How AI can make your business more profitable

A look at AI projects that cut costs and improve margins

6-minute read

Published July 16, 2026

When used strategically, artificial intelligence (AI) can save time. But does that time really translate into cost savings?

That’s the real question business owners should ask when adopting AI. “You should always look at AI through the lens of return on investment,” says Hugues Mailhot, Partner and Vice-President at Explorai, a Canadian AI consulting firm.

“If a tool costs $100 a month, ask whether it actually saves at least five hours of work. If not, it isn’t worth using.”

Still, the potential is there. SMEs that use AI to automate administrative tasks and certain sales, marketing and finance activities can aim to save about 10% on payroll costs in the first year, and up to 25% in the second year, according to Mailhot.

If you have six office employees and a gross annual payroll of $500,000, AI can help you aim to save about $50,000 in the first year, and around $120,000 in the second. That’s a major impact.

Tasks you can automate with AI

AI can automate some or all of these tasks, but it doesn’t replace human supervision and validation.

Administrative tasks	Finance and billing	Human resources (HR)
Sorting, filing and drafting emails Transcribing and summarizing meetings Preparing and analyzing calls for tenders Entering and extracting data	Processing invoices Bookkeeping Preparing financial reports Reviewing contracts Automating accounts payable and accounts receivable management Budget forecasting	Writing job descriptions Screening and shortlisting resumes Preparing HR documentation Analyzing employee satisfaction surveys Preparing schedules
Sales	Marketing	Operations and production
Providing customer service with chatbots Forecasting demand Preparing client briefs Drafting sales letters and responses Qualifying leads	Creating content (text, images, video) Automating and planning campaigns Monitoring competitors Translation Personalized marketing Client segmentation	Predictive maintenance Sorting service requests Production scheduling Detecting anomalies using computer vision Optimizing delivery and logistics Optimizing inventory management

3 AI use cases to make your business more profitable

1. Automating administrative tasks

AI can help automate most of a business’s administrative tasks.

For example, AI can read and analyze an email that says, “Where is my order?” or “I haven’t received my photos,” then prepare a draft response for a team member to review before it is sent out.

Managing invoices is another example. If you receive invoices by email, print them, send them for approval and manually re-enter them into your system, low-cost tools can help you do the work faster.

If you have 200 invoices to process each week and that work takes five hours, that adds up to 20 hours a month. In this case, using AI can be worthwhile.

In every business, some tasks add little value. They are tedious and repetitive. That’s where we should be using AI, without replacing human expertise.

To take it a step further, consider AI agents, which are essentially virtual collaborators.

Some, such as HR agents, are designed to meet specific needs.

“An employee can ask the HR AI agent for the internal policy on paternity leave or who to contact for a replacement hard hat,” explains Mailhot.

Specialized agents can also work together semi-automatically. For example, one agent can check a CRM overnight for missed tasks, while another drafts emails for human review.

“AI agents will transform office work in the coming years,” says Mailhot.

2. Cost estimating and bidding on calls for tenders

AI can generate significant gains, especially in sectors such as construction and manufacturing, where businesses prepare a high volume of bids in response to calls for tenders.

In particular, it can speed up cost estimating, document analysis, information extraction and the preparation of draft bids.

Preparing bids takes hours of research, analysis, calculations and data extraction. The main challenge is that the time spent isn’t billable: if you win one project out of eight, the other seven don’t generate any revenue.

3. Production scheduling

AI can complement your ERP system or use relevant data from an Excel file to consider order delivery dates, raw material availability and team schedules, then determine the order in which to manufacture your products. It can also simulate different production scenarios in advance to help you choose the best course of action.

For example, avoiding machine cleaning between two similar production runs can save valuable time and improve efficiency.

Instead of realizing that you should have done things differently at the end of the week, you can test production scenarios ahead of time. AI can help reduce the time needed to create the production plan by 60%.

Where to start

Identify recurring, well-documented tasks that take up more than 15% of your team’s time. Choose one concrete task to test with AI, without turning it into a major project or committing a large budget.

“Don’t set up an AI committee to try to find the best ideas and wait for everyone to agree. I recommend choosing one repetitive process to test with an AI agent. Measure the time saved and keep going if it works. Then build a company-wide AI strategy,” says Hugues Mailhot.

He adds that the first department to assess for potential AI projects is the one where you are about to hire a new employee. Before starting the recruitment process, look at which processes and clerical tasks could be automated.

Although generative AI has become increasingly common in recent years, its business applications go much further. In many cases, they involve several systems or tools working together.

Mailhot compares AI to Lego pieces: you assemble several building blocks, such as a vision model, a generative AI model and other tools, and coordinate them to produce the desired result through an interface.

AI is neither a monolith nor a magic wand. It’s a tool used in a process. Like medicine, AI has many specializations, and each project requires the right combination of tools.

Mistakes to avoid

Trying to do everything at once.

Buying and implementing several AI tools piecemeal, without a plan or a clear inventory of your needs, can leave you with “a tangled patchwork of systems that don’t work together and will eventually need to be sorted out,” says Mailhot.

Starting small with a pilot project is a good start, but you then need to define a company-wide AI strategy.

Buying pro licences for the whole team at the outset.

Identify team members who are comfortable with the technology and interested in joining a pilot project.

Neglecting data security and privacy risks.

Mailhot warns against using free versions of generative AI when working with company data. “For about $20 a month, you can get a better version that ensures data confidentiality. If it’s free, you’re the product.”

Using AI to replace human expertise entirely.

AI can help us work faster, but it should not replace human judgment. “Brands and businesses with a more distinctive voice will stand out in the years to come. And the people who will succeed will be the people who know how to use AI effectively,” concludes Mailhot.

Next step

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