Welcome to the “We’ve Got a Bot for That” Era—Trends in Conversational AI

Amy Stapleton January 24, 2024

By Amy Stapleton, Senior Analyst, Opus Research


2023 saw a pivotal change in Conversational AI, sparked by OpenAI’s release of ChatGPT, which accelerated Large Language Model (LLM) development. Other companies soon followed, leading to a surge in competing models. This era marks a significant reshaping of customer care and redefines how businesses will engage with their customers and employees.

In 2024, we anticipate the continued expansion of Conversational AI through LLMs and GenAI. Here are some ways we predict these trends will play out:

  • Increased Utilization of LLMs and GenAI in Businesses: After initial trials in 2023, companies now recognize the substantial benefits of LLMs and GenAI and plan to further incorporate them into their customer care systems.
  • More Packaged GenAI Solutions from Vendors: Recognizing that businesses often lack the resources to evaluate different LLM models thoroughly, vendors will offer comprehensive GenAI solutions tailored for specific business needs, simplifying technology adoption.
  • Complex Task Automation with GenAI: Businesses will move beyond using GenAI for simple tasks such as summarizing calls and suggesting responses to customer inquiries, to automating more complex and repetitive business processes, which can result in significant operational savings and return on investment.
  • Heightened Focus on the Cost of GenAI: As the use of advanced LLM models incurs costs, decision makers will increasingly scrutinize the financial implications, weighing the expenses against tangible benefits and improvements.

Turning Attention to Customer Experience and Employee Engagement

Generative AI and LLMs are revolutionizing customer care with their superior natural language understanding (NLU), outperforming older models. These advanced models simplify and speed up the process of setting up chatbots and virtual assistants by eliminating the need for extensive configuration. LLM-based models are effective immediately upon implementation.

These technologies not only save time but also enable more sophisticated, contextually aware customer interactions, closely resembling human conversation. Recognizing this, the industry is rapidly integrating these technologies into customer experience (CX) software to maintain a competitive edge.

However, the challenge for companies and brands lies in effectively applying these innovative AI tools in their operations. Verint provides a rapid and flexible method for businesses to adopt these capabilities.

A New Era of Intelligent Assistance and Bots

Opus Research has long discussed “Intelligent Assistance,” encompassing NLU, machine learning, and data analytics to enhance customer experiences and support agents with AI-driven guidance. This concept materializes when a chatbot successfully resolves a customer inquiry on the first attempt or when an agent accesses a customer’s past interactions and order history during a call.

However, despite advancements, Intelligent Assistance faced limitations, with NLU systems often struggling to fully comprehend customer needs. The advent of LLMs has now dramatically overcome these challenges.

Verint, with its extensive experience in machine learning, swiftly adapted to this shift. Integrating LLMs into their Da Vinci™ AI platform, Verint has enhanced their product offerings with efficient, LLM-powered bots, marking a new phase in Intelligent Assistance for businesses.

Bots to Elevate Human Performance

Dan Bodner, CEO of Verint, has been quoted as saying “Brands need to do more with fewer resources.”

To meet this demand, Verint develops specialized bots designed to streamline processes and augment human work, enhancing productivity without sacrificing quality. Examples of Verint’s GenAI-powered bots include:

  • Voice Containment Bot: Automates responses to routine customer inquiries over the phone and completes actions, such as booking a hotel room.
  • Transfer Bot: Summarizes call progress and provides all necessary information to human agents for a smooth transition.
  • Call Risk Scoring Bot: Prevents fraudsters from reaching a live agent to reduce risks of social engineering and other fraudulent activities
  • Knowledge Suggestion Bot: Rapidly provides agents with pertinent information needed during calls, such as CRM system procedures.
  • Coaching Bot: Offers real-time advice for agents on customer interactions and identifies upselling opportunities.

Companies can start with just one bot, or employ an entire bot workforce, integrating these automated workers seamlessly into their existing contact center platform.

This bot-based consumption model solves a number of issues that are hampering acceptance of GenAI in the enterprise. Businesses are receptive to hiring a bot and managing it like a member of the hybrid workforce. They pay fees commensurate to the value of the tasks the bot performs; thus establishing some certainty to the price that a business is willing to pay for integrating GenAI into their IT infrastructure.

Verint’s new breed of Conversational AI in the enterprise is keeping pace with the rapid changes occurring in technology. Their approach is at last bringing to fruition the promise of Intelligent Assistance that for so long was just beyond reach.