When people think about AI, the conversation often jumps immediately to major transformation.
We think there is a more useful place to start.
Look for work that is repetitive, predictable and consumes time without necessarily requiring human judgement at every step.
Here are five examples, and how we are already using AI to tackle them.
1. Chasing missing information
Meter readings are a perfect example. Instead of somebody repeatedly emailing customers and checking replies, an Agent can manage much of the process and pass exceptions to a person.
What we’ve built:
Our AI Meter Reading Assistant can automatically help manage the process of chasing outstanding meter readings, reducing the amount of manual follow-up required from the team.
2. Reading and sorting incoming communication
An Agent can examine an incoming message, determine what it appears to be about and help direct it towards the appropriate process or person.
What we’ve built:
Our Mail Triage system uses AI to help understand incoming emails and determine where they need to go, helping teams deal with high volumes of communication without manually sorting every message.
3. Checking data before somebody processes it
Is important information missing? Does a value look inconsistent with previous information? Does this record require somebody to review it before proceeding?
AI can help perform that first check.
What we’ve built:
Our AI Meter Reading Assistant can also validate the readings it receives, helping identify information that may need checking before it moves further through the process.
4. Summarising information
Instead of asking somebody to work through a long service history, customer record or series of interactions, an Agent can help prepare the relevant information for review.
What we’ve built:
Our RMM system brings together information from across a customer’s IT environment, helping teams understand what is happening without having to work through every individual piece of information themselves.
5. Preparing the next action
A customer may need a follow-up. A service issue may need attention. A salesperson may need to know about an opportunity.
An Agent can help identify and prepare that next action while leaving the decision with the person responsible.
What we’ve built:
Our RMM system can help turn the information it gathers into actionable information for the team, helping identify issues that require attention and giving people the information they need to decide what happens next.
The point is not that AI should do everything.
It is that your experienced people should not spend their day doing work that software can help them prepare, check and organise.