At a glance
- Only 18% of Canadian organizations have embedded AI into workflows and operations, while 46% are still experimenting and have not yet achieved meaningful ROI.
- 29% of organizations have delayed major investments because of economic uncertainty, reinforcing a more cautious approach to transformation.
- The biggest barriers to productivity are organizational rather than technological, including legacy operating models, fragmented decision-making, and resistance to change.
- Organizations achieving the strongest productivity gains are redesigning workflows, governance, and decision-making processes rather than simply deploying additional technology.
- The next era of productivity will depend on leadership’s ability to redesign how work gets done.
Last year, we published Canada’s Productivity Paradox report focused on understanding the factors contributing to Canada’s long-standing productivity challenge. Despite its many advantages, Canada lags its peers in productivity growth and innovation-based economic performance—impacting our long-term competitiveness.
Since then, productivity has moved further into the foreground for Canadian business leaders, policymakers, and investors alike. Economic uncertainty, rising operating costs, workforce pressures, regulatory complexity, and accelerating Artificial Intelligence (AI) adoption have increased the urgency around productivity and competitiveness across sectors. We’ve also seen a growing alignment between public policy priorities and private-sector concerns around the need to strengthen Canada’s productivity performance.
While awareness and urgency have increased, progress remains uneven. Organizations across industries are investing in technology, data, and AI, but many continue to struggle to translate those investments into measurable operational gains. The challenge isn’t a lack of understanding what leadersabout the importance of digital transformation. Most organizations recognize the opportunity—and the risk of standing still.
The greater challenge is execution. Capturing productivity gains requires more than adopting new technologies; it demands fundamental changes to how decisions are made, how work gets done, how resources are allocated, and how organizations are governed. The organizations that move the needle on productivity over the next decade will not necessarily be those investing the most in technology. They will be the ones empowering their people and redesigning workflows.
This report draws on insights from a BDO Canada survey conducted by Angus Reid of 520 Canadian business leaders, as well as perspectives from professionals across BDO. We explore why productivity gains remain elusive, what leading organizations are doing differently, and where leaders should focus their efforts next.
What will determine Canada's next productivity gains?
The next era of productivity will be shaped by how effectively leaders redesign workflows, empower their people, and translate AI investments into organizational change.
Why productivity gains remain elusive
Technology investment has accelerated across Canadian organizations over the past several years, particularly around AI, automation, and data infrastructure. Yet many organizations continue to struggle to achieve measurable improvements in productivity, operational efficiency, or decision-making speed.
AI adoption is accelerating, but operational transformation is lagging
This graph represents organizations and their stage of AI maturity
The data reveals a widening gap. Nearly half of organizations are testing AI capabilities, yet relatively few have embedded those capabilities into day-to-day operations or broader workflow redesign.
At the same time, organizations are navigating a highly uncertain business environment. They are balancing a combination of rising costs, revenue volatility, workforce pressures, regulatory complexity, and capital constraints—all while evaluating where and how aggressively to invest in transformation.
Top business risks that economic uncertainty is posing to organizations within the next year
These pressures are creating a more defensive posture inside many organizations and influencing strategic decision-making. Leaders are behaving cautiously rather than strategically. They are increasingly seeking certainty around AI returns before committing to large-scale transformation investments.
0%
of organizations report delaying major investments because of economic uncertainty.
How economic uncertainty is impacting productivity across sectors
While all organizations are facing pressure to improve productivity and manage costs, the risks driving strategic decisions vary considerably by industry.
Top risks by sector
While the sources of pressure differ across industries, the outcome is often the same. Leaders become more cautious about where and how they invest. That caution is understandable. However, the organizations generating the strongest productivity gains are often taking a different approach. Rather than treating disruption as a reason to postpone change, they are using it as an opportunity to simplify processes, modernize decision-making, and build more adaptable operating models.
Why operating models are limiting productivity gains
The biggest barrier to improving productivity is not technology maturity. It’s organizational inertia.
Many organizations are still approaching AI as a technology initiative rather than a broader business operating model shift. They are experimenting with tools, pilots, and proof-of-concept initiatives, but they have not fundamentally changed how decisions are made, how workflows operate, or how resources are allocated. That disconnect is becoming one of the defining productivity challenges facing Canadian businesses today.
To date, much of the focus has been on improving individual productivity. Employees can summarize documents faster, automate routine tasks, generate content more quickly, and reduce administrative work. Those gains matter, but individual efficiency does not automatically translate into organizational productivity.
Additionally, organizations are layering AI onto operating models that were designed decades before the current pace of technological change. Layered approvals, fragmented ownership structures, siloed functions, duplicated governance processes, and slow decision cycles continue to create operational friction that limits productivity gains.
As a result, AI can expose weaknesses already existing inside organizations, rather than solving them.
Measuring activity versus productivity
One of the clearest indicators of this disconnect is how organizations measure success. Many continue to measure technology activity rather than operational outcomes.
Activity is not productivity
Deploying more tools does not automatically create value. Faster decisions, fewer handoffs, reduced friction, and greater organizational capacity do.
Productivity is increasingly defined by improving decision quality, accelerating execution, reducing organizational friction, and increasing adaptability—rather than just reducing labour inputs or cutting costs.
Many organizations want faster execution and better outcomes while continuing to protect the same legacy structures that slow them down. Productivity gains become difficult to achieve when leaders protect every legacy process, approval layer, and reporting structure along the way.
Rather than asking how AI can improve existing processes, leaders should be asking whether those processes should exist in their current form at all. This involves challenging the assumptions behind existing processes before redesigning them. That starts with asking a series of fundamental questions:
- Why does this process exist?
- What decisions require human judgment?
- Which workflows create the most friction?
- What information drives better decisions?
- What would this process look like if it were designed today?
This approach shifts the conversation away from technology deployment and toward operational redesign. In practice, that often means flattening management structures, reducing coordination overhead, improving data accessibility, automating routine decision support, and increasing management leverage. It can also involve accelerating reporting and forecasting processes and embedding operational intelligence directly into day-to-day workflows.
Organizations making these changes are creating advantages that compound over time through faster execution, stronger forecasting, improved responsiveness, and greater workforce leverage. The goal is to focus on higher-value judgement, problem-solving, relationship-building, and decision-making.
Meanwhile, those that delay transformation risk becoming increasingly constrained by slower decision cycles, increasing complexity, and rising operating costs—ultimately falling behind competitors.
Why leadership determines productivity success
If productivity challenges are rooted in operating models, leadership teams ultimately determine whether those operating models change.
One of the biggest organizational bottlenecks to productivity is the tension between executive urgency and organizational resistance to change. Senior leadership understands the strategic urgency around AI and modernization. Employees are experimenting with new tools and ways to be more efficient. Yet full scale organizational change is stalled along the way.
As organizations modernize, leadership teams are being forced to confront difficult questions around governance, accountability, workforce design, and organizational adaptability. Functions that once required significant manual effort may become increasingly automated, while new responsibilities emerge around problem solving, data stewardship, and AI-enabled decision support.
These decisions cannot be delegated to technology teams alone. They require leadership teams to make deliberate choices about how work should change. Many leaders underestimate the degree of alignment required to navigate this change, and the scale of operational and cultural adaptation required to generate meaningful productivity gains.
Leaders need to rethink how they are incentivising these changes.
Leadership plays a critical role in executing change management with a clear vision for the future of work and ensuring that efforts remain connected to business priorities rather than isolated technology initiatives.
Organizations that focus only on technology adoption may achieve incremental gains. Those that focus on enabling their people, building adaptability, and creating accountability for outcomes are more likely to achieve meaningful productivity improvements.
To learn how BDO Canada’s leadership team approached its own AI transformation journey, see 5 lessons from our AI journey as client zero.
How leading organizations across industries are improving productivity
While productivity challenges vary across industries, the organizations making the most progress are moving beyond experimentation and applying technology to solve specific business problems.
For manufacturers, rising costs and supply chain disruption often leave little capacity for transformation. The people best positioned to redesign processes and drive adoption are frequently consumed by day-to-day operations, making it difficult to move AI initiatives beyond isolated pilots.
Paul Dostaler, National Manufacturing & Distribution Industry Leader at BDO Canada, notes, “The manufacturers leading the way are breaking out of the ‘R&D prison’—a cycle of pilots and proof-of-concept initiatives that never make it into production.”
These organizations are embedding AI directly into operational environments, using AI to improve production by helping technicians access historical knowledge faster, streamlining customer service, and accelerating troubleshooting and decision-making on the plant floor.
For financial institutions, productivity challenges are often shaped by regulatory requirements, legacy systems, and increasingly complex data environments.
Many organizations continue to operate across fragmented technology platforms that create duplicate controls, disconnected data, and operational inefficiencies. As a result, AI initiatives often remain isolated within individual functions rather than creating enterprise-wide value.
Leading organizations are modernizing data environments, connecting information across systems, and embedding AI into customer service, finance and treasury management, lending, fraud detection, anti-money laundering monitoring, and reporting processes.
Importantly, governance is increasingly becoming an enabler of transformation rather than a barrier to it. In highly regulated environments, leading organizations are building governance frameworks alongside their AI initiatives. These controls help address regulatory expectations around bias, transparency, privacy, and risk management while enabling leaders to scale AI safely.
“Strong governance frameworks help clarify accountability, build trust, and create the confidence organizations need to scale AI responsibly,” said Ziad Akkaoui, Financial Services Industry Leader at BDO Canada.
For real estate and construction organizations, particularly developers, rising costs, tighter margins, and ongoing market volatility have reinforced a cautious approach to investment.
Many leaders remain reluctant to be first-movers, delaying technology investments until clear returns have been demonstrated. Jennifer Agro, National Real Estate & Construction Industry Leader at BDO Canada, sees this hesitation frequently in conversations with clients, “The challenge is that waiting carries its own risks; it means falling behind your competitors who are adopting AI and creating advantages.”
Leading organizations are using AI-enabled planning and dynamic forecasting tools to improve project coordination, optimize resource allocation, and reduce material waste. The benefits extend beyond operational efficiency. Faster project completion reduces financing costs, improves cash flow, and creates a meaningful competitive advantage in an industry where margins remain under pressure.
For private equity firms, productivity is ultimately a value creation strategy.
Investors are continuously evaluating opportunities to improve performance across portfolio companies. Firms are increasingly looking at leadership capability, workforce effectiveness, and operating model design.
“AI is beginning to reshape traditional value creation playbooks. Rather than focusing solely on where technology can be added, investors are reassessing how work gets done across functions such as sales, customer service, reporting, due diligence, finance, and decision-making,” said Sunil Sharma, National Leader, Transaction Services and Private Equity, BDO Canada.
Importantly, many firms are focusing less on selecting the "right" technology platform and more on understanding how AI could reshape their portfolio companies over time.
What leaders should prioritize now
For leaders trying to improve productivity over the next one to two years, the challenge is determining where to focus your priorities first. Here, we highlight five priorities leaders can implement today.
Identify high-friction workflows
Organizations should begin by identifying workflows where decision-making stalls, coordination overhead is excessive, or operational friction creates bottlenecks. Leaders should prioritize workflows that combine:
- High decision frequency
- High operational impact
- Strong data and leadership readiness
These areas often create the largest opportunity for measurable productivity gains and can help build momentum for broader transformation efforts.
Redesign workflows from first principles
Once high-friction workflows have been identified, leaders need to reassess them from the ground up, stripping processes down to core components.
That means challenging assumptions that may no longer serve the organization and asking whether current ways of working reflect today's business realities or yesterday's constraints. In practice, this often involves:
- Eliminating activities that no longer create value
- Reducing unnecessary approvals and handoffs
- Improving access to information and insights
- Simplifying decision-making processes
- Redesigning workflows around speed, responsiveness, and business outcomes
The objective is not to make existing processes marginally faster—it is to remove friction, improve decision quality, and increase organizational capacity.
Reallocate resources intentionally
Improving productivity often requires making deliberate decisions about what to stop funding. Organizations need to reduce investments in activities that add complexity without adding value.
Leaders should instead redirect resources toward:
- Workflow redesign
- Operational intelligence
- Data accessibility
- AI enablement
- Change management
- Workforce adaptability
Build adaptability—and lead the change
Many organizations are encouraging experimentation and learning around AI tools. But long-term productivity improvement will depend less on curiosity and more on adaptability.
As Sonia Edmonds shared, "Curiosity matters. But adaptability matters more.”
Organizations need to create the conditions for change. This requires strong change management, clear leadership direction, and a willingness to challenge long-standing ways of working.
Leaders should focus on:
- Communicating a clear vision for the future of work
- Creating accountability for productivity outcomes
- Equipping employees to succeed with new skills and capabilities
- Supporting experimentation and workflow redesign
- Aligning incentives and performance expectations with new ways of working
As AI adoption accelerates, organizational adaptability may become one of the most important determinants of long-term competitiveness.
Build AI literacy at the leadership level
Organizations do not need every executive to become a technology specialist. However, leadership teams need sufficient understanding of AI capabilities, limitations, governance requirements, and operating model implications to make informed decisions about transformation priorities. BDO’s AI Vision Report: Past the Pilot to the Agentic Future of Work provides perspectives on how these capabilities are expected to reshape organizations, leadership teams, and the future of work over the coming decade.
Without that understanding, organizations risk either overestimating AI's capabilities or delaying action unnecessarily.
From awareness to action
Productivity has moved higher on the agenda for Canadian business leaders over the past year. Economic uncertainty, workforce pressures, rising costs, regulatory complexity, and accelerating AI adoption have all increased the urgency around improving performance and competitiveness.
Most organizations already understand the importance of AI, digital transformation, and operational modernization for improving productivity. Awareness is not the challenge. The challenge is translating that awareness into meaningful organizational change—quickly enough to create an advantage.
Organizations that are making progress are not waiting for perfect timing. They are building the capabilities, leadership alignment, and adaptability needed to respond as conditions evolve.
The productivity conversation is ultimately a leadership conversation. It requires making decisions in the face of uncertainty, challenging assumptions that no longer serve the organization, and creating the conditions for change to take hold. This is where BDO is helping organizations focus their efforts—identifying productivity barriers, redesigning workflows, building governance capability, and turning transformation ambitions into practical outcomes. We also help organizations improve finance effectiveness by streamlining back-office operations, enhancing reporting, and increasing financial visibility to support better decision-making.
The organizations that emerge stronger over the next decade are unlikely to be defined by the technologies they adopted. They will be defined by how effectively they empowered their people, adapted to change, and translated that change into sustained performance.
Looking to create measurable productivity gains?
Sources:
Angus Reid survey conducted on behalf of BDO Canada, April 2026.