Tech Explained: Here’s a simplified explanation of the latest technology update around Tech Explained: Turning Canada’s AI momentum into measurable returns in Simple Termsand what it means for users..
Although 93 per cent of organizations report using AI in some capacity, most remain far from full deployment. Only 31 per cent have moved beyond proofs of concept and pilots to implement AI across core operations, while the rest are still in early stages: 32 per cent with partial deployment into select workflows and 20 per cent still testing or piloting.
Organizations continue to report that generative AI has yet to produce measurable business returns, a finding that reflects the current state of deployment. With most implementations still in pilot or partially deployed phases, the conditions for meaningful value capture are not yet in place. Only two per cent of respondents said their organizations are seeing a return on their generative AI investment. Among those reporting a return, more than half (57 per cent) described it as modest (between five and 20 per cent) while nearly one third (31 per cent) were unable to quantify it at all.
Behind these modest returns lies a common challenge: many organizations still face foundational barriers that prevent AI from scaling across the enterprise. Legacy systems, siloed data, and unclear success metrics often prevent AI from being embedded throughout the organization.
Low AI integration may also reflect a lack of clear strategy for selecting the right use cases. Companies should not underestimate the effort it requires to select, refine, and mature their use cases, ensuring that they create both tangible business value and personal value for employees. When AI tools address real pain points and make day-to-day work easier, employees are far more likely to adopt, adapt, and sustain use.
A further contributor to low ROI may be the tendency to layer AI on top of existing processes rather than redesigning workflows to take full advantage of the technology. Integrating AI into current workflows can create incremental improvements, but the greatest value comes from AI-optimized processes where tasks, decisions, and systems and redesigned to leverage AI’s full capabilities.