Gartner recently predicted that agentic AI will automatically resolve 80% of common customer service issues by 2029. Sounds exciting, right? But you may also be asking yourself…’what exactly would this look like?’
The possibilities of agentic AI — a type of AI designed to autonomously execute tasks, make decisions, and take action, all while adapting to evolving conditions in real time — are practically endless. And it’s easy to feel overwhelmed by too many options. In fact, that’s why geniuses like Einstein and Obama prefer to have closets full of the same color clothes!
So rather than letting your imagination run wild with hypothetical scenarios, we’ve decided to highlight a few transformative and totally tangible agentic AI applications used by real CX teams. Because choosing the right agentic AI use case for your CX organization is much more critical than deciding what shirt to wear. Or, at least we think so.
Orchestrate Reward Programs Across Systems
This use case involves an AI agent that can combine knowledge of loyalty program policies with specific customer data from across systems to provide highly personalized service and rewards. It can dynamically automate key decisions and processes to issue credit, offer discounts, upgrade shipping, and more based on a customer’s tenure, rewards card status, loyalty points tier, purchase history, return frequency, etc. Any actions taken or additional data points gathered are recorded in the appropriate systems to help eliminate information silos.
What Makes This Agentic
In addition to offering custom, bi-directional integrations with other CX tools, true agentic AI platforms provide an orchestration layer that guides the conversation flow. The AI agent leverages various Process Guides to dynamically adapt and respond to users’ questions.
These Process Guides provide general instructions for handling particular tasks, while also specifying which tools and knowledge the agent can invoke when appropriate. In this refund scenario, the AI agent can:
- Look up customer information, including order status and membership level
- Access knowledge bases containing return and warranty policies
- Generate a personalized response based on all available context
- Initiate the return process on the customer’s behalf
Rather than relying on predefined, rigid if/then logic, the AI agent determines which actions to take based on conversational context. Every interaction passes through a series of pre- and post-generation guardrails that combine LLMs, business rules, and other validation mechanisms to ensure the exchange is appropriate, on-brand, accurate, and genuinely resolves the customer’s issue.
Diagnosis and Routing via Image Recognition
In this scenario, the agentic AI agent is used to accurately diagnose product issues and route customers to the appropriate human agents for troubleshooting. The AI agent does this by leveraging sophisticated image recognition and combining it with both general product and account-specific information gathered during the conversation and from across other systems.
What Makes This Agentic
Not only does this AI agent use the communication and reasoning power of LLMs to fully comprehend language and users’ inquiries, but it also leverages image processing as part of its Process Guide. It’s similar to how human technicians are taught to know when to ask for an image and look for visual cues to accurately diagnose an issue. The AI agent can then factor this knowledge into the context of the conversation and take the appropriate next step by escalating the customer to the right human agent.
The best part? All the information the AI agent collects over the course of the conversation, including the image and data accessed from other systems, is passed to the human agent at the time of escalation. In addition to receiving an AI-generated summary, the human agent is also able to read back over the full conversation in detail. This seamless handoff ensures the customer never has to repeat themselves, and significantly accelerating time to resolution.
Proactive Service Recovery
Using this agentic AI service enables travel and hospitality companies to detect customer patterns that typically lead to negative experiences based on historical data, and proactively address them to improve guests’ experiences. For example, imagine a guest arrives late, the hotel restaurant is closed, and the pool cabana they want is sold out the next day.
A front desk employee may receive an automated email alert flagging these issues due to the effects they had on previous guests. To proactively improve this customer’s experience and increase the chances they will re-book with the hotel in the future, it’s recommended they bring a bottle of wine and hand-written thank you note up to the guest’s room. Or, the agentic AI service could automatically address these concerns by text messaging a coupon for a free wine bottle to the guest directly.
Example Agentic AI Workflow
Discover More Agentic AI Use Cases
Did you find these agentic AI use case examples insightful? We’re just getting started! Our latest guide is meant to help bring the art of the possible to life by exploring:
- Agentic AI applications across three key industries: Retail (including eCommerce), Travel & Hospitality, and Consumer Services
- Nine increasingly complex use cases, including a review and feedback analysis engine, cross-channel service orchestration, and many more
- Real success stories from a top furniture retailer and other early adopters of agentic AI for CX
