The barriers holding organizations back from AI transformation

As we continue to follow the developments in artificial intelligence (AI), it can feel like the future is arriving all at once.

New tools appear almost weekly. AI agents are starting to automate entire workflows. Entire categories of work are beginning to change shape and require new skills.

For many organizations across Canada’s mid-market, the pace of change is becoming harder to ignore.

In fact, the speed is unlike anything organizations have experienced before, compressing innovation cycles and shortening the time it takes for new capabilities to move into market. Inside organizations, adoption is unfolding in different ways. In some areas, teams are experimenting and moving quickly. In others, progress is more measured as leaders work through how AI fits into their operations, systems, and decision-making.

And, as innovation continues to accelerate, AI adoption is becoming uneven.

The MNP Digital Report: The Business of AI 2026 depicts a landscape where progress is not consistent across organizations. Instead, adoption is developing in pockets, often slowed by barriers related to skills, system readiness, investment priorities, and organizational confidence.

One of the most significant barriers we’re seeing in The Business of AI 2026 is what can best be described as an understanding gap. While it isn’t identified as a standalone finding in the data, it is a consistent thread running through the report. Organizations recognize the potential of AI, but many are still working through what it means in practice and how to apply it within their day-to-day operations.

This is also supported by findings from the report, including that 40 percent of leaders report a lack of clarity around their AI strategy, highlighting that the issue extends beyond technical capability. It points to a deeper uncertainty around how AI connects within the business and where it can create meaningful value.

We see this play out consistently. Many organizations are stuck in an experimentation phase and are struggling to move into a true transformational phase. While interest is high and isolated use cases are appearing, leaders often struggle to move beyond pilots into more integrated applications that deliver measurable value, competitive advantage, or growth.

This shift often begins with reframing the question, not how do we use AI?, but what can AI do for the business? That change in perspective creates clearer objectives and opens the door to more practical, outcome-driven applications.

Organizations know AI requires investment, and many are already making room for it in their budgets, as findings from The Business of AI 2026 show: 

• 47 percent plan to fund AI by reprioritizing existing IT budgets
• 27 percent expect net new investment in AI

However, with the intense pace at which new tools, platforms, and capabilities are developing, many leaders are finding it difficult to determine where AI can create the greatest benefit and which solutions are worth pursuing.

The challenge becomes more visible in the findings:   

• 39 percent are uncertain which AI solutions are most effective
• 41 percent say the rapidly changing AI landscape makes it difficult to choose solutions

Organizations are willing to invest in AI. The barrier isn’t commitment, but deciding where that investment should go to generate meaningful business outcomes.

For now, many organizations continue to focus on efficiency, using AI to automate tasks, reduce manual effort, and improve productivity. It’s an effective starting point and, in several cases, where early returns are first seen. However, organizations that are pulling ahead are beginning to look beyond efficiency alone, focusing instead on how AI can drive business advantage across growth, productivity, risk, and insights.

Amid the acceleration of AI adoption, another major issue many organizations face is whether their teams are prepared to adopt AI with confidence and at scale.

The data illustrates a workforce that’s interested but not fully ready:

• 42 percent say employees lack understanding of AI capabilities and applications
• 36 percent point to insufficient training programs for staff to use AI tools effectively
• 34 percent report difficulty recruiting AI talent or specialists

Cultural and operational complexities compound the challenge:

• 32 percent identify employee resistance or fear of job loss as a barrier
• 27 percent say IT lacks capability or is creating barriers to adoption
• 23 percent cite a lack of implementation and training support

The result is inconsistent progress. Interest is high, but many organizations remain in pockets of experimentation without the shared skills, trust, and role alignment needed to move into significant transformation.

For Canadian mid-market businesses, AI’s impact on talent is twofold. Work is changing faster, and organizations need to build the literacy, practical enablement, and role alignment required to keep pace.

The path forward is not simply about adding more AI. It’s about helping people understand where it creates valuable impact, build trust in how it’s being used, and give teams the confidence to apply it effectively in their roles.

The Business of AI 2026 report makes clear that organizations are working through questions around skills, systems, integration, and risk, yet throughout these challenges, progress consistently starts with people.

AI will continue to evolve, but it does not replace human curiosity, judgment, or decision-making. What it changes is how those capabilities are applied — taking a more practical approach, building understanding, testing where value can be created, and giving teams space to learn and adapt along the way.

In many ways, AI transformation isn’t a business shift, but a personal one. It starts with how individuals choose to engage with these tools, how leaders create direction, and how teams build confidence in using them to solve real problems.

Progress toward the AI frontier doesn’t require removing every barrier upfront. It starts with taking the next step with intention, connecting AI to real outcomes, and building from there.

To explore the full findings and see how Canadian organizations are approaching AI adoption, download the MNP Digital Report: The Business of AI 2026.

Jon is a Partner with MNP’s Digital Services team. Jon leads the Client Services teams in MNP’s Digital practice, helping clients drive value and transformation from their digital investments. Collectively, the firm’s Client Services teams support all aspects of business development for MNP’s Digital practice, including marketing, sales enablement, revenue operations, client service sales, strategic partnerships and proposal management.

Lisa is a Partner with MNP Digital Services team in Ottawa, where she leads the firm’s Digital Experience Solutions group. With more than two decades of experience in client experience and digital technologies, she guides organizations through transformative digital initiatives. Lisa helps clients uncover operational efficiencies, design new digital experiences, and develop innovative services and products.