Every support team, whether a customer help desk, an IT service desk, or a government contact center, faces the same problem at scale. Cases arrive faster than people can read them. Someone has to decide what each one is about, how urgent it is, and who handles it. Mistakes send cases to the wrong queue, urgent ones wait behind routine ones, and the patterns hidden in thousands of cases go unnoticed.

AI is now good at exactly this kind of work: reading a message, understanding it, and putting a structure on it. Here’s how to put it to work, first on each case as it arrives, then on all of them together.

Part 1: Classify and route every case

Decide what classification is for

Start with the purpose, because it shapes everything else:

  • Routing: sending each case to the right team or person, based on the topic, the product or service, or the expertise it needs.
  • Prioritization: making sure urgent cases are handled first and routine ones follow.
  • Reporting: tracking what people contact you about, so recurring issues show up.

Define the criteria

Then decide what the AI labels each case with. The most useful criteria are usually:

  • Type: a question, a problem, a request, or feedback.
  • Product, service, or program: what the case is about.
  • Area: the specific part involved, such as sign-in, payments, or an application form.
  • Urgency: an outage or a security issue needs a response now; a general question doesn’t.
  • Sentiment: a frustrated customer or resident may need attention sooner than the topic alone suggests.

Write the criteria down with clear definitions and examples. The AI follows them exactly as written, so precise criteria lead to precise classification.

Classify at the right moments

On Plant an App, classification runs as a step in a workflow. The AI reads the case and returns structured fields, which the workflow saves and acts on:

  • When a case arrives, through a form, an email inbox, an API, or a connection to your help desk, a workflow starts within seconds and labels it with type, area, and urgency.
  • As the conversation develops, the workflow runs again on new messages, so urgency and routing can change when the case does.
  • When a case is resolved, a final classification records how it was handled (for example, whether it needed escalation), which makes reporting far more useful.

Route and act

Once a case is classified, the workflow acts on it: it assigns the case to the right queue, raises its priority, alerts a supervisor about a security issue, or answers a simple question directly. The rules are yours, and they change as often as your teams do.

You choose the AI provider (OpenAI, Azure OpenAI, Amazon Bedrock, or Google Vertex AI) and use your own keys.

Part 2: Learn from all your cases

Classifying each case well also builds something bigger: a structured record of everything people contact you about. Here’s how to turn it into decisions, in seven steps.

  1. Bring cases together. Cases often live in several places: a help desk, a CRM, email, spreadsheets. Connect them through their APIs or databases, or import spreadsheets, so analysis covers all of them.
  2. Define what you want to learn. Choose the insights that matter for your goals: the most common issues, the slowest to resolve, the ones that cause the most frustration.
  3. Structure every case. Use the classification from Part 1 to give every case, including past ones, consistent fields that can be counted and compared.
  4. Make it visible. Show the results in dashboards, or send them to the BI tool your organization already uses.
  5. Act on the pain points. Share recurring issues with the teams that can fix them at the source: the product team, the program owner, the people who wrote the confusing form.
  6. Automate the follow-up. Set alerts when a type of issue spikes, and route recurring problems, such as defect reports, straight to the team that owns them.
  7. Review the criteria regularly. What people contact you about changes. Revisit the criteria with the teams who use the results, and update them.

Common mistakes

  • Vague criteria. If the definitions are unclear, the classification will be too.
  • Looking only backward. Reports on last quarter are useful; alerts on what’s happening today are more useful.
  • Insights nobody acts on. Every report needs an owner and a next step.
  • Teams left out. The people handling cases need to know what’s being measured, and why.

The result

Cases reach the right people faster, urgent ones stop waiting behind routine ones, and the organization finally sees what thousands of conversations have been telling it. And because it all runs on the same platform as the rest of your systems, the process can keep changing as fast as the cases do.