Sync NI met with Christopher McCausland and Bronagh Lannigan, Principal AI Engineers at the Artificial Intelligence Collaboration Centre (AICC) to discuss how AI can be adopted in a way that is practical, responsible and genuinely valuable to small and mediumsized enterprises in Northern Ireland.
A £16.3 million initiative led by Ulster University in partnership with Queen’s University Belfast, and supported by Invest NI and the Department for the Economy, the AICC has a clear mandate: to help Northern Ireland’s SMEs move beyond curiosity into confident, responsible, realworld AI adoption. At its core, it is less about selling technology and more about building capability.
“We’re here to advance awareness and adoption of AI technologies among small and medium enterprises in Northern Ireland,” explains Christopher McCausland, Principal AI Engineer at the AICC. “we do that through handson support working directly with companies and through training that strengthens the wider AI ecosystem locally.”
That dual focus, on delivery and skills, sets the tone for everything the centre does.
What makes the AICC distinctive within Northern Ireland’s tech landscape is not simply its scale or funding, but its position as a connector. For many SMEs, engaging with university research can feel intimidating or inaccessible. The AICC acts as a bridge, translating academic advances into applied solutions that fit real business constraints.
“A lot of the companies we work with wouldn’t naturally know where to start with the universities,” Christopher says. “But there’s huge value there in research and expertise, particularly when you can connect it properly. That’s where we come in.”
Bronagh Lannigan, also a Principal AI Engineer at the centre, describes the work as inherently bespoke. Rather than pushing generic AI solutions, the team works with businesses to break down their specific problems and determine whether AI even makes sense in the first place.
“Sometimes the answer is actually ‘no, you don’t need AI for this,’” Bronagh says. “And that’s an important outcome too. When AI is appropriate, it tends to be very tailored towards niche problems in local contexts, with very practical deployments.”
Running through everything the centre does is a strong emphasis on responsible AI. Every project begins with a critical question: should this system even exist, and if so, how can it be deployed safely, ethically and transparently?
That mindset, once peripheral, is increasingly central to Northern Ireland’s AI identity.
Ask which sectors are best positioned to benefit from AI today, and the answer is less about novelty and more about data and pressure.
“The biggest opportunities tend to be in industries that are datarich or under resource pressure,” Bronagh explains. “Financial services, advanced manufacturing, retail, legal tech, industries where there are bottlenecks, repetitive processes, or compliance burdens.”
Rather than replacing expertise, AI is being used to augment it. Predictive maintenance in manufacturing, for example, can reduce downtime. Retailers are using AI to optimise supply chains and forecasting. Professional services firms are adopting AI tools to reduce manual review and improve accuracy.
Crucially, the AICC does not approach these sectors with a onesizefitsall solution.
“Our first question isn’t ‘how do we sell AI?’” Christopher says. “It’s ‘do you actually need it?’ And if the answer is yes, we focus on using AI to handle the mundane but necessary tasks, freeing people to apply their domain expertise where it really matters.”
Much of this work happens through the AICC’s Transformer Programme, which provides handson support to local SMEs across a broad range of sectors. Projects range from legal technology and renewable energy to floodrisk analysis and medical imaging. This is designed to help transition from proof of concept to realworld impact.
One of the most impactful examples currently underway involves medical imaging to support cancer triage. Working with a company that already has a strong track record in this area, the AICC is helping integrate AI to improve both speed and accuracy.
“That’s where it becomes real,” Christopher says. “When you can see tangible outcomes that benefit society such as decision support systems for faster triage, it really brings home the value.”
Elsewhere, the team has delivered fraud detection systems for financial services firms, precision tools for legal workflows, and forecasting models to help manufacturers manage global supply chains. In one recent case, a local manufacturer worked with the centre to develop an AIdriven forecasting pipeline to anticipate component demand months in advance.
“They ended up hiring someone specifically to manage that system,” Christopher notes. “That’s a concrete example of AI creating roles, not removing them.”
Success, however, looks different for every business. For some, it is time saved. For others, fewer errors, higher confidence with clients, or the ability to launch entirely new services.
“There isn’t one metric,” Bronagh says. “The point is whether it delivers meaningful value for that company.”
As AI tools become more accessible, there is a growing misconception that deep technical skills are becoming optional. Both Christopher and Bronagh push back strongly on that idea.
“You still need the fundamentals,” Bronagh says. “If you can’t code, it’s very hard to critically evaluate the output of code and you’re still accountable for it.”
Beyond programming, understanding the data has become increasingly vital. Where the data comes from, how clean it is and what biases it may carry are considerations that sit at the heart of AI workflows.
“More and more,” Bronagh adds, “there’s also a translation role. Engineers have to work closely with domain experts, becoming partners rather than just implementers.”
Christopher sees AI as a broad spectrum of tools rather than a single skillset, ranging from traditional machine learning and image analysis to prompt engineering with large language models.
“Not everyone needs to know everything,” he says. “What matters is mapping a clear business use case first, and then deciding which tools and frameworks make sense.”
Equally important is the ability to evaluate AI systems properly, not just in abstract metrics, but in the business context.
“Accuracy, sensitivity, specificity, these numbers only matter if you understand what they mean for the actual problem you’re solving,” he says. “And AI never exists in isolation. You also have to think about system cost, latency, failure modes.”
So how much AI competency is about mathematical depth versus practical application?
“It depends entirely on the role,” Christopher explains. “If you’re a full AI engineer or researcher, you should understand models from first principles. But for many users, especially senior leaders, what’s more important is understanding how AI works at a high level, its limitations, and its risks.”
That highlevel literacy, he argues, is essential for informed decisionmaking in boardrooms as much as in engineering teams.
Bronagh agrees. “Different roles wear different hats. Depth and breadth are both valuable… just in different measures.”
Concerns about AI replacing jobs are rarely far from the conversation, but the AICC’s experience on the ground paints a more nuanced picture.
“We’re seeing entirely new roles emerge,” Bronagh says, pointing in particular to responsible AI, governance and assurance positions. “Companies want to use AI ethically and safely, and that requires people who understand both the technology and its implications.”
There has also been a surge in demand for AI engineers, applied data scientists, data engineers and technical product managers. These positions are often filled by professionals transitioning from more traditional software roles.
What stands out is how often AI adoption leads to hiring, not redundancy.
“When companies see real value,” Christopher says, “they invest further. They build capability around it.”
For software engineers, the next decade is likely to feel less like replacement and more like acceleration. This will be a period of augmentation rather than simple automation.
“Developers are already using AI to handle boilerplate code, search logs, identify bugs,” Bronagh explains. “What took hours can now take minutes.”
That does not make the role less technical, but more strategic.
“You still need to understand what’s happening,” she says. “But it gives you more time to focus on design, integration and higherlevel thinking.”
Christopher describes AI fundamentally as an augmentation tool.
“It speeds things up, but responsibility still sits with the engineer,” he says. “The challenge for organisations is making sure that speed doesn’t lead to burnout and that people still have time to think creatively.”
With students and graduates understandably anxious about the future, both engineers offer reassurance, practical guidance and advice for the next generation.
“Don’t be afraid of AI,” Christopher says. “It’s a tool, and it’s here to stay. Young people are already highly techliterate, and they often see opportunities others don’t.”
He encourages students to explore entrepreneurial ideas and to become proficient with AI rather than avoiding it.
Bronagh’s advice is simpler, but no less powerful: learn how to learn.
“The tools will change,” she says. “What matters is staying curious, asking good questions, and being open to change.”
Communication skills, she adds, are increasingly critical when it comes to translating between stakeholders, technology and realworld needs.
Looking ahead, Christopher is particularly excited about more efficient AI models such as smaller, taskspecific systems optimised for energy usage.
“We have to be conscious of the environmental cost of AI,” he notes. “Using the right model for the right job matters.”
For Bronagh, the excitement lies not just in the technology, but in human imagination.
“Seeing how people want to use AI and coming up with ideas we’d never think of ourselves is really inspiring,” she says. “Turning those ideas into something real.”
If there is one thing both engineers would like to see more of, it is shared learning between organisations across Northern Ireland and beyond.
“People don’t need to share everything,” Bronagh explains, “but sharing lessons builds confidence and sparks ideas.”
Christopher, meanwhile, is extremely encouraged by how far Northern Ireland has already come.
“In just over a year, we’ve seen a real shift towards responsible AI,” he says. “It’s now part of the conversation and not just an afterthought.”
That culture around collaborative, ethical and grounded work practices may prove to be Northern Ireland’s greatest advantage as AI continues to reshape the global economy.
As Christopher puts it: “It’s not just about what we can do with AI, but actually what we should do.”
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