Jim Lao

Enterprise AI spending is surging globally: budgets doubled in the current year, and one estimate put 2026 business AI outlays at $2.59T.
Yet most organizations reported limited payoff, with research showing 96% did not see dramatic gains in efficiency, innovation, or work quality overall.
The core issue was not AI capability but outdated business architecture, where tools worked technically while workflows failed to carry context across teams.
One framework said 70% of AI value comes from people, culture, and process change; infrastructure contributes 20%, with algorithms accounting for 10%.
To improve returns, companies should phase adoption: start with routing, add predictable automation, preserve customer context, then expand once those foundations are solid.

AI Investment Needs Process Transformation

In Canada, children often learn money habits by watching daily choices, making parental behavior more influential than formal lessons when financial values take shape.
Family finance research suggests ~90% of children would ask parents for money advice, yet only ~60% of parents feel confident having that conversation.
One key lesson: status purchases can feel hollow, while spending aligned with purpose, utility, or experiences may better reflect what success actually means.
A smaller car once changed the spending yardstick: performance stayed the same, fuel costs fell, and value became function instead of image.
In Ontario, a health center found online sports betting among students reached ~10% by 2025, showing how quickly money messages now reach children.