AI is not equally useful everywhere
To find where AI will give value for you specifically, it helps to know what it is strong and weak at. Then you will see your tasks in this light. AI is especially good where there is a lot of text, data, repetitive routine and typical communication — and every company has plenty of that.
Where AI usually gives value
- Routine processing: mass repetitive tasks (sorting, data entry, categorization).
- Text work: content, emails, documents, translations, summarization.
- Data analysis: reports, finding patterns, parsing feedback.
- Typical communication: first-line support, reply drafts.
- Accelerating specialists: drafts for lawyers, marketers, analysts.
Where AI is weak or dangerous
- Accuracy-critical: where an error is unacceptable without verification (finance, law, medicine).
- Decisions about people and strategy: judgment, empathy, context.
- Top-level unique and creative work: where the human spark is exactly what is valued.
How do I understand which processes in my company are good candidates for AI?
Walk through the processes and look for signs: 1) A lot of repetitive manual work with text or data (sorting tickets, drafting standard documents, data entry). 2) Bottlenecks where there are not enough hands for routine. 3) Tasks where employees spend time on "blanks" instead of valuable work. 4) A large volume of similar communication. Mark 3-5 such points with the biggest potential (a lot of time x often). That is your candidate list. Avoid starting with accuracy-critical areas without human control. Tell me about your company and I will help prioritize.
Look for the "painful and frequent" intersection
The best AI candidates are tasks that both take a lot of time and happen often. A one-off complex task is not worth adoption; frequent routine is a gold mine. Map processes along these axes and start with the top-right corner.
Rule: AI gives value where there is a lot of text, data and frequent routine. Start with tasks that are both painful and frequent, avoiding accuracy-critical ones without control.
🧠 Which tasks are the best candidates for AI adoption?