The Task, the Data, the People: The Three Things to Align So AI Pays Off

If AI's advantage in isolation is only 5.1%, the practical question becomes: where does the rest of the benefit hide, and how do you capture it? Statistics Canada's 2026 data points to the complementary investments: data analytics, training, processes. Translated for an SME that wants a concrete starting point, it comes down to three things to align: the right task, clean data, a team on board.

The right task first. A task worth a first AI project is repetitive, time-consuming, and runs on text, numbers or customer requests. Preparing quotes, sorting emails, summarizing documents, making sense of sales data: nothing exotic. The test is simple. If you can't name the task in one sentence and estimate the hours it eats each week, it's not yet the right starting point.

Clean data next. AI works on what you feed it. Before installing it, you need to know where the information the task requires lives, whether it's reliable, and whether it's accessible without begging for it across three systems. This isn't a big IT project. It's targeted tidying, limited to what the task requires. But it's that tidying, more than the tool, that decides the quality of the result.

The people last. A tool no one uses produces nothing, and a misunderstood tool produces distrust. Bringing the team on board means explaining what the machine does and doesn't do, giving them time to get comfortable, and listening to what they see that you don't. It's the least technical and most decisive part. Align those three things, and the tool's small 5% starts working alongside the big 95% of the rest.

At Paquin & Co., our work is exactly to align those three things with you, in the right order. paquinco.com