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Artificial intelligence in customer experience has come a long way from the early days of clunky, rule-based chatbots that could only follow rigid scripts.
Today, thanks to advances in natural language processing and machine learning, AI can understand, respond to, and even anticipate customer needs with surprising accuracy.
But thanks to agentic AI, we’re now entering a new era, one defined not just by intelligent responses but also by autonomous action.
Companies are already deploying this AI architecture within their structure to streamline customer support operations and deliver reliable 24/7 support.
In this blog, we’ll break down how agentic AI is redefining customer experience, the benefits for businesses, and what it means for the future of customer support.
What is agentic AI?
Agentic AI is a type of artificial intelligence that can think and act on its own to solve problems, without needing constant human help.
As the AI agent vs chatbot debate continues, agentic AI stands out by being able to:
- Understand what the customer is saying (even if it’s complex or emotional).
- Decide the best way to solve the problem based on past experiences and company rules.
- Act by doing things like issuing refunds, updating accounts, or sending follow-ups, all automatically.
Think of it like a smart assistant that doesn’t just answer questions; it actually gets things done.
Basically, it is AI with agency, hence the term ‘agentic AI.’
How agentic AI in customer support works
Agentic AI is like a super-smart support agent that understands what customers need and takes action to help, without waiting for human instructions. Here’s how it works behind the scenes:
Understands customer intent deeply
Agentic AI doesn’t just scan for keywords. It leverages LLMs alongside natural language understanding (NLU) and sentiment analysis to grasp the full context, tone, and urgency of a customer’s message, whether it’s via live chat, email, or voice.
This allows it to interpret complex queries and emotional cues just like a human agent would.
Determines the best course of action
Once it knows what the issue is, the AI checks things like your order history, company policies, and past customer interactions.
It then decides the best way to solve the problem, just like a skilled support agent would.
Executes functions autonomously
After choosing a solution, this smart agentic system doesn’t wait for approval. It can perform tasks such as issuing a refund and sending customer follow-up messages.
It does all this by connecting with other systems (like payment platforms or help desk ticketing systems) and making the right changes instantly.
Learns and improves over time
Agentic AI continuously learns from interactions, customer feedback, and outcomes. Over time, it becomes more efficient, accurate, and better aligned with your brand’s tone and service goals.
Generally, what sets agentic AI apart from other AI tools is its ability to work autonomously, handle complex tasks, learn from each interaction, and improve over time.
Use case example
If a customer complains about a late delivery, agentic AI can check the shipping status, offer a discount, and arrange a reshipment, all without needing a human to step in.
Why agentic AI matters for customer experience
Using agentic AI in customer service improves both operations and user interactions, enabling systems to act independently and accurately. Here are the common benefits:
Effortless product discovery with natural language understanding
Finding the right product should feel intuitive and very simple. With agentic AI, customers can express their needs in plain language and instantly receive tailored, relevant results.
This capability eliminates friction, saves time, and creates a personalized shopping experience that makes customers feel understood and valued. It’s the kind of convenience that keeps them coming back.
Fast support with smart human handoff
A great customer service experience is generally tied to speed, reliability, and quality. Agentic AI handles routine tasks instantly and escalates only the most complex cases, like “I need to transfer multiple subscriptions to a new account,” to the right human agent.
This balanced human-AI partnership ensures seamless handoffs, optimizes workflows, and delivers fast, personalized support that drives customer satisfaction.
Strategic intelligence that fuels growth
Agentic AI continuously learns from every interaction to build a unified understanding of customer behavior, enabling businesses to anticipate needs and deliver personalized experiences at scale.
It also provides real-time visibility into customer sentiment and operational performance, helping teams refine strategies and uncover growth opportunities.
Empathetic support that builds trust
Empathy transforms customer service by turning moments of friction into opportunities for connection and trust.
Agentic AI draws on rich, contextual insights from every interaction to deliver emotionally intelligent support, interpreting tone, recalling past conversations, and responding with genuine care.
The result is less frustration, deeper engagement, and stronger, long-term customer relationships.
Real-world applications of agentic AI in customer experience (CX)
A report by Cisco has predicted that by 2028, 68% of customer service interactions will be handled by agentic AI.
This could mark the largest transformation in customer support since the internet era.
Here’s how agentic AI transforms customer experience:
Resolving order issues in e-commerce
Order delays are among the most common and frustrating customer pain points in online shopping. Traditionally, resolving the order issues is a manual, time-consuming process that can take hours or even days.
However, with agentic AI, this entire process becomes seamless and instant. When a shipment is delayed, the autonomous AI easily:
- Detects the delay in real-time.
- Verifies inventory availability.
- Notifies the customer with a personalized message.
- Offers a discount or store credit as compensation (if applicable).
- Initiates a reshipment request.
- Updates backend systems to reflect the change.
All of this happens in under a minute, without human intervention. This leads to a frictionless agentic experience that turns a potential complaint into a moment of delight.
Real-life example
VTEX, a global enterprise e-commerce platform, has embedded agentic AI as an autonomous operational layer across its customer service ecosystem. It handles various issues such as order status updates, returns, catalog clarifications, and account modifications across multiple channels with minimal human input.
Handling payment failures in banking and finance
In banking and fintech, failed payments lead to frustration, service disruptions, and customer churn. Too often, legacy systems only send an alert, leaving customers to fix the problem themselves.
Agentic AI changes this by acting autonomously and intelligently when a payment fails.
Instead of just alerting customers, it:
- Retrieves transactions using updated card details (with consent).
- Switches to preferred alternative payment methods based on user history.
- Adjusts billing dates dynamically to match customer cash flow patterns.
Real-life example
EXL’s financial services clients use its agentic AI orchestration platform to automate payments and customer‑service workflows with domain‑specific LLMs.
Streamlining appointment scheduling in healthcare
In various healthcare institutions, scheduling appointments can be really frustrating. Patients have to endure long hold times, staff struggle to manage their calendars, and rescheduling often turns into a logistical nightmare.
Agentic AI revolutionizes this process by acting as an intelligent, always-on scheduling assistant, streamlining operations and enhancing the patient experience. It is able to:
- Scans real-time calendars and patient preferences (e.g., only mornings).
- Propose optimal slots, balancing clinician availability, urgency, and travel time.
- Prevents no-shows with adaptive reminders (SMS/email/voice) based on patient behavior.
- Self-corrects conflicts by automatically rescheduling around emergencies or delays.
- Syncs seamlessly with EHRs, Outlook, and patient apps, ensuring no double-booking disasters.
Real-life example
Air AI, an agentic AI platform, runs human‑like calls and takes actions across more than 5,000 apps (e.g., calendars/CRMs) to book, reschedule, and log appointments, all done proactively.
Enhancing multilingual support in IT services
For the global tech industry, delivering consistent, high-quality support across diverse languages and regions is a significant challenge.
Fragmented systems in IT, reliance on multilingual agents, and varying cultural expectations often lead to inconsistent experiences and delayed resolutions.
Agentic AI for customer engagement bridges this gap by offering real-time translation and cultural context awareness, eliminating the need for multilingual staff while ensuring a seamless, localized agentic experience for users worldwide.
Real-life example
Siemens, a tech company, deployed Moveworks’ multilingual AI inside Microsoft Teams to resolve IT issues instantly, trigger workflows, and even proactively detect and fix problems before tickets are raised based on deep regional awareness.
This unified multilingual experience replaced fragmented portals and reduced resolution times dramatically.
Automating returns and refunds in retail
Returns and refunds are a necessary part of retail, but they don’t have to be painful. Slow refunds, confusing return labels, and denied claims (especially in categories like apparel) drive customers away.
In fact, 55% of online shoppers say they won’t buy again from a retailer that’s slow to refund.
Agentic AI for customer engagement flips this costly pain point into a competitive edge by automating the entire returns process seamlessly. Here’s how:
- Instant return approvals
- Swift refund or credit processing
- Effortless return logistics
- Real-time system updates
Real-life example
Klarna, a Swedish-based financial services company, uses an agentic AI tool that handles the majority of support flows end‑to‑end.
This includes refunds, returns, payment‑related issues, cancellations, disputes, and invoice inaccuracies in more than 35 languages. Tickets are completed in less than 2 minutes on average, compared to the previous average of 11 minutes.
Challenges of agentic AI in customer experience
Of course, it’s not all smooth sailing. Agentic AI brings challenges we can’t ignore. Below are some of the drawbacks that come with it and how you can solve them:
Lack of AI-human balance
Challenge: While powerful, agentic AI systems can disrupt the balance between human and machine decision-making by acting autonomously without sufficient human oversight. This can lead to over-reliance, reduced accountability, and misaligned goals.
Solution: Keep humans in the loop, design transparent and value-aligned AI, and set clear boundaries for AI autonomy. These measures help ensure AI supports human agency rather than replacing it.
Difficulty maintaining a seamless CX at scale
Challenge: While agentic AI offers autonomy and speed, ensuring that every interaction, regardless of channel, context, or complexity, remains accurate, timely, and reflective of brand values is increasingly difficult as systems scale.
Solution: Organizations should implement a centralized experience layer, real-time monitoring, and cross-channel synchronization to maintain brand alignment and accuracy. Additionally, integrating contextual memory, human oversight, and governance frameworks enables adaptive learning and trust across all customer touchpoints.
Data privacy and security challenges
Challenge: Agentic AI often operates with high levels of autonomy, accessing, processing, and sharing sensitive data without direct human oversight, raising serious risks of unauthorized data exposure, misuse, or breaches.
Solution: Build your systems with privacy-by-design principles, ensure GDPR, CCPA, HIPAA compliance, and use encryption, access controls, and an audit trail.
Ethical concerns
Challenge: When agentic AI systems make biased decisions, operate without transparency, or mishandle sensitive customer data, they can autonomously reinforce discrimination and unfair treatment. This not only compromises customer trust but also exposes organizations to legal and reputational risks.
Solution: Implement a robust AI governance framework that enforces fairness, transparency, and privacy compliance. This includes bias audits, explainability mechanisms, strict data protection measures, and oversight by dedicated ethics committees.
Embracing the agentic AI revolution for the best CX
Customer experience is entering a new agentic era, ushering in the next frontier of customer service evolution.
By combining autonomous decision-making, instant problem-solving, and personalized support, businesses can deliver faster, smarter, and more satisfying customer experiences while improving efficiency across the board.
BoldDesk is at the forefront of this agentic revolution. Built for the next generation of autonomous customer support, BoldDesk uses intelligent automation to streamline repetitive tasks, learn from every interaction, and proactively address customer needs.
Consequently, businesses can achieve:
- 70% of customer interactions resolved without human handoff
- Faster average resolution times
- Fewer escalations to human agents
- 24/7 availability with zero downtime
Ready to upgrade your customer experience? Contact our support team for a personalized consultation and discover how BoldDesk can transform the way you serve your customers.
Kindly share your thoughts about this topic in the comments section below.
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Frequently Asked Questions
Agentic AI in customer service acts independently to solve problems, offer help, and personalize support. It can handle tasks like answering questions, resolving issues, and recommending products without constant human input.
Agentic AI autonomously plans, makes decisions, and executes actions to achieve specific customer service goals, while generative AI focuses primarily on creating new content such as text, images, or speech based on input prompts.
Basically, an agentic AI example like BoldDesk combines generative capabilities with autonomous decision-making and action execution.
Training involves combining large language models with reinforcement learning, goal-based simulations, and continuous real-world feedback to develop autonomous decision-making capabilities.
It requires integration with business tools, structured data access, and human oversight to refine planning, reasoning, and action execution in customer experience environments through iterative improvement cycles.
BoldDesk is one of the top help desk platforms delivering specialized AI agents for customer service across specific domains. Additionally, it allows users create fully customized AI agents tailored to their unique workflows, brand voice, and operational needs.
AI models, particularly Large Language Models (LLMs) like GPT-5 that are fine-tuned with domain-specific data, power modern customer service tools. These models enable AI agents, virtual agents, and assistive systems to deliver intelligent, responsive, and context-aware support experiences.
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