Here's something most business owners already suspect but rarely act on: a significant chunk of their team's week is spent on repetitive, manual tasks that don't require human judgement. Data entry, sorting emails, generating reports, chasing invoices — the list goes on. According to Barefoot Solutions, companies across industries are now using AI to take over tasks like data entry, customer support, document processing, and scheduling, freeing up staff for work that actually requires creativity and decision-making.
The problem isn't a lack of AI tools. There are thousands of them. The real challenge is knowing where to start — figuring out which of your specific processes are good candidates for AI assistance, and which ones aren't worth touching. That's exactly what we do at Brain.mt, and below I'm sharing the six-step approach we use with our clients.
1. Define What You Actually Want to Achieve
Before looking at any tool or platform, get clear on your objectives. Are you trying to reduce the time your team spends on admin? Cut down on errors in financial reporting? Speed up customer response times? As Ivan Carillo outlines in his widely shared LinkedIn framework, establishing clear objectives is the essential first step. Without them, you'll end up buying software you don't need and ignoring the problems that actually cost you money.
2. Map Out Your Current Processes — Honestly
This is where most businesses skip ahead, and it's a mistake. You need to sit down and document how things actually work today — not how you think they work, or how they're supposed to work. According to Cyber Husky, many organisations discover that their real workflows look nothing like their official procedures. Gaps, workarounds, and bottlenecks only become visible when you write it all down. Ask your team: What takes you the longest each week? What do you dread doing? Where do mistakes happen most often?
3. Identify and Prioritise the Right Tasks
Not everything should be handed to AI. The best candidates are tasks that are repetitive, rule-based, and time-consuming. Barefoot Solutions points to six common areas: data entry and management, customer service queries, document processing, scheduling, report generation, and quality checks. Once you have a list, rank each task by three criteria: how much time it consumes, how complex it is, and how much impact improving it would have. Start with the quick wins — the tasks that eat up hours but are relatively straightforward to address.
4. Build a Concrete Plan (Not a Wishlist)
A plan means specifics: which tool handles which task, who's responsible for the transition, what resources you need, and a realistic timeline. Carillo's framework recommends outlining each step of the process, the tools to be used, and the resources needed. This isn't about buying the fanciest AI subscription. Sometimes a well-configured chatbot or a simple document-processing tool does the job perfectly well.
5. Implement Step by Step — Don't Try to Do Everything at Once
Roll out changes one process at a time. Cyber Husky makes an important point here: the best AI automation projects work within your existing systems rather than replacing everything overnight. Start with one department or one workflow. Get it right. Learn from the bumps. Then move to the next one.
A Real-World Example: Invoice Processing
Let me give you a concrete case. One of our clients — a mid-sized services company — had a finance team spending roughly 15 hours per week manually entering invoice data into their accounting system. We mapped their process, identified the bottleneck (manual data extraction from PDF invoices), and introduced an AI-based document processing tool that reads invoices, extracts key fields (supplier name, amount, date, VAT number), and populates their system automatically. The finance team now spends about 2 hours per week reviewing and approving entries instead of typing them in. That's 13 hours reclaimed every single week — over 670 hours per year — for one process alone.
6. Monitor, Adjust, Repeat
Once a process is running with AI assistance, keep an eye on it. Are error rates going down? Is the time saving real? Carillo's final step is to monitor performance and adjust as needed. AI tools improve over time, but they also need human oversight, especially in the early weeks. Set up simple metrics — time saved per week, error count, employee satisfaction — and review them monthly.
Ready to Find Your Hidden Hours?
If any of this resonates with you, that's exactly the kind of work we do at Brain.mt. We help businesses identify which processes can benefit from AI, guide you through the selection and setup of the right tools, and make sure your team is confident using them. I also offer dedicated workshops and training sessions tailored to your industry and your specific workflows. Get in touch to start a conversation — you might be surprised how many hours are hiding in plain sight. 🚀
