real communication with employees can substantially increase the likelihood of a deployment succeeding.
“Clarity and investment in skills make the biggest difference. Employees are more confident when organisations explain how AI will affect their roles and back that up with practical training,” says McCorry.
