100 AI use cases • Executive briefs • Technical analysis
This is like giving every support rep a super-smart assistant who can instantly read past tickets, policies, and FAQs, then draft helpful replies or answer customers directly in chat or email.
This is like giving every support agent a super‑smart colleague who has read all past tickets, help articles, and policies, and can instantly draft replies or answer questions based on your company’s own data.
This is an overview of all the ways companies can use AI as a ‘super-assistant’ for customer service—answering questions, routing tickets, summarizing conversations, and helping human agents work faster and smarter.
This is like giving every customer a smart digital helper that can chat with them 24/7, answer common questions, and solve simple problems without needing a human agent each time.
This is about using smart software—like chatbots and virtual assistants—as the first line of support for customers, so they can get instant answers 24/7 and human agents only handle the tougher questions.
This is like giving every support agent, chatbot, and help center a smart assistant that instantly looks through all your FAQs, guides, and past answers to suggest the best response for each customer question.
This is like giving every customer a smart, always-on support rep who can instantly answer common questions, help people complete tasks (like tracking orders or resetting passwords), and only bring humans in when needed.
This is like giving your customer support inbox an emotional thermometer. It automatically reads every ticket, figures out if the customer is happy, confused, or angry, and flags what needs urgent attention so your team can respond smarter and faster.
This is like giving your customer support team a smart robot receptionist that can instantly answer common questions, route issues to the right agent, and keep customers updated—without needing a human every time.
This is like giving every call center agent a super-smart copilot that listens to customer conversations in real time, looks up the right information, and suggests what to say or do next so issues get resolved faster and more consistently.
Think of this as a smart listener that reads what your customers write (emails, chats, reviews, tickets) and instantly tells you if they’re happy, confused, or angry—at huge scale and in many languages—without needing a room full of people to read everything.
This is like giving your call center and support team a super-smart digital receptionist that can talk to customers, answer questions, and route issues 24/7 without getting tired.
Think of ServiceNow’s generative AI as putting a smart assistant inside your IT and customer service portal that can read tickets, your knowledge base, and system data, then talk to users, draft replies, summarize issues, and even kick off workflows automatically—without agents or employees doing everything manually.
This is like giving every retail contact center a smart co-pilot: customers get a smarter self-service chatbot that can answer more complex questions, and human agents get real‑time guidance and summaries so they can solve issues faster and more consistently.
This is like giving every call center and support agent a very smart digital co‑pilot that listens to customer conversations in real time, suggests what to say or do next, and automates repetitive steps so issues are resolved faster with fewer errors.
Think of this as a smart traffic cop for customer support: AI reads every incoming ticket, figures out what it’s about, how urgent it is, and who should handle it, then routes and responds faster than a human triage team ever could.
Imagine your support inbox has a super-smart teammate who instantly reads every ticket, understands what the customer is asking, searches all your past tickets and help docs, and then drafts the perfect reply or even solves it automatically—before a human agent has to touch it.
Think of this as an AI co-pilot for genetic testing labs and clinicians: it reads huge DNA files, compares them to medical and genomic knowledge, and highlights which genetic changes are likely to matter for a patient’s disease and treatment options.
This is like giving every customer their own tireless, super-trained support rep who can answer questions, solve common issues, and route complex problems to humans—instantly and at any hour.
Think of this as a supercharged help desk where an AI assistant works alongside your human support team—instantly answering common questions, routing tickets to the right agents, and suggesting replies so agents can resolve issues faster.
This is like giving your customer support team a tireless digital assistant that answers all the routine questions—order status, returns, simple troubleshooting—so human agents only deal with the tricky cases.
This is like giving every call center agent a super-smart sidekick that listens to customer interactions in real time, figures out what the customer is feeling and wants, and then quietly tells the agent the best next thing to say or do.
This is like giving every customer a tireless digital helper that can answer questions, solve common problems, and route issues to the right human—24/7—through chat on your website, app, or messaging channels.
This is a playbook for turning your customer experience into something like a 24/7 super-listener and problem-solver: software that reads what customers say in surveys, chats, emails, and reviews, figures out what they really mean, and then helps your team respond faster and smarter.
This is a guide that shows call centers how to teach software to “listen” to customer conversations, figure out whether people sound happy, angry, or frustrated, and then use that information to improve service and agent performance.
This is like giving your helpdesk inbox a smart assistant that can read every customer message, understand what it’s about, answer common questions instantly, and route tougher issues to the right human agent with all the context pre-filled.
Think of this as a smart email inbox for customer support that can read every message, understand what it’s about, automatically suggest or send replies, and route it to the right person—while making sure privacy rules like GDPR are respected.
This is like giving your customer support inbox a smart assistant that automatically understands, sorts, and drafts replies to tickets so your human agents only handle the tricky parts.
This is like giving every customer a super-trained digital support rep that never sleeps and instantly knows your policies, FAQs, and past tickets, powered by the latest ChatGPT 5.1 model.
Think of an AI helpdesk as a smart, tireless receptionist plus support agent that lives inside your email, chat, and ticket tools. It reads what customers ask, finds the right answers from your knowledge base, drafts replies for agents, and sometimes responds to customers automatically—24/7—so humans only handle the tricky cases.
Think of this as putting an AI ‘air traffic controller’ on top of your customer support systems in the cloud. It quietly watches everything—traffic spikes, slow services, error logs—and automatically tunes the environment so support agents and customers get fast, reliable help 24/7.
Now Assist is like an AI super-assistant built directly into ServiceNow that helps employees and agents answer questions, resolve tickets, and complete workflows much faster by understanding natural language and surfacing the right information or actions automatically.
This is like giving every small or mid-sized company its own 24/7 super-helpful support rep that never sleeps, remembers everything customers asked before, and can instantly look up answers across all your docs, FAQs, and past tickets.
This is like giving your call center or helpdesk a smart ear that listens to what customers say (emails, chats, social posts) and instantly tells you if they’re happy, angry, or worried, using prebuilt AI from cloud providers.
This is like a smart mailroom for customer support: an AI reads every incoming support ticket, understands what it’s about and how urgent it is, then automatically sends it to the right team or queue in Zendesk without a human triaging it first.
Think of this as a smart digital receptionist for your support team. It reads incoming customer issues, asks the right follow‑up questions, fills in ticket details correctly, and routes them to the right place—without needing a human to touch every single request.
Think of this as a smart control tower for a call center. It watches millions of customer interactions, spots what’s working and what’s broken, and then uses AI to help agents answer faster, better, and with less effort even when call volumes spike.
Imagine your customer service as a team where humans handle the tricky, emotional conversations and AI assistants quietly do all the busywork in the background — looking up answers, drafting responses, and routing issues so customers get help faster and agents aren’t overwhelmed.
This is like giving every customer their own smart, always‑on support rep that can instantly answer questions, fix common problems, and pass tricky issues to humans when needed.
Think of this as upgrading from a dumb FAQ bot to a smart service rep that can actually understand what customers mean, look up the right information, and respond in full sentences across channels—without needing a human every time.
This is like giving your company a super‑listener that reads what customers write (emails, chats, reviews, social posts) and instantly tells you if they’re happy, angry, or confused—at large scale and in real time.
This is like having an always-on assistant that reads every customer message, review, or chat and tells you in plain language whether people are happy, angry, or confused – then rolls that up into clear dashboards for your teams.
This is like giving your service desk a superpower that reads the emotional tone of every email, ticket, and chat so you know which customers are getting frustrated before they actually complain or leave.
This is like giving your helpdesk a tool that can instantly read every support ticket and judge how happy or upset the customer is, so managers know where fires are burning before they spread.
This is like a super-smart traffic controller for your customer messages. Every email, chat, or ticket is instantly read by AI, understood, and sent to the right person or team without humans manually sorting the queue.
This is like having a super-smart mailroom clerk for your support team who instantly reads every incoming customer request, understands what it’s about, how urgent it is, and then sends it to exactly the right person or team to handle it best.
This is like giving your shared support inbox a smart assistant that reads every incoming email, understands what the customer wants, creates or updates the right support ticket, and replies or routes it automatically instead of your agents doing it manually.
This is like an intelligent triage nurse for your support inbox. It reads each incoming support ticket, figures out how urgent and important it is, and assigns a priority automatically so your team works on the right things first.
This is like giving your customers a smart digital receptionist that can answer questions, solve common issues, and guide them 24/7 without needing a human agent on the line for every request.
This is like giving every customer service agent (and your IVR/chatbot) a super-smart digital co-pilot that can instantly read knowledge bases, past tickets, and policies to answer customers in natural language across phone, chat, and other channels.
This is like giving your customers and employees a smart, always-on digital concierge that can understand questions in normal language, look up the right information across your systems, and respond instantly on chat, voice, or other channels.
Think of AutoCompose as a smart autocomplete for customer service agents: while they’re typing replies to customers, it suggests full, high‑quality responses so they mostly click, tweak, and send instead of writing from scratch.
Think of this as a smart, always-on receptionist and helpdesk team that can talk to customers by chat, voice, or video, answer most questions instantly, route complex issues to humans, and learn from every interaction to get better over time.
This is like giving every call center and support agent a super-smart digital co-worker that can understand customer issues, look things up across systems, and take actions (like updating an order or issuing a refund) instead of just suggesting responses.
This is like giving your helpdesk inbox a smart assistant that reads every support ticket, figures out what it’s about, suggests or writes the reply, and routes it to the right person—so agents only handle the tricky edge cases.
Think of it as a tireless, super-trained support rep that can instantly read your help docs, past tickets, and policies, then chat with customers in natural language across email, chat, and voice—escalating to humans only when needed.
Think of this as an ultra-fast, always-awake logistics expert that can read emails, orders, shipment data, and policy documents, then speak back to customers and staff in plain language with tailored answers and next steps.
This is like having a 24/7 super-helpful store assistant that lives inside your website or app. It instantly answers questions, tracks orders, helps with returns, and guides shoppers to what they need, without making them wait for a human agent.
This is about using smart digital helpers that can talk to customers like a human support rep—answering questions, solving common issues, and routing complex problems to the right person—24/7, across chat, email, and voice.
This is like giving drug development teams a super‑smart writing assistant that knows clinical trial rules and medical language, so it can help draft and refine trial protocols much faster and with fewer mistakes.
This is like giving your helpdesk inbox a smart assistant that can read each support ticket, understand what the customer needs, draft (or send) the right response, and update your systems, instead of a human manually handling every ticket.
Imagine your customer support inbox staffed by a tireless digital assistant that can instantly read every ticket, understand what customers are asking, suggest or send replies, and route issues to the right human when needed. That’s what an AI ticketing system does for support teams.
This is like giving your customer support inbox a smart assistant that reads every ticket, understands what the customer wants, fills in the right fields, routes it to the right team, and sometimes even drafts the reply—before a human ever looks at it.
Think of ZenML as the plumbing and control room behind any AI assistant that answers your customers’ questions. It doesn’t replace your chatbot; it makes sure the models, data, and workflows behind that chatbot are reliable, testable, and easy to update as you learn from real conversations.
This is a playbook for how libraries can safely and effectively use AI chatbots as virtual librarians—answering questions, guiding patrons, and handling routine requests—without breaking trust, privacy rules, or service standards.
This is like giving every customer message a quick mood check—happy, angry, confused—so your support team knows which issues to jump on first and how to respond in the right tone.
This is like a very smart “mood detector” for text. It reads what customers write in emails, chats, reviews, or social media and automatically figures out whether they’re happy, angry, or worried—and why—so your teams don’t have to read everything manually.
This is about using smart software ‘helpers’ that can read customer messages, understand what they want, and either solve the issue automatically or guide a human agent with the next best step—like giving every support rep an extra pair of expert hands and eyes that never get tired.
This is like giving every customer a smart, always-on support agent that can instantly answer questions and resolve simple issues by reading your existing help docs, tickets, and internal systems.
This is like upgrading your website and support search bar into a smart assistant that understands full sentences, remembers context, and can guide customers through their shopping or support journey instead of just showing a list of links.
This is about using smart chatbots and virtual helpers as the ‘first line’ in customer service, answering common questions automatically so human agents focus on complex issues.
Think of this as a supercharged digital assistant for your support team that can instantly read all past tickets, FAQs, and product docs, then draft accurate replies, suggest next best actions, and handle simple customer questions end‑to‑end without human involvement.
This is like giving every customer their own smart digital helper that can answer questions, solve simple problems, and guide them 24/7 without needing a human on the line every time.
Think of this as upgrading your call center and digital channels from a scripted FAQ robot to a smart, always-on concierge that knows your products, your policies, and each customer’s history—and learns from every interaction.
This is like hiring a very smart language expert (GPT) to read customer messages and decide whether they’re happy, angry, or confused—without having to build a custom model from scratch.
Think of this as a 24/7 digital receptionist that not only answers calls and messages but can also tell when a customer sounds happy, angry, or frustrated, and then responds in a more human, appropriate way or routes them to the right person.
This is about using AI ‘digital bank tellers’ that can chat with customers, answer questions, and help with routine banking tasks 24/7, so human agents only handle the tricky issues.
This is a buyer’s guide that compares many different ‘ChatGPT-like’ tools built specifically to answer customer questions, resolve issues, and deflect support tickets on channels like web chat, email, and messaging apps.
Think of this as a tireless, smart help desk rep that never sleeps. It reads customer questions, looks up the right answers across your documentation and past tickets, and replies instantly—only escalating to humans when things get tricky.
This is like a super-fast digital receptionist for your support inbox that reads every incoming ticket, understands what it’s about, and sends it to the right team or priority queue automatically.
This is like having a smart assistant read all your customer comments, emails, chats, and reviews and tell you, in real time, who is happy, who is frustrated, and exactly what they like or dislike (e.g., “service was slow”, “agent was helpful”).
Think of this as putting a very smart, tireless digital assistant into your customer-service operations so it can read requests, understand what people want, and either respond automatically or prepare the work for your human team.
This is like building a very smart assistant for lung cancer doctors and drug developers that studies huge amounts of scans, lab tests, and treatment histories to spot patterns humans can’t see—who really has cancer, how it’s likely to progress, and which treatment or trial is likely to work best for each patient.
This is the market of tools that act like smart, always‑on support agents—chatbots, voice bots, and assistants that can understand customer questions, pull answers from company systems, and respond instantly across chat, email, or phone.
This is like hiring a team that reads everything your customers say about you online—reviews, emails, social posts—and then gives you a clear, automatic summary of whether people are happy, angry, or neutral and why.
This is like giving your company “emotional radar” for all the messages customers send – emails, chats, social posts, reviews – so software can automatically tell who’s happy, upset, or confused and flag what needs attention.
Think of this as the evolution from simple FAQ chatbots to smart digital service reps that can understand complex questions, look up the right information across systems, and respond in natural language—similar to a well-trained human agent but available 24/7 and infinitely scalable.
This is like giving every customer on your website or app a smart, always-on support rep that can chat, answer questions, and handle simple tasks automatically, instead of making people wait for a human agent.
This is like giving every customer their own smart, tireless service rep who remembers past conversations, can answer common questions instantly, and knows when to pull in a human—so customers don’t have to repeat themselves or wait on hold.
Think of this as a smart, tireless support agent that reads past tickets, FAQs, and documentation, then instantly suggests answers or resolves simple issues so human agents only handle the tricky cases.
Think of ServiceNow’s generative AI as putting a very smart help‑desk brain on top of all your tickets, knowledge articles, forms and workflows. Instead of agents and employees hunting through ServiceNow screens, they can just ask questions in plain English and the system suggests answers, drafts responses, and even kicks off the right workflow automatically.
This is about using ChatGPT-like technology as a supercharged helpdesk agent that can instantly answer customer questions, draft replies for human agents, and automate routine support tasks across chat, email, and other channels.
This is like testing two kinds of "emotion detectors" for customer messages: older rule/ML-based detectors versus newer deep learning/AI models, to see which better understands if customers are happy, angry, or neutral.
This is like giving your IT helpdesk a smart assistant that reads all your tickets, docs, and logs so it can answer routine questions, route issues, and suggest fixes automatically for employees and customers.
Think of this as a Lego-style software system for running clinical trials: instead of rebuilding from scratch each time, you snap together pre‑built, configurable pieces to match each study’s unique needs, and increasingly let AI handle the repetitive work.
This is about building an AI helper that can chat with your customers on your website or support channels, answer common questions automatically, and only escalate to humans when needed.
This is like a super-smart FAQ and support helper that can understand customer questions in normal language and instantly surface the right answer or next step, without needing a human agent.
This is a scientific study that tested what happens when customer website chats are handled by AI instead of humans. Think of it as a controlled A/B test where some customers talk to a human, some to an AI, and the researchers measure who buys more, stays longer, and feels more satisfied.
This is like giving every customer their own helpful support agent who’s available 24/7, answers instantly, and can handle many routine questions at once without getting tired.
This is about using AI as a super-fast digital assistant for your customer service and operations teams, taking over repetitive tasks like answering common questions, routing requests, and summarizing information so people can focus on harder problems.