How to use AI to solve business problems
Decide when to use AI, search, or automation. Compare sales, support, and operations examples, then test one workflow with a practical pilot checklist.
Direct answer
AI can help solve business problems when a task requires interpreting text, finding scattered information, or drafting a response with context. Start with a recurring workflow and measure how it performs today. Use rules for predictable steps, restrict access to approved sources, and keep decisions that affect customers or the business with the person accountable.
- If you can express the condition as a rule, automate it first.
- If people cannot find the current version, improve search first.
- If a draft would save time, test AI with source links and human review.
Choose the tool based on where work gets stuck
| Problem | First intervention | What to measure |
|---|---|---|
| Quotes go without follow-up | A rule creates a task for the owner when the follow-up deadline passes. AI can summarize the history or draft a message if that saves work. | Quotes followed up on time and duplicate tasks. |
| Inconsistent support answers | Retrieve the current article from an approved knowledge base and draft a response the support rep can verify. | Answers backed by the correct source and requests escalated. |
| Requests arrive with missing information | Extract details and suggest a category. A person confirms ambiguous fields before they are recorded. | Correct fields and requests that require correction. |
Illustrative example: quotes that go unanswered
A sales team sends quotes from its CRM, but reps keep reminders wherever they can. Before adding AI, set a deadline and a rule: if the opportunity is still open, has an owner, and shows no reply, create a task. If the buyer already replied or the deal is closed, do nothing.
Once the task is visible, an assistant can summarize the conversation and draft a message from approved records. The rep checks the tone, price, and promises before sending. When something is missing, the assistant flags it rather than filling in the blank.
Compare the share of quotes followed up on time before and during the trial. Count unnecessary alerts and drafts that had to be rewritten. If the rule alone solves the delay, keep the rule.
Checklist for your first pilot
- Choose a task with enough volume, an accountable owner, and a success criterion.
- Record how long it takes and how often it fails before the pilot.
- Include ordinary cases and exceptions: missing data, conflicting sources, and users without access.
- Start with read-only access or drafts. Require approval before sending messages or updating records.
- Compare time, quality, and corrections against the baseline. Stop the pilot if it exposes information outside approved permissions.
For a fuller approach to documenting and measuring AI risk, see the NIST AI Risk Management Framework.
Where Cohere fits
Cohere offers components to search by meaning, rank results, and generate answers from retrieved context. Digital Reset assesses how these capabilities fit your data and workflow. If the bottleneck is a missing rule or an outdated source, that comes first.
Cohere implementation for businesses
Official sources
Sources checked on .
What task would you like to test first?
Tell us how it works today, who owns it, and what data it uses. We can use that to scope a useful pilot.
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