There’s more to an AI contact centre than chatbots and automated responses. Richard Higginbotham from Netcall explores how AI can support customer interactions, assist agents and improve processes across the contact centre.
For years, automation in the contact centre largely meant predefined IVR menus, routing rules and scripted chatbots.
Today, AI can understand natural language, identify intent, summarise conversations, support agents in real-time and increasingly take approved actions to help resolve customer requests.
That creates an important distinction between simply adding an AI tool and building an AI contact centre where intelligence is embedded throughout the customer journey.
And the same principles apply whether organisations describe this as an AI contact centre or AI call centre: AI is being used to improve how customer interactions are understood, handled and resolved.
So, what does that actually look like?
An AI contact centre uses artificial intelligence alongside contact centre technology and human agents to automate, assist and improve customer interactions across channels such as voice, email, chat, SMS and social media.
But it goes beyond adding AI to individual conversations.
By connecting communication channels with customer data, systems and workflows, AI can help understand what a customer needs, support the person handling their enquiry and, where appropriate, take action to help resolve it.
Depending on the use case, that might mean:
The aim isn’t to remove people from customer service. It’s to use AI where it can reduce effort while making human expertise easier to access when it matters.
Modern contact centre artificial intelligence combines several technologies rather than relying on one form of AI.
Natural language processing helps systems understand written or spoken language. Machine learning can identify patterns within interactions and data.
And generative AI can create summaries and responses, while conversational and agentic AI can support increasingly sophisticated interactions and tasks.
These capabilities can be applied at different stages of the customer journey.
Before an agent becomes involved, AI might identify intent and provide self-service.
During an interaction, it can retrieve information, provide guidance or translate conversations.
Afterwards, it can generate a summary and help analyse interactions for wider trends.
In an AI call centre, these capabilities can work across the customer journey rather than operating as separate, standalone tools. The result is AI embedded across the interaction rather than confined to a chatbot.
An AI call centre or contact centre can use AI in several practical ways.
AI virtual assistants use conversational AI to understand natural language and respond to customer enquiries.
They can work across voice and digital channels, automating suitable routine enquiries and giving customers access to support outside traditional opening hours.
Crucially, automation shouldn’t create a dead end. When the customer needs human support, there should be a clear route to an agent.
Agent assist works alongside the human agent during an interaction.
It can retrieve knowledge, suggest responses and next-best actions and provide real-time guidance so agents spend less time searching for information and can concentrate on the conversation itself.
AI-generated summaries can also reduce the amount of manual administration required once an interaction has ended.
AI can use intent, context, skills and priorities to help determine where an interaction should go through intelligent routing rather than relying solely on rigid menu structures.
That can reduce unnecessary transfers and help customers reach the right agent or service faster.
Customer conversations contain valuable information about what’s working and where problems are occurring.
AI can analyse interactions at scale to identify patterns, sentiment and opportunities for improvement, giving managers a broader view than manually reviewing a small sample of conversations.
AI can help translate interactions, making it easier for agents and customers who speak different languages to communicate.
This can improve accessibility while reducing the need to maintain separate processes for every supported language.
AI autonomous agents take contact centre automation beyond answering questions.
Using agentic AI, they can understand what a customer needs and take approved actions to help complete a request, rather than stopping at providing information.
This creates opportunities to move from the initial conversation through to resolution across connected systems and workflows. Where an enquiry needs human judgement, empathy or support, it can be escalated to an agent with the relevant context.
The value of contact centre AI comes from applying it to genuine sources of customer and employee effort.
AI can answer suitable enquiries immediately, retrieve information faster and remove repetitive administrative steps.
Customers don’t always want to speak to somebody. Often, they simply want an answer or task completed.
AI-powered self-service can provide conversational support across voice and digital channels while maintaining a route to a person when human assistance is needed.
As straightforward requests move to self-service, agents can find themselves dealing with a greater proportion of complex interactions.
AI can provide relevant information and guidance during those conversations, helping people work with better context.
One of the most useful ways to think about contact centre AI is not AI versus people, but AI supporting people.
Imagine an agent handling an unfamiliar enquiry.
Traditionally, they might place the customer on hold, search a knowledge base, check another system, return to the conversation and then manually document everything afterwards.
AI can change that workflow.
Relevant knowledge can be surfaced during the interaction. Guidance can appear based on the context of the enquiry. When the interaction finishes, a summary can be generated automatically.
A unified agent desktop can then bring that information together with customer history and interactions across voice and digital channels rather than requiring the agent to constantly switch systems.
The agent remains responsible for the customer relationship. The technology removes some of the work surrounding it.
AI can automate an increasing range of contact centre tasks, but not every customer interaction should be automated.
Complex complaints, sensitive situations, unusual cases and conversations requiring empathy or judgement are examples where human support remains important.
The more useful question is therefore:
Which parts of the customer journey should AI handle and where should a person become involved?
Good AI contact centre design creates a smooth transition between the two.
A customer shouldn’t have to restart their journey simply because an automated interaction needs to become a human one. Context should move with them so the agent understands what has already happened.
Not all contact centre AI software provides the same capabilities. When evaluating technology, consider whether it can:
It’s also worth looking beyond individual AI features. AI delivers more value when it connects with the systems and workflows required to actually resolve the customer’s request.
You don’t need to automate your entire contact centre at once.
Start with a specific problem. Where are customers waiting unnecessarily? Which enquiries are highly repetitive?
Where do agents spend time searching for information? Which administrative tasks add little value? Where are customers being transferred or having to repeat themselves?
Then identify where AI could remove that friction.
That might mean using AI virtual assistants for routine enquiries, agent assist to support people handling more complex conversations, or autonomous agents to complete suitable tasks across connected systems.
Whether you’re developing an AI contact centre strategy from scratch or adding AI to an existing operation, starting with a defined problem makes it easier to identify where the technology can deliver genuine value.
The most effective AI contact centre isn’t necessarily the one using AI everywhere.
It’s the one using AI appropriately – applying automation where it makes the journey easier while keeping people available where their judgement, expertise and empathy matter most.
This post has been re-published by kind permission of Netcall - view the original article.
Reviewed by: Megan Jones