AI can be worth paying for if it helps your team finish work that has been piling up, cut paid overtime, or deliver work faster after you account for the time spent checking its output. Start with a question. If AI gave your team five hours back next week, what would you do with them, and who would do that work?
The Canadian Federation of Independent Business (CFIB) estimated an average of 5.4 hours of net time saved per business over a standard five-day week among small and medium-sized businesses already using generative AI. The calculation used two survey estimates: (2.05 hours the work would otherwise take − 0.97 hours spent using AI) × 5 days = 5.4 hours. Use the figure as a starting point for the question, and use your own records to estimate the answer.
Decide What You Want the Time Back For
The value depends on where the hours land. Time recovered during a busy period might reduce paid overtime. Time given back to a supervisor might let them clear an approval backlog that holds up several people. An owner who gets their evenings back might consider that worthwhile on its own. Each is a different reason to spend money, and each calls for different evidence. If your reason is lower overtime, check overtime. If it's faster approvals, check how long work sits waiting for approval.
In a separate OECD survey, 65% of small and medium-sized businesses using generative AI said it improved employee performance, 45% said it helped them save money, and 26% said it helped increase revenue. These are reported benefits across the countries surveyed. The survey did not measure the size of those gains. The size of the gain depends on what changes in your own workflow.
Find Out What AI Adds to the Work
An Ontario manufacturer quoted in the CFIB report described using generative AI to create templates that staff then adapted to their needs. The benefit they described was avoiding the work of starting from scratch. That detail raises a useful question for any business considering a recurring AI expense. Once you have a good template, how much work is left for AI to do each time?
Look for recurring work where a first draft takes time and someone can check it against a reliable source. Drafting routine customer replies, turning approved meeting notes into action lists, or pulling standard sections into a proposal can be good candidates.
Compare AI with the simplest way your team could get the result. That might be a reusable template, a feature in software you already pay for, or a change to who reviews the work. Ask what AI would add to that version of the process. A faster first draft can be useful. How much it matters depends on what happens between that draft and the finished work.
Protect Customer Information and Check the Output
Before uploading customer emails, invoices or contracts to a cloud AI tool, check what information the task actually needs, how the provider handles it, and who can access it. Use records without personal information where possible. Check which privacy law applies to your activity, including PIPEDA or applicable provincial law. In Ontario, health information custodians handling personal health information should assess the proposed use under PHIPA. See the federal privacy commissioner’s AI privacy guidance for businesses for practical considerations.
Assign someone to review AI-assisted work before it goes to a customer. Have them check prices, contract terms and commitments against approved sources. Where the work calls for professional advice or specialist judgment, have a qualified person review it.
Put a Number on the Benefit
Take a batch of recent work suitable for the tool, including items that came back for correction, and compare the time it takes to finish with and without AI. Use the same standard for accuracy and completeness. Record the minutes spent preparing inputs, reviewing the output, and correcting errors. Then use your normal monthly volume to estimate how much time you could recover.
Monthly hours recovered = net minutes saved per finished item × monthly volume ÷ 60. Net time includes preparation, review and corrections. For the arithmetic, 12 net minutes × 100 items ÷ 60 equals 20 hours of capacity per month.
Keep the time estimate separate from the financial result. If your goal is to reduce overtime, use payroll records to see how many paid overtime hours actually disappeared and what they cost. Compare that reduction with the recurring cost of the tool and the work needed to maintain it. Include setup, training and data preparation when you assess the overall investment. If the hours go toward clearing a backlog, track how long work waits and who is using the time to clear it. If your aim is to grow sales, track the share of quotes you win separately from how quickly you send them.
Decide What Would Make You Continue, Narrow or Stop
Choose a review date based on how often the work occurs and how long staff need to learn the process. A few weeks may give you enough evidence for a frequent task. A workflow that needs integration or has a seasonal workload may need longer. Agree on what you will look for before you start.
For a project meant to cut costs, check that verified monthly savings cover the tool and the staff time needed to maintain it. The amount left over should cover setup costs within your agreed payback period. If the goal is faster approvals or better turnaround, set a target for that result and decide what you are prepared to pay for it.
- Continue if the result improves enough to justify the cost and the team can sustain it.
- Narrow the scope if the tool helps with routine work but the exceptions take too much time to check or correct.
- Pause or stop if the net benefit disappears after review, serious errors keep recurring, or you cannot handle the required information appropriately.
Before You Review Proposals or Apply for Funding
Once you know what result would justify the investment, you can ask a provider to explain how the proposed work will help you reach it, how you will test it, and what your team will still need to do after handover. Our guide to reviewing AI consulting proposals covers the scope, fees and responsibilities to clarify before signing.
Funding can change what you pay and when you can start. It helps to work out what the project is worth to your business before deciding how to fund it. If you have a defined project in Ontario, see our guide to AI grants and funding for Ontario small businesses for program fit and timing.
If you're weighing an AI investment and the expected benefit is still hard to pin down, bring us one workflow and the result you'd like to improve. We can help you identify where the work is getting stuck, compare your options and decide what would be worth testing. Explore AI consulting for small businesses.
Sources
Canadian Federation of Independent Business. Digital Transformation: How Small Businesses in Canada Are Leveraging AI and Technology for Growth and Productivity. Time-savings estimate (p. 18 and Appendix A) and Ontario manufacturer example (p. 16).
OECD. Generative AI and the SME Workforce. Reported benefits among businesses using generative AI (Figure 2.7).
Office of the Privacy Commissioner of Canada. AI, Privacy, and Your Business and Privacy Guide for Businesses. Generative AI privacy guidance and federal privacy obligations.
Information and Privacy Commissioner of Ontario. Collection, Use and Disclosure of Personal Health Information. Ontario’s PHIPA requirements for health information custodians.