The rise of generative AI solutions, such as ChatGPT, has had a profound impact on virtually every business environment. This year, companies from all industries have begun rapidly adopting generative AI tools for everything from creating content to improving collaboration.
Currently, reports show that the market for generative AI is expected to reach a value of $667.96 billion by 2030, and the contact center is one of the biggest landscapes driving this growth.
“AI has hit the mainstream, thanks to significant breakthroughs like ChatGPT, Stable Diffusion, and DALLE-2. Consumers are already starting to expect AI to be integrated in nearly every product—and AI will be a critical component to any company’s product roadmap moving forward,” says Dylan Fox, Founder and CEO at AssemblyAI.
With generative AI solutions, companies can develop more advanced self-service experiences via creative and intuitive chatbots. They can empower workers with amazing virtual assistants, and even process and synergize business data more effectively.
But how does generative AI impact the growing world of conversational intelligence and analytics in the contact center space? Here are some of the key use cases companies can explore.
The Benefits of Generative AI in the Contact Center
Generative AI and conversational AI tools are beginning to work together in the customer experience landscape, empowering businesses to produce not only more valuable chatbots and virtual assistants, but also more engaged, productive teams.
Around 90% of contact centers say they handle calls faster and more efficiently after implementing cutting-edge AI tools. What’s more, generative AI solutions ensure companies can deliver more personalized, relevant experiences to consumers across multiple channels.
In the broader contact center space, generative AI can:
- Improve productivity: Generative AI solutions can automate repetitive tasks, such as summarizing text or collecting insights from consumers, giving agents more time to focus on delivering exceptional support and guidance.
- Enhance customer experience: Gen AI tools and conversational AI solutions can empower businesses to deliver intuitive self-service experiences, and more personalized interactions. They can also offer valuable insights into the customer journey, and consumer needs.
- Upgrade business insights: Generative AI solutions are excellent for collecting insights into brand strength, satisfaction rates, churn rates, and risks. Some solutions can even assist with market research and competitive analysis.
Use Cases for Generative AI in Conversational Analytics
Conversational analytics tools have become an essential component of the customer experience space in recent years. These solutions leverage natural language processing and understanding technologies, alongside AI and machine learning to assist businesses in unlocking valuable insights.
When combined with generative AI, conversational analysis tools can support a variety of use cases, five of the most significant opportunities include:
1. Automating Analysis to Improve Productivity
One of the biggest benefits of generative AI in the contact center is its ability to support employees in rapidly automating tasks, without the need for complex coding and workflow building. Generative AI can complete tasks with nothing but natural language input from team members.
This means employees can rapidly ask tools to take notes from meetings, upload information to a database, source information from a knowledgebase, and more. AI algorithms can use the data gathered from conversational analytics to create optimized schedules for teams, and provide step-by-step coaching throughout customer calls.
Some companies, such as AssemblyAI, even offer organizations access to production-ready AI models, helping businesses more easily combine conversational and generative AI into tools that can immediately help teams reduce manual tasks, and automate the analysis of crucial conversations.
2. Collecting Detailed Information from Transcripts
While many conversational analytics tools can automatically transcribe conversations for compliance, training, and business insights, not all solutions make it easy to assess transcriptions. If companies manage hundreds of calls per day, sorting through transcriptions to find trends and patterns can become a time-consuming and complex process.
