AI use cases by industry
Practical AI uses for your industry, by team, with what each needs to work.
FreeRuns in your browserNo signupUpdated 2026-11-05
Effort levels
- Low Off-the-shelf tools, little or no connection to your systems.
- Medium Connects to one or two of your systems, with a person checking output.
- High Custom build, several systems or sensitive data, and testing before use.
Every use case keeps a person in charge of the final decision.
Use cases
9
Quick wins
5
Low effort: start here
Product descriptions
MarketingLow effortWrites and updates product copy and meta descriptions from specifications.
Needs: Clean product data, a brand voice guide, and a check on every claim.
Review analysis
MarketingLow effortGroups reviews and support tickets by theme so recurring problems stand out.
Needs: An export of reviews and tickets.
Email sorting and reply drafts
OperationsLow effortSorts incoming email and drafts replies for a person to send.
Needs: Access to the shared inbox, a tone guide and an approval step.
Meeting notes and actions
OperationsLow effortSummarises meetings and lists actions with owners.
Needs: Attendees' agreement to record, and a place to store notes.
Job ads and interview questions
HRLow effortDrafts job ads and structured interview questions from a role description.
Needs: A person who checks for accuracy and bias.
Order status and returns
Customer serviceMedium effortAnswers 'where is my order' and starts returns on the website or WhatsApp.
Needs: A connection to the shop and courier tracking, the returns policy, and a hand-off to staff.
Product recommendations
SalesMedium effortSuggests related products on the site and in emails.
Needs: A catalogue with good product attributes, and enough traffic to learn from.
Website FAQ assistant
Customer serviceMedium effortAnswers common questions on your website from your own content, with a hand-off to a person.
Needs: Current FAQs and policies, and a hand-off route.
Stock planning support
OperationsHigh effortFlags products likely to sell out or be overstocked, based on sales history.
Needs: At least a year of clean sales and stock data.
# AI use cases: Retail and e-commerce ## Product descriptions - Team: Marketing - What it does: Writes and updates product copy and meta descriptions from specifications. - What it needs: Clean product data, a brand voice guide, and a check on every claim. - Effort: Low ## Review analysis - Team: Marketing - What it does: Groups reviews and support tickets by theme so recurring problems stand out. - What it needs: An export of reviews and tickets. - Effort: Low ## Email sorting and reply drafts - Team: Operations - What it does: Sorts incoming email and drafts replies for a person to send. - What it needs: Access to the shared inbox, a tone guide and an approval step. - Effort: Low ## Meeting notes and actions - Team: Operations - What it does: Summarises meetings and lists actions with owners. - What it needs: Attendees' agreement to record, and a place to store notes. - Effort: Low ## Job ads and interview questions - Team: HR - What it does: Drafts job ads and structured interview questions from a role description. - What it needs: A person who checks for accuracy and bias. - Effort: Low ## Order status and returns - Team: Customer service - What it does: Answers 'where is my order' and starts returns on the website or WhatsApp. - What it needs: A connection to the shop and courier tracking, the returns policy, and a hand-off to staff. - Effort: Medium ## Product recommendations - Team: Sales - What it does: Suggests related products on the site and in emails. - What it needs: A catalogue with good product attributes, and enough traffic to learn from. - Effort: Medium ## Website FAQ assistant - Team: Customer service - What it does: Answers common questions on your website from your own content, with a hand-off to a person. - What it needs: Current FAQs and policies, and a hand-off route. - Effort: Medium ## Stock planning support - Team: Operations - What it does: Flags products likely to sell out or be overstocked, based on sales history. - What it needs: At least a year of clean sales and stock data. - Effort: High
About this tool
How it works and how to read the result.
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See the serviceWhat it does
This list of AI use cases by industry shows practical ways businesses use AI today, filtered by industry and team. Pick one of nine industries, from professional services to construction, and optionally a team such as sales or customer service. Each use case says what it does, what it needs to work, such as clean data, a system connection or a person to review, and how much effort it takes. Quick wins are listed first. You can include uses common to most businesses and export the list as Markdown. No figures or returns are claimed; the value depends on your volumes.
How to use it
- Choose your industry.
- Choose a team, or leave it on All.
- Keep "Include uses common to most businesses" ticked to see email, meetings, FAQs and hiring.
- Read the "Needs" line for each use case and mark the ones you could support today.
- Download the Markdown to discuss with your team.
How to read the result
The default industry, retail and e-commerce, shows 9 use cases with the common ones included, and 5 of them are quick wins. The quick wins include product descriptions and review analysis, which work with off-the-shelf tools and an export of your data.
Order status and returns on WhatsApp is medium effort because it needs a connection to the shop and the courier's tracking, plus a hand-off to staff for anything unusual. Stock planning is high effort because it needs at least a year of clean sales and stock data, and the output feeds buying decisions.
The "Needs" line is the one to read closely. If a use case needs data you do not have, such as a year of clean sales history, fix that first or pick a different use case.
Filter by team to give each manager a short list. In retail, choosing customer service leaves two: order status and returns, and the website FAQ assistant.
We build AI assistants and agents that connect to your systems as part of AI agents. To estimate running costs for a use case, try the AI API cost calculator.
Questions
Frequently asked.
Which AI use case should a business start with?
One that is frequent, low risk and easy to check: drafting replies, summarising documents or answering common questions from approved content. Start where a person can review every output, measure the time it takes today, and run the pilot for a few weeks before moving to anything that acts on its own.
Do these use cases need custom software?
Low-effort ones usually work with off-the-shelf tools. Medium-effort ones connect AI to one or two of your systems, such as a booking tool or CRM, which takes some setup. High-effort ones need a custom build, several systems or sensitive data, and careful testing before staff or customers rely on them.
Are these use cases safe for customer data?
They can be, if you choose tools with suitable data terms, limit what data each one sees, and keep a person in charge of decisions that affect customers. Health, legal and financial data need extra care and often specific approvals. Check your data protection obligations before connecting any tool to customer records.
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