The AI Copilot is one of the most exciting innovations in the customer experience landscape, powering a new age of productivity and efficiency in teams.
It builds on the evolving presence of artificial intelligence and machine learning solutions in the contact center, leveraging the opportunities offered by generative AI and LLMs. Countless innovative vendors have already begun highlighting the opportunities these tools provide.
Microsoft has a version of its Copilot assistant for the Dynamics 365 ecosystem. There's also Microsoft Copilot for Sales, and Microsoft Copilot for Service.
Salesforce is experimenting with a new Copilot solution powered by Einstein. Even Webex is experimenting with innovations in conversational AI tech.
While these AI Copilots may have slightly different features (and names), they’re all designed to augment the modern contact center agent and improve customer interactions. Here’s everything you need to know about the AI Copilot and its impact on the future of CX.
What is an AI Copilot for Customer Experience?
The term “AI Copilot,” or just “Copilot,” used to refer to an AI assistant, was initially coined by Microsoft when unveiling its generative AI assistant for the Microsoft 365 stack. Microsoft chose the name because the solution was designed to support and empower agents, essentially acting as an always-on enterprise assistant.
Today’s AI copilots combine large language models and conversational interfaces to support users in various tasks and decision-making processes. They can understand, analyze, and respond to multiple data types and automate countless tasks.
In the CX or contact center space, the AI Copilot uses innovative AI technology to support customer service, success, and sales agents. These tools can provide context-aware assistance to employees throughout the customer journey, leveraging business data and CRM insights.
They can automatically take notes during calls and conversations, summarize discussions, highlight action points, and even provide intelligent suggestions for improving customer sentiment. Copilots can also help to unify various disparate systems, connecting the data from multiple platforms and tools to offer employees a comprehensive source of guidance.
AI Copilots vs Chatbots vs Virtual Agents: What’s the Difference?
The AI Copilot isn’t the first AI-powered assistant we’ve seen in the contact center. Companies have experimented with chatbots and virtual assistants to help employees with various tasks for years. Chatbots, similar to copilots, combine conversational interfaces with machine learning algorithms and natural language processing capabilities.
They can handle various tasks but are usually designed to support customers through advanced self-service experiences. Chatbots can answer questions, link customers to FAQs, and even provide personalized product recommendations in some cases.
Virtual agents can support consumers and employees with AI, natural language processing, and automation. They often support omnichannel communication and are used to create standard chatbots, voice bots, and interactive voice response systems.
Copilots are an advanced version of both solutions. AI copilots use the latest generative AI technology and large language models to assist with tasks a standard bot or virtual agent couldn’t handle. They can deliver personalized assistance and guidance to teams, learn from user behaviors, and automatically generate content and responses to customer queries.
Typically, AI copilots in the contact center are designed to empower customer service and sales professionals rather than serving customers directly.
How Do AI Copilots Work in the CX Space?
So, how do AI Copilots work? As mentioned above, they’re powered by large language models and generative conversational AI interfaces. Algorithms applied in machine learning, natural language processing, and context understanding enable copilots to operate at an advanced level.
At the same time, through integrations, APIs, and training methods, copilots can be refined and fine-tuned to suit the specific needs of employees in different industries.
Different types of AI Copilots can operate in varying ways. A basic copilot, for instance, will use API calls to LLMs to respond to general inquiries using vast knowledge databases. More advanced copilots, on the other hand, can chain multiple LLMs together and draw data from a company’s existing tools, contact center platforms, CRMs, and databases.
This means some of the most advanced copilots can deliver more contextual responses to requests and learn from business and customer experiences. In virtually every instance, AI Copilots are extremely easy to use. Employees can interact with them using basic text or voice prompts.
These prompts tell the copilot what the agent needs, and it generates a response accordingly. With machine learning and human-in-the-loop feedback, the copilot can be more efficient, accurate, and valuable over time.
The Benefits of AI Copilots in Customer Experience
Generative AI tools have proven extremely useful in various business landscapes. They can help automate mundane tasks, align data systems, and improve team creativity. By 2032, the market for generative AI is expected to reach $191.8 billion!
In the contact center, an AI copilot can help boost team productivity and efficiency, streamline customer interactions, and strengthen brand loyalty.
The right tools can: