“We are all the two-faced gods of our businesses,” said Gaetano Mazzuca.
“Because as CIOs… one is to secure, keep, archive, stable, control… but on the other side, we’re transforming. We’re deviating. We’re changing. We’re asked to mature,” .
Mazzuca, CIO at the City of Red Deer, shared this with the crowd at the CIO Association of Canada’s Peer Forum. Drawn from Roman mythology, the metaphor framed the day’s central contradiction: CIOs are charged with managing risk and reliability while simultaneously driving disruptive transformation.
That tension shaped day two of the event, where sessions focused not on whether AI is coming, but how to lead through it. From governance to trust, data to culture, Canadian IT leaders outlined what it means to guide organizations in a moment of accelerating complexity.
As the national media partner for CIOCAN, Digital Journal followed the conversations to understand what Canada’s IT leaders are learning and what they’re being asked to become.
Across sectors, it was clear that the role of the CIO is evolving again. And this shift will be shaped not by what tools they choose, but by how well they help others make sense of what’s happening.
Governance is being redefined, not relaxed
CIOs face a core challenge: scaling AI adoption across the enterprise without compromising trust, privacy, or accountability.
At Housing Infrastructure and Communities Canada, that starts with structure.
“We have an AI framework that really lays out what is it that we’re trying to tackle”, said Kate Burnett-Isaacs, acting chief data officer, Housing, Infrastructure and Communities Canada (HICC). “What are the privacy considerations, the ethical considerations?”
Her team’s approach grounds AI work in clearly defined business needs, ensuring that governance is embedded from the start.
“We’ve also laid out a road map,” she said. “A project life cycle that says, ‘Okay, let’s tackle this problem with the data at our disposal, our technology at our disposal, and the people at our disposal.’”
Others echoed the importance of treating governance as a living framework — one that reflects how teams actually work, not just how policies are written.
“We predicate everything on security,” said Ian Calder, senior manager, information systems and technology at EfficiencyOne. “AI is a business enabler. It’s less about IT.”
Calder described how his organization initially blocked ChatGPT, but later realized the need to explore tools in a structured, responsive way.
“You need to explore. You need to learn and understand your users’ needs,” he said. “They won’t know until they start benefiting, but have some reins and controls and standards for your organization.”
From the legal side, Duncan Fraser, partner at Noticia LLP and a leading expert in e-discovery, added another layer to the discussion.
“We don’t organize information for legal events. We organize our information to serve our business,” said Fraser.
He cautioned against designing systems primarily around litigation or regulatory readiness. Instead, he argued for a pragmatic focus of supporting core operations first, while ensuring that legal and compliance needs can be met when they arise. Governance is often looked at as a restriction, but his perspective reframes it as a natural outcome of aligning systems with the business itself.
Getting the data house in order is leadership work
Across sessions, it was consistently noted that nothing about AI works without data. But the problem with “data” isn’t only about the technology, it’s a leadership problem, too.
“We’re data rich,” said Ian Calder. “But we’re focused on affordability and delivering value. That’s our primary mandate, and we do it through many different needs, predicated on data.”
His team is using AI to enhance contact centre performance, enabling remote assessments using smart meter data.
Surani Adamesco, SVP of IT at SiriusXM, emphasized that her team’s AI priorities are grounded in customer experience. They use AI to detect real-time sentiment shifts during calls and bring in supervisors when needed.
“Long term, there’s a lot more to be gained from it,” she said, but efficiency is a meaningful start.
Others emphasized the importance of linking data work to practical, operational gains. “We completely transformed our operations report,” said Calder. “It used to take hours of time across cross-functional teams. Now it’s all structured and automatically generated.”
The human work is the hard work
Several sessions emphasized that building confidence in AI starts with how leaders frame the change. Change, after all, is no longer something that can be neatly managed.
If AI requires clean data, it also requires trust, and trust isn’t built by policy alone. It’s shaped by how leaders frame change, and how teams are invited to participate in it.
“You can’t manage what you can’t predict,” said Jay Kiew, CEO of Citizencentric. “Change shouldn’t be managed. It’s something we need to become fluent in.”
That fluency includes how we talk about AI inside organizations.
Michael Langton, vice president of sales, data and AI at Converge Technology Solutions, uses an analogy to position AI as an opportunity rather than threat.
“The way I would describe AI to senior leadership would be, just think of it as bionic arms and legs for productivity you can do,” he said.
“It’s not about replacing jobs and fear factor. It’s about imagining that I could run faster, do more.”
When leaders approach AI as a tool to augment rather than displace, it creates space for momentum.
For Joseph Geraci, founder of NetraMark, the real transformation lies in how people interact with AI systems. As human roles shift from execution to orchestration, organizations will need to cultivate a culture of experimentation.
“Establish an experimental way of thinking in the company,” he urged. That includes learning how to work with intelligent systems, not just implementing them.
Fluency in AI, in other words, will come from practice, through doing, testing, and learning in real time.
Not every organization is ready for that shift. But the ones that are willing to embrace uncertainty, invest in trust, and empower their people to adapt are already laying the groundwork for what comes next.
A new posture for the CIO
The fact that CIOs are no longer simply tasked with delivering infrastructure or overseeing procurement was repeated throughout the day.
The role is shifting toward meaning-making. They’re helping boards, peers, and staff not just understand what AI does, but grapple with what it demands.
“We don’t move at the speed of technology,” said Jay Kiew. “We move at the speed of the enterprise.”
Kiew’s framing emphasized that transformation is less about integration than adaptation. For CIOs, that means listening deeply, setting pace with intention, and knowing when not to automate.
Others emphasized that navigating this moment will require more than implementation. It will demand new instincts.
“The human role is evolving,” said Joseph Geraci. “Employees aren’t just executing tasks, they’re overseeing outcomes.”
The challenges may differ across sectors, but the mindset is converging. These leaders are developing new muscles for strategic patience, for cross-functional learning, and for resilience in ambiguity.
That, perhaps, was the real message from Ottawa: AI is accelerating, yes. But CIOs are stepping into it with intention. Asking hard questions, pacing for the long term, and leading their organizations through complexity, not around it.
Digital Journal is the national media partner for the CIO Association of Canada.
This article was created with the assistance of AI. Learn more about our AI ethics policy here.
