Slow down to speed up: Why steadfast IT leadership is critical in the age of AI

As originally published in CIO.com by Glen Brookman

AI is not a shortcut to transformation, and its success depends on the fundamentals leaders put in place long before adoption.

Not long ago, I found myself in a conversation about AI with a mix of business leaders and fellow technology executives. It was the kind of meeting I’ve been part of countless times throughout my career, but I noticed something different in the room. The energy felt sharper and more urgent than it had even a year ago. What struck me was the intensifying expectation that AI should be fast, simple, and almost magically transformative.

The questions reflected this new tone. How soon can we automate this process? How quickly can we add these capabilities? Why can’t we accelerate this transformation? The curiosity that once defined conversations about AI has shifted into a sense of competitive pressure. The expectation is that because AI has advanced so rapidly, organizations should be able to advance just as quickly.

As I listened, I understood something important. The gap between what many believe AI can deliver instantly and what is required to adopt it responsibly is widening. The faster technology evolves, the more essential it becomes to ground our decisions in reality. I have learned over the years that technology never overrides the fundamentals, such as governance, quality assurance, security and operational readiness. It only amplifies them. If an organization has a strong foundation, AI strengthens it. If the foundation is weak, AI exposes it.

This is why the idea of slowing down to speed up has become so crucial. It’s not about resisting innovation, but about preparing the ground so innovation can take root. We need to acknowledge that desires to move quickly must be matched with the discipline needed to move correctly. Organizations that understand this balance will gain a competitive advantage. Those who don’t understand it risk reputational damage, financial losses and diminishing trust with clients.

The pressure to accelerate AI adoption is being felt by CIOs everywhere. Conversations that once centered on exploration now come with an edge of impatience. Business leaders want to seize opportunities. Boards want visible transformation. Customers expect smarter and more responsive services. Vendors promise rapid outcomes. It is no surprise that many organizations feel they must move immediately. According to KPMG’s latest Global Tech Report, 87 per cent of Canadian technology leaders say their role has evolved significantly over the past two years and that they expect the pace of change to continue accelerating. 

But speed without readiness creates risk. In my own experience and in conversations with other CIOs, I hear the same story told in different ways. Legacy systems that were never designed for modern workloads must suddenly support AI models that demand more from infrastructure. Data sets that have not been cleaned or governed properly are fed into tools that assume accuracy and consistency. Operating models that were built around slow and linear development must suddenly support rapid experimentation. These are real challenges that arise long before the first AI use case is deployed.

I often tell my teams that delivering new technology without rethinking the way we deliver it is a risky proposition. It is impossible to reengineer decades of processes overnight, especially when it comes to AI. The underlying systems, data and governance are essential and don’t make an organization slower but resilient. They also determine whether an AI initiative becomes a sustainable capability or a short burst of activity that never scales.

Hype can never replace the hard work of preparation. One of the most concerning patterns I see today is the belief that the fundamentals can be addressed later. The assumption is that because AI is powerful, it can paper over gaps in process, planning or governance. I’ve come to call this the gravity doesn’t exist anymore mindset, and I’ve watched it emerge in organizations under pressure to be first rather than ready. Establishing the groundwork steps may feel slow, but skipping them creates fragility. A system that is not designed for speed will not become faster simply because AI is added to it. It will become more vulnerable. 

This is why 75 per cent of Canadian organizations continue to rely on structured pilots to provide a disciplined way to learn, adapt and scale. They remain so critical because they reflect an understanding that progress requires rigor. This way, organizations are also better equipped to avoid scattered experimentation that often creates confusion, inconsistent results and missed opportunities.

Governance plays an essential role as well. Without it, organizations might rush ahead with new tools before the right checks are in place. They might launch capabilities without clear oversight or expose sensitive data without realizing it. When foundational steps such as validation, testing and security are overlooked, vulnerabilities appear later in the form of system failures, incorrect outputs or reputational harm. These are not just technical problems. They affect trust, and trust is the currency of modern leadership.

The risk of moving too quickly has grown in recent years. Nearly half (49 per cent) of CIOs and CTOs surveyed say technology is now a greater source of risk than resilience for their organization. It is a reminder that AI is not a plug-and-play program. It requires thoughtful integration, the ability to recognize dependencies and to respect the complexity of the environment it enters.

All of this places CIOs at a pivotal moment. We are being asked to guide organizations through one of the fastest technology cycles in history. Expectations are climbing. Scrutiny is intensifying. The decisions we make carry greater weight, and the consequences of getting them wrong are more visible than ever.

Yet this moment also presents an opportunity. In Canada, 7 in 10 organizations say that IT is leading their AI implementation, and more than half see IT as a strategic differentiator in their efforts to become early adopters. That trust is not automatic. It comes from delivering stability, clarity and successful outcomes. We build it by demonstrating how responsible leadership helps organizations move faster in the long run and helping colleagues understand what it takes to adopt technology responsibly. The recent deployment of our agentic AI assistant, Omni, at KPMG Canada reflects this principle in action. Our ability to introduce it quickly and responsibly stemmed from the steady credibility our IT teams had built over time. It’s a great example of how a disciplined, readiness‑first approach allows organizations to accelerate when opportunities truly arrive.

Credibility is what allows a CIO to speak honestly when timelines are unrealistic or when foundational work has been overlooked. It makes it possible to guide a conversation away from urgency and toward readiness without being seen as resistant to innovation. When leaders across the organization understand that responsible adoption is not a barrier to progress, but the path to it, they are far more likely to listen.

CIO credibility also shapes how technology investments are prioritized and sequenced. When IT is seen as a partner rather than a cost center, organizations unlock faster innovation, better risk management and measurable value creation, and it enables CIOs to build momentum that lasts beyond the first deployment. 

The role of the CIO is not to hit the brakes. It is to ensure the organization has a stable engine, reliable steering and a clear runway before it accelerates. The pressure to move fast will continue to grow, but gravity still exists. Foundations still matter. It is our responsibility to remind our organizations of this reality. When we are responsible for shaping change rather than being swept up in it, the decisions we make may outlast the technology itself.

Slowing down to speed up is not a contradiction. It is a strategy rooted in experience and in the understanding that sustainable transformation is built, not rushed. AI will continue to evolve, and the hype will continue to grow. But responsible innovation is not about being first – it’s about being ready. If we anchor our decisions in the fundamentals and lead with clarity, rigor and balance, we will not fall behind in the race for AI. We will be prepared to win it.