In 2025, it feels like there is always a new AI model just around the corner. Generative AI sparked the first big push, opening contact center leaders' eyes to the potential of automation. Agentic AI came to the forefront more recently, going a step further with fully autonomous capabilities and independent action.
While generative AI offers the ability to engage with customers in intuitive, natural language, agentic AI offers proactive and autonomous decision making.
With so much potential, it seems that agentic AI would be taking the CX community by storm. Yet, many contact center leaders are still working to build an understanding of the true impact of this technology. According to CCW Digital research, as few as 15% of contact center executives say they are very familiar with agentic AI and recognize how it differs from other AI.
Here we break down the core features of agentic AI and unpack key ways it can transform contact center operations moving forward.
What is Agentic AI?
Agentic AI uses reasoning to autonomously solve problems. When compared with generative AI, that primarily summarizes and generates text, agentic AI can act independently. It goes beyond just an interaction, it can take action on specific goals, tackle challenges proactively and adapt to changing preferences.
How does it actually do this? Agentic AI is powered by machine learning, natural language processing and automation technologies. It makes decisions on learned behaviors and adapts to customer inputs. As the technology continuously improves, it proactively refines the customer experience over time.
According to Salesforce, “What sets autonomous agents apart from its predecessors is that it can reason not only based on predictions it makes from large datasets, but also based on their ability to perceive their environment and then take autonomous action, and even learn from feedback and adapt.”
This level of reasoning can actually match near-human cognition in many different areas - meaning AI agents can problem solve in dynamic and highly complex environments.
How are Brands Using Agentic AI?
Agentic AI is particularly useful as a customer service tool. AI agents are one of the most popular use cases of agentic AI today. But, what actually is an AI agent? It’s important to understand that AI agents are not just exceptional chatbots that enhance conversations.
AI agents can take on tasks and proactively detect challenges based on predetermined goals. For example, AI agents can track customer emotion in real-time and identify moments where a customer might be frustrated or upset. From there, the AI agent can prompt recommended responses or training for the agent to leverage after the interaction. Alternatively, agentic AI can monitor agent performance and intervene with coaching or relevant content for improvement. These challenges can be flagged by the AI agent and addressed without the need for any human intervention.
AI agents will likely be leveraged across industries as a tool for more proactive and streamlined support. Citi recently shared a report on how the bank intends to use agentic AI to power the ‘Do It For Me’ Economy. In its discussion of the technology, it shared that users will have their own AI agents helping them choose products and execute transactions. It highlighted use cases like personalized offers for adaptive financial advice, custom lending officers, dynamic pricing and tailored insurance policies. It also covered use cases like financial forecasting with live cash flow forecasts and dynamic investment timing strategies or automated premium calculations.
Vibhor Rastogi, Global Head of AI/ML Investments at Citi Ventures shared,“We think the hottest new area of venture investment will be autonomous AI agents, software agents that can simulate human behavior and plan, make decisions, and execute tasks in complex environments without human intervention or supervision. Autonomous AI agents are just emerging from research and development, and as of now, their funding pales in comparison to the funding for GenAI’s core infrastructure.”
The Future Powered By Agentic AI
While Rastogi mentions that funding is currently paling in comparison to GenAI, there is still strong progress being made in the Agentic AI space. Organizations like Talkdesk, Cognigy, Observe.AI and ServiceNow have built agentic AI solutions that feel like the next logical step in innovating the contact center.
As leaders look ahead, it is important to understand how this technology can not only transform operations but shift employee workflows. With 50% of companies stating that they are investing more in AI in 2025, it is a critical time to reassess the future of support. By investing in AI agents, many organizations may need to rethink how agents will interact with customers and what their role might look like.
Taking the time now to truly plan for the future, outline organizational goals and desired outcomes, will keep companies ahead of the curve.
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