AI tools can help businesses analyse information, assist customers and automate selected tasks. Their value depends on the problem, the quality of the data and how carefully people review the results. This article introduces common applications across industries.
A practical example
Before buying an AI tool for invoice processing, identify the document types, sensitive fields and accounting checks involved. Trial it with permitted representative examples, including poor scans and unusual layouts. Decide who approves the result and how errors are corrected. Evaluate the whole workflow, including integration and review time, rather than only extraction speed.
Choose an AI tool by its job
| Focus | Practical approach | Check before proceeding |
|---|---|---|
| Input | Identify the information the tool must process. | Check permissions and the handling of sensitive data. |
| Output | Define what a useful result looks like. | Evaluate realistic examples before wider use. |
| Workflow | Choose where a person reviews or approves the result. | Account for integration effort and ongoing monitoring. |
How can a small business compare AI tools fairly?
Use the same representative tasks and agreed evaluation criteria. Include incorrect outputs, review effort, data handling and operating cost in the comparison.
Useful next steps
For a related perspective, read AI and Machine Learning: Start With a Measurable Product Problem, Responsible AI Development: Data, Impact and Accountability, Using ChatGPT at Work: Drafting, Summarising and Planning.
If you need help applying this to your business, explore our AI development and automation or discuss your project.
Sources and further reading
By Tech Me Today. Originally published September 25, 2023. Expanded on .
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