Artificial Intelligence
Getting Started with AI in Your Business: Practical First Steps
AI can save real time on everyday work, but only if you start with the right problem and put sensible checks in place. A practical guide to choosing a first use case, managing risk and measuring results.
SAG Encoders · · 2 min read
Generative AI tools can draft, summarise, classify and extract information from text in seconds. Used well, they remove hours of repetitive work. Used carelessly, they produce confident mistakes and can expose confidential data. The difference is mostly in how you start.
Start with a problem, not a tool
The best first projects are tasks that are frequent, time-consuming, text-heavy and easy to check. Good candidates include:
- Drafting first versions of emails, proposals, job descriptions and product descriptions.
- Summarising long documents, meeting notes or customer feedback.
- Extracting data from invoices, receipts and forms into a spreadsheet or system.
- Triaging customer enquiries by topic and urgency so they reach the right person faster.
- Answering questions about your own policies and documents for staff.
Avoid starting with decisions that seriously affect people, such as hiring, lending or medical advice, where errors are costly and fairness matters most.
Understand the main limitation
Large language models generate text by predicting likely words. They do not look facts up unless they are connected to a source, so they can produce fluent answers that are simply wrong, often called "hallucinations". Two practices reduce this risk:
- Ground the AI in your own information. A technique called retrieval-augmented generation (RAG) gives the model the relevant passages from your documents and asks it to answer from them, ideally with references you can check.
- Keep a human in the loop for anything that goes to a customer, involves money or has legal consequences.
Protect your data
Before staff paste information into an AI tool, check the provider's terms: where data is processed, how long it is kept, and whether it may be used to train models. Business plans from major providers usually offer stronger commitments than free consumer versions. Agree a simple policy on what may never be entered, such as customer personal data, passwords and confidential contracts, and remember that the Nigeria Data Protection Act applies to personal data however it is processed.
Run a small, measured pilot
- Measure the current process first: how long the task takes and how often errors occur.
- Pilot with a small group on real work, with a clear review step.
- Compare time saved and error rates against your baseline.
- Decide whether to expand, adjust or stop. Stopping is a valid result.
Build on a sound foundation
As your use grows, a light governance framework helps you keep track of where AI is used, who is responsible and how risks are managed. The US National Institute of Standards and Technology's AI Risk Management Framework is a free, widely referenced starting point. Finally, invest in people: staff who understand both the strengths and the limits of these tools get far better results than those who are simply handed a login.