IT Support Provider in Toronto Shares a Guide on Adopting AI in Business
The 2025 AI Index from Stanford reports that 78% of businesses worldwide now use AI, which is a huge increase, as only 55% were using it last year. Large companies use AI pervasively, while smaller businesses are slower to adopt it. Part of the reason why smaller companies are slower is that adopting AI in business is more complex than it may seem.
| “Many businesses rush into AI adoption. There is value in getting ahead of this trend, but rushing isn’t doing you any favours. Instead, you must take a moment to think about why you need AI. This exercise will help you select tools that your employees will actually use.” – Cory Kiehn, VP of Sales at Tenecom |
Despite its complexity, being left behind is risky. A business that delays AI adoption risks slower output, weaker competitiveness, and higher operational costs. Competitors that use AI can complete work faster, produce better insights, and reduce errors, which raises performance standards across the market.
That’s why you need a plan on how you’re going to use it effectively. It’s not enough to simply purchase an AI platform. One survey by Gallup found that only 16% of employees actually find the AI tools their employer invested in helpful in their daily workflows.
If 78% of businesses are investing in them, and only 16% of employees are truly using them, there is clearly a disconnect between what employers are purchasing and what they should be purchasing.
In this article, a reliable Toronto IT support provider explores the key benefits of AI adoption, how to implement the right tools, and best practices to get the most value.
What Are The Biggest Benefits of Adopting AI in Business?
1. Improved Process Efficiency
Implementing AI lets companies automate repetitive, low-value tasks so human effort shifts toward higher-value work. By streamlining routine workflows, businesses can reduce time and resource spend, lower error rates, and more reliably deliver on commitments.
2. Smarter Decision-Making
AI systems help analyze large volumes of data, detect patterns, and generate insights that are difficult for humans to spot on their own. This means managers and teams can base choices on evidence rather than intuition alone, leading to better outcomes and fewer missteps.
3. Cost Reduction
AI adoption often leads to measurable cost savings by reducing manual effort, speeding processes, and lowering waste. In many cases, the investment in AI pays off because fewer resources are required to achieve the same or better results.
4. Risk Detection
AI tools make it possible to monitor operations in real time and flag anomalies or emerging issues. This strengthens oversight and allows organizations to act sooner when things start going off track. Tightening controls this way makes it easier to reduce losses and avoid regulatory compliance issues.
5. Innovation
Using AI opens opportunities for new business models, services, and products that were previously impractical. This means organizations can adapt more agilely to change, seize new markets, or differentiate themselves from competitors.
6. Talent Liberation
When AI handles routine or data-heavy tasks, employees are freed to focus on strategic, creative, or relational work. That shifts the human role from execution to thinking, problem-solving, and innovation. This change can improve job satisfaction, retention, and help your company harness the full potential of your workforce.
How to Adopt AI in Business
1. Define Why You Want AI in The First Place
List your top business objectives, such as faster response times, better reporting, or reduced manual work; simply “keeping up with trends” is not enough. 42% of businesses already underutilize their IT tools; you don’t need your AI investment to end up in the same place.
Tie each objective to a specific team or function. This gives you a clear filter for which AI tools you should even consider.
2. Map Current Workflows
Ask each team to document how work gets done today, including where delays, rework, or errors show up. Highlight tasks that are repetitive, data-heavy, or rule-based. These are strong candidates for AI support because they are easier to automate or augment.
3. Identify Specific AI Use Cases
Turn your goals and workflow insights into clear use cases, such as “draft first-pass customer emails,” “summarize meeting notes,” or “flag unusual transactions.” Write a simple success statement for each use case so you know what “good” looks like before you pick a platform.
4. Shortlist & Test AI Tools Against Real Work
Research a small set of tools that match your use cases. Run a limited pilot with real tasks and real users from different roles. Compare how each tool impacts speed, accuracy, and ease of use. Keep tools that fit your workflows instead of forcing teams to adapt to poor fits.
5. Prepare Your Data
Decide what data AI tools can use, who can access them, and what information must stay out of the system. Document simple rules for acceptable use, privacy, and review. This helps you manage risk while still allowing employees to experiment and learn.
6. Roll Out in Phases & Track Adoption
Start with a few teams, then expand once you see proof of value. Provide short, practical training focused on the tasks employees actually perform. Measure usage and outcomes, then adjust your tools or use cases if adoption is low. This keeps your AI investments aligned with how people really work.
Common Challenges of AI Adoption in Business You’ll Need to Mitigate
Technology is often full of surprises. While there is a lot that you can do to keep it predictable, new updates and advancements will introduce new changes. So, it’s important to anticipate what you can and proactively plan how you intend to mitigate it.
Here are some insights.
| Challenge | What To Mitigate | How To Mitigate It |
|---|---|---|
| Limited access to proprietary data | Weak model performance caused by incomplete, inaccurate, or minimal internal data. | Invest in basic data cleanup, document data sources, and confirm which datasets are reliable enough for AI use. |
| Difficulty scaling | Strong early tests that fail to translate into sustained enterprise-level value. | Start with small wins, review usage patterns, and refine workflows before expanding AI into more teams. |
| High oversight demands | Time-consuming human review is needed to correct errors, address drift, or validate outputs. | Assign owners for each use case, schedule regular reviews, and track output quality over time. |
| Skills shortages | Slow adoption because staff lack experience with AI or prompt-based tools. | Provide hands-on training using real tasks, build internal champions, and offer ongoing learning time. |
| Early financial losses | Cost overruns are usually linked to poor implementation, rework, or unplanned risks. | Test tools in low-risk environments, compare vendors carefully, and review potential risks before committing. |
Best Practices For AI Adoption in Businesses
Involve Your Employees
Speak with the people who will use the AI tools every day. Ask what slows them down and what would make their work easier. Turn their feedback into a short list of “must have” and “nice to have” features. This reduces the risk of wasting money on tools that no one ends up using.
Create Simple, Practical AI Use Guidelines
Publish short, plain-language rules for how employees should and should not use AI, including privacy, confidentiality, and acceptable content. Reference existing regulations and internal policies so people know which tasks are appropriate for AI and which need human handling.
Invest In Hands-On Training
Offer training that shows employees how to use AI on their own tasks, not just generic demos. Give people time to experiment, share examples, and refine prompts, so the tools feel like part of their normal workflow instead of an extra chore. A lack of skills and unclear value are common barriers, and structured learning improves comfort and usage.
Set Realistic Expectations
AI works best when you treat it as a tool that supports your work rather than something that replaces full tasks. Many business owners expect AI to replace large chunks of human work quickly. In reality, this is rarely the case.
One Deloitte survey found that only 10% of businesses that have adopted AI are seeing their expected ROI from it. This result is less about the value of the tools and more about how they were evaluated. So, instead of expecting massive shifts, expect initial results to be modest. Aim for small, steady improvements, followed by larger gains after time has been spent refining workflows.
Document What Success Looks Like
Record how AI should improve timelines, quality, or workflow steps. Share these targets, so teams understand why the tool matters. This creates internal alignment and helps avoid the disconnect between investments and real usage.
Work With Vendors Who Offer Strong Support
If AI adoption is new to your business, seek partners who can provide strong support. Like any technology, you will inevitably encounter unexpected issues as AI weaves itself into your workday. Someone who already has extensive experience with these tools can help you navigate these challenges.
Adopt AI in Business with Trusted IT Support in Toronto
AI is a new technology, so understanding how it can benefit your business may not be clear. You’ve likely heard many popular reasons to use it, but these benefits may or may not apply to your organization’s specific workflows. That’s why careful analysis is required.
If you want help from experts, ask Tenecom’s team of IT consultants. We can help you assess your current IT infrastructure and help you make decisions about where AI can fit in. Our goal is to help you get the most bang for your buck by helping you invest in tools that truly add value.
Contact a trusted Toronto IT support provider today to tell us more about your needs.
