Mentioned in 39 AI use cases across 19 industries
A company can build separate scoring models for different kinds of deals, like one model for one region and another for a different business unit, so each model learns from the right examples.
Zendesk turns AI labels on tickets into sorting rules, queues, and dashboards so urgent or specialized cases go to the right people faster.
The retailer used customer shopping history and product details to send each shopper wine suggestions and marketing emails that felt more like advice from a knowledgeable store associate.
AI tells reps what to do next and automates parts of follow-up, helping them stay in touch with prospects and move deals forward faster.
An energy company uses customer data to estimate which households are likely to leave, so it can intervene before they switch providers.
When the sales agent is connected to Salesforce, admins can grant it extra permissions so it can read activities, tasks, events, and custom fields needed to fully research leads and optionally write summaries back.
It lets a team fetch segment rules and status by API, so they can audit which customer groups exist and whether they are active or still processing.
BritBox teaches its AI support agent to sound warm, polite, and locally familiar so customers in different countries feel like the service understands them.
Instead of billing customers from separate spreadsheets and systems, one setup connects contracts, installed equipment, meter readings, and finance so bills are created automatically and correctly.
Developers can build apps that plug deeply into Seismic so teams can add custom features or connect Seismic to internal systems.
The tool studies which kinds of contacts became qualified leads before and then scores new contacts based on how similar they are to those successful contacts.
AI reads incoming support requests and sends each one to the best available agent instead of making teams sort them by hand.
Reckitt uses AI to handle repetitive marketing work like post-campaign analysis and to speed up the creation of new concepts, so teams can spend more time on higher-value decisions.
Instead of building every connection themselves, insurers can pick ready-made connectors from a marketplace to plug into common services faster.
If customer complaints are already logged in a service system, the company can connect that complaint system to quality workflows so complaints automatically feed formal corrective action tracking.
Combine product usage and customer feedback into a health score, then alert customer success when an account starts slipping so the team can intervene early.
AI writes personalized building messages so occupants get clearer guidance about what is happening and what they should do.
Gymshark uses AI to suggest products shoppers are likely to want, helping people find relevant items faster during Black Friday traffic spikes.
Utilities connect Oracle systems so customer, billing, and operations data can move between applications without manual re-entry.
Adobe predicts how likely each customer is to do something, then lets marketers build audience lists using those scores.
When a member contacts Modivcare, the system uses their profile and history to guide them to the right care workflow and help agents resolve issues faster.
After a customer call ends, AI writes the notes and summary for the agent so they spend less time on paperwork.
The platform studies customer usage and account data so energy retailers can tailor prices and offers to what each customer actually needs.
A technician uses one mobile app to see customer details, outage history, manuals, capture photos and signatures, order parts, and update job status instead of using paper and phone calls.
PLDT built one shared customer brain that combines wireless and broadband data so it can talk to each customer with the right offer at the right time.
The system watches when each customer is likely to run out of a medication or wellness product, then sends a reminder email at the right moment with a one-click reorder link.
Ulta asked app shoppers a simple question about eye color, used the answer to suggest matching products, then later sent follow-up messages with products tailored to that preference.
Use AI to plan smarter driving routes so crews make fewer unnecessary trips, saving fuel and cutting emissions.
The utility used SEW’s SmartWX platform to make sure field crews get the right job orders and information faster, so they can fix issues sooner and waste less time.
The system finds which customers are most likely to stop buying, so the company can send them the right offer or message before they leave.
AI drafts help-center procedures and flags weak bot procedures so admins can improve self-service and reduce how often human agents need to take over.
Oracle provides downloadable integration guides so utility teams can see how different cloud systems connect before they deploy or upgrade them.
Instead of crews writing things down later or using separate systems, workers can enter time and substation job details on mobile tools while in the field, making records faster and more accurate.
AI-like optimization software acts like a smart dispatcher that decides which utility crew should do which job and what route they should take, then keeps updating the plan when things change.
A company rolls out AI agents carefully by choosing workflows, connecting systems, setting rules, and measuring results so the AI can act safely in customer service.
It acts like a shared brain for utility data, connecting analytics with billing, customer, meter, asset, and other Oracle utility systems.
Sales teams can jump from a deal record in Clari to the actual Gong call recording, and back again, so they can check what was really said before deciding if a deal is healthy.
A customer can buy business internet in an app while an AI agent checks availability, verifies details, builds the contract, and even suggests an extra service like fleet management.
When an agent ends a messaging session, the follow-up ticket can be treated like email work for routing purposes so it still gets handled in the support workflow.
A script can open a new support ticket in Zendesk automatically instead of someone creating it by hand.