AI agents for customer engagement : Enhance your customer experience

Customer engagement is no longer about sending emails or replying to tickets — it’s about creating ongoing, intelligent conversations that adapt to every customer’s context and intent.

In 2025, this evolution is being powered by agentic AI a new generation of AI agents capable of reasoning, planning, and acting autonomously to deliver instant, personalized experiences at scale.

Unlike traditional chatbots that follow fixed scripts, agentic AI agents can understand customer needs, trigger workflows, and resolve tasks end-to-end whether that’s refunding an order, updating an account, or booking a meeting. They bridge the gap between automation and empathy, ensuring that every digital touchpoint feels human, proactive, and on-brand.

Recent CX studies show that over 70% of support and engagement teams are adopting AI agents to automate repetitive queries, increase retention, and unlock 24/7 availability all while improving satisfaction scores. As brands move beyond rule-based automation, AI agents are emerging as the backbone of modern customer engagement strategies.

In this guide, we’ll explore what customer engagement really means, how agentic AI agents work, key benefits and risks, real-world use cases, and best practices to help you deploy them effectively with pagergpt.

In a fundamental sense, customer engagement refers to providing every type of support and interaction that helps meet customer needs through meaningful, consistent communication. It’s about creating two-way relationships where customers actively participate and emotionally connect with your brand — across every digital touchpoint.

Customer engagement prioritizes active participation, personalization, and emotional bonding. Successful brands design customer engagement strategies that cover every channel — from social media and ecommerce platforms to websites, chatbots, and knowledge bases — anywhere customers expect instant, helpful interactions.

Example of customer engagement in action

Imagine a shopper visits your ecommerce site to buy a product that’s out of stock. Instead of losing the opportunity, your AI agent instantly detects intent and offers options — sending a restock alert, recommending similar products, or scheduling a notification via WhatsApp or email. This kind of AI-driven engagement keeps the conversation alive, builds trust, and increases the likelihood of conversion when the item is available again.

Why AI agents are redefining customer engagement

Modern AI agents elevate engagement beyond traditional support. They:

• Understand intent in real time and offer contextual replies.

• Automate repetitive conversations while maintaining a human-like tone.

• Proactively assist customers across channels like chat, email, and WhatsApp.

• Scale engagement 24/7 without increasing operational cost.

By combining agentic AI reasoning with brand-specific training, AI agents make engagement more personalized, predictive, and proactive — turning every interaction into an opportunity to strengthen customer relationships.

Fostering meaningful interactions with the help of AI agents for customer engagement builds loyalty, reduces churn, and opens new revenue streams — proving that engagement is not about closing tickets, but about building long-term connections that grow your brand.

In a very fundamental way, providing every type of support to meet customer needs through meaningful interactions can be referred to as customer engagement. 

Customer engagement prioritizes active participation and emotional bonding with the brand. It is apparent to promote healthy customer engagement tactics across all touchpoints, from social media platforms to ecommerce sites and business sites to knowledge bases and anywhere where your customers are.

There are a lot of advancements in customer service. Only a handful of businesses seem to take advantage. This is why most companies have yet to unlock the full potential of AI agents for customer engagement. McKinsey’s 2025 workplace AI report indicates that only 1% have reached AI maturity. This means that many businesses are in the early stage of adoption only and not fully utilizing AI agents. For customer support, businesses follow the old-school methods, which are inefficient and error-prone. 

Traditional tools work in silo and lack integration:

Do you deny that your businesses use only one integrated tool for communication? It is not that your customer support work in silo. Many companies use emails, CRM, Chatbots, and social media platforms for customer engagement. Built on legacy systems, these tools don’t integrate and are restrictive to a unified experience. 

Slow and reactive services: 

Fragmented systems don’t provide a single source of truth for your customer support agents. Without any context of previous user issues, traditional tools cannot help much. Customer service representatives also lack real-time context to provide a response, which is unfortunately reactive, prompting customers to return to the service desk again.  

Overworked teams: 

Your agents are busy handling repetitive and mundane tasks, leading to errors in delivering responses. Backlogs pile up, forcing teams to stretch hours. Customer support teams become exhausted and fatigued, which is a significant reason for agent attrition. 

AI agents unify customer interactions, automate repetitive tasks, and deliver real-time, personalized engagementhelping businesses move from manual support to seamless, end-to-end automation.

According to Salesforce, 82% of CS representatives say customers want more than they used to. There is also a rise in workloads for service desk agents, given the volume of changing customer demands and the monotonous nature of requests. 

Traditional customer engagement methods, including non-agentic AI systems, fall short of the tools to meet the growing challenges. Enter AI agents for customer engagement. 

AI-driven customer engagement, powered by Agentic AI automation, mimics human-level agency to make independent decisions at every step of complex workflows and solve problems. 

Trained on massive data resources or LLMs and designed to process NLP and NLG, AI agents can instantly provide answers to customer queries and escalate them to human agents when needed to minimize MTTR and boost customer experience efficiently.  

The ability to learn over time by observing ongoing customer interactions, past history, and changing patterns in customer behavior enables AI agents to easily self-train and adapt to new conditions to solve customer problems at scale. 

AI customer engagement is the way forward to shape customer support. With AI-powered customer support, you can transform how customer problems are solved, provide more strategic ways for service desk agents to nurture their creative side, and provide more quality support.

AI agents can reason, memorize instances from one day to the next, and analyze the intent and context of a human query before surfacing a meaningful answer. This ability gives it human-level agency to make independent decisions for multi-step or multi-turn queries. AI agents can ask questions if needed. To boost customer engagement, AI agents can offer proper guidance and resolve their tickets by providing personalized answers.

For example, call it a travel AI agent. Connected to external business systems and contextual data resources, the travel AI agent can help a family plan a trip. Based on existing user preferences, the AI agent can create an itinerary, map routes, recommend hotels, and also help with booking rooms—all without any intervention from a human agent

AI in customer engagement unlocks massive potential for unlimited ways to help customers find answers and autonomously solve their problems. On the other hand, traditional methods are limited, and they don’t help scale support. Beyond the fundamental differences, AI agents for customer engagement outperform traditional methods in many quarters. 

A quick view into traditional non-agentic systems vs. AI agents for customer engagement: 

AI agents have massively taken over generative AI and are being viewed as an essential AI tool to enhance customer engagement. From crypto trading to seat reservation, AI agents unlock exceptional abilities to accomplish many use cases and help with customer engagement. According to McKinsey, AI-driven customer engagement can boost customer retention up to 40%, which is highly efficient in increasing sales and revenue growth. Here are various use cases of AI agents that boost customer engagement. 

eCommerce product assistant: 

What is your ecommerce business type—apparel, cosmetics, books, gardening tools, and anything? Your customers can have multiple questions about the product, its variety, price, suitable recommendations, etc. AI agents can assist your customers. They can read and analyze customer preferences and recommend the best product tailored to their needs. For example, if a customer needs tools for their small roof garden, the AI agent can recommend the most suitable tools for them. 

Event and booking concierge AI agent:

In travel, hospitality, and event domains, AI agents can maintain processes independently end-to-end. Whether booking tickets, uncovering the agenda of an event, or asking for details about availability, AI agents can guide you properly without any human assistance. You can accurately provide answers on pricing, offers, and discounts, and you can also help with rescheduling and follow-up communications. 

Customer support and FAQ AI agent: 

Your customers can come and ask common questions related to your product or service. By integrating with your business-related resources or intranet, AI agents can easily guide customers to find accurate answers and solve their queries. When critical questions arise, AI agents are designed to escalate them to the right person to handle them efficiently. 

eCommerce and retail customer success:

AI for customer engagement can play a pivotal role in boosting customer loyalty. AI agents can assist with customer onboarding onto your product platform, answer FAQs, facilitate order management, exchanges and refunds, and discover products, to name a few. Also, you can have AI agents capture customer details to let you create powerful marketing initiatives and build prospects. 

Finance and banking AI agents: 

Financial services, especially with banking operations, involve multiple customer engagement activities. If not done on time, your customers can face transaction-related disruptions. AI agents accomplish tasks such as KYC, opening/closing accounts, loan applications, finding ATM, etc. Your customers would be more engaged because AI agents deliver real-time, contextual, personalized recommendations and insights. 

Telecommunication AI agents: 

Customers of telecommunication services can have numerous queries related to their billing, service disruptions, poor connectivity, etc. Instead of waiting for human agents to solve their problems, AI agents alleviate hurdles efficiently. These agents can solve common issues, help them pay bills, assist with refunds, and get new connections among many without seeking human help. 

The advantage of LLMs and advancements in AI helps you use AI agents for any use cases for any business functions. You can customize workflows to manage operations across airlines, education, automotive, insurance, and anything you name. 

AI agents bring excellent promise to the customer support area. They make handling customer service easy and flexible, engaging customers with all the necessary information and consistent assistance to solve their problems. There are several ways in which AI agents drive an AI-driven customer experience on a grand scale. 

24/7 availability 

According to an article by Inc., 51% of customers expect their customer service to be available 24/7. AI agents are driving this expectation to the fullest potential. By offering guided assistance through FAQs and LLM-grounded company knowledge, AI agents can solve multi-step problems and help accomplish various tasks independently. It makes it easy to provide support 24/7 without having to rely on human agents. 

Instant responses 

AI agents have transformed how customer support automates interactions and problem-solving. Not just predefined questions, but any unique questions can be answered instantly using AI agent-driven customer support. Service desk agents also harness the effectiveness of agentic automation to retrieve instant context of a user problem and quickly address customer issues. 

Scalability 

Unlike traditional customer engagement, AI agentic-led customer support can easily adapt to the growing volume of tickets, reduce backlogs, solve customer issues steadily, and become available to handle more critical queries.  

Cost efficiency 

In a study, Gartner predicts that Agentic AI will autonomously resolve 80% of repetitive or common customer support queries without human intervention, leading to a 30% operational cost reduction. 

Continuous customer experience

AI agents are designed to unleash multifaceted abilities that can help customer support provide answers at any time of the day, facilitate smart escalations for complex queries, interact in the familiar language of a user, and ask follow-up questions to provide a continuous customer experience without any friction. 

Omnichannel support 

AI agents can sync with any business systems to provide continuous customer service. You can assist your customers across Slack, MS Teams, WhatsApp, Facebook Messenger, Instagram, Website, Intranet, and Knowledge base. 

Hyper-personalization

Based on previous interaction data, AI agents can efficiently analyze user preferences and personalize requests. For example, if a user wants to buy a running shoes, AI agents can suggest shorts, a t-shirt, and other necessary materials. 

Improved customer retention 

AI agents are good at harnessing customer interaction data and analyzing it to build a robust sales funnel. For example, AI agents can automatically send reminders and special offers tailored to a buyer’s needs. 

Reduced human errors 

With no more repetitive tasks, there is less probability of errors that otherwise occur due to the monotony and lack of attention. AI agents help boost productivity and gain efficiency with multi-turn complex tasks. 

Lean team 

SBMs can work with a lean team to help their customers. Yes, AI agents make it possible. AI can provide relevant answers to repetitive customer queries and free up support agents to focus on other strategic operations. 

AI in customer engagement changes how it works. It shows much promise and provides a massive scope for a large-scale adoption. Gartner also predicts that 25% of customer service operations will rely on AI agents by 2027. Harnessing this new technology opens up opportunities for growth and an elevated experience. 

Finding AI agent success requires strategic implementation. Just harnessing the tool doesn’t materialize your plan; instead, it needs concrete action.  The best practices include, 

Identifying pain points in your customer engagement workflows:  

Know where your customer's engagement workflows fail to serve your customers. Are there response delays, inconsistent responses, or other factors? Identify these pain points and design your workflows. 

Focusing on hybrid support 

AI can’t scale alone. Build synergy between AI and humans for your AI-agentic-led customer engagement. It helps you tackle repetitive queries while managing complex queries with human support. 

Integrating AI agents with enterprise-grade systems 

AI agents are more productive and efficient when they are deeply integrated into business systems. They can talk with the systems, fetch relevant data to simplify interactions, and solve problems for administrative operations. Besides, AI agents can resolve common customer queries at scale and help boost customer experience. 

Monitoring KPIs for performance enhancements 

Monitoring the AI agents' performance regularly is key to keeping your AI-based customer engagement effective and successful. Finetuning AI agents with accurate knowledge bases, company data, etc, can help improve response delivery and reduce latency. Another effective idea is to ask for user feedback. It enables you to improve AI agents’ performance. 

Upskilling support agents 

Helping your service agents work alongside AI agents can boost productivity. With AI agents accomplishing every repetitive task at speed, human agents can learn ways to handle AI tools and utilize AI insights to improve customer interactions.

Implementing AI agents effectively requires a clear strategy, strong data foundation, and continuous optimization. Follow these best practices to ensure seamless deployment and maximum customer impact.

Define clear goals and use cases

Start by identifying which customer interactions your AI agents will handle — such as FAQs, order tracking, or onboarding. Clear objectives help align automation with measurable business outcomes.

Train with high-quality, relevant data

Use accurate and up-to-date customer data, FAQs, and knowledge-base content to train your AI agents. Quality training ensures context-aware, brand-consistent responses.

Integrate with your existing systems

Connect AI agents with CRMs, helpdesks, and communication channels. Integration ensures unified context, smooth data flow, and consistent engagement across touchpoints.

Monitor performance and analytics

Track metrics like resolution time, deflection rate, and CSAT to measure effectiveness. Use insights from analytics dashboards to fine-tune behavior and improve response accuracy.

Balance automation with human touch

Set clear escalation paths to live agents for complex or sensitive queries. A seamless AI-to-human handoff ensures empathy and builds customer trust.

Ensure security and compliance

Implement GDPR and SOC-2 compliant workflows to protect customer data. Secure integrations and access controls help maintain privacy and transparency.

Continuously update and optimize

Regularly retrain AI agents using new data, customer feedback, and performance results. Continuous improvement keeps interactions accurate, relevant, and aligned with evolving business needs.

pagergpt is a powerful customer engagement platform to enable businesses to manage all-encompassing support needs and increase CSAT and boost growth for businesses. pagergpt harnesses the best LLM models to unleash knowledge discovery and customer engagement with loads of AI tools. 

No-code setup: pagergpt’s AI agent studio offers AI tools to create out-of-the-box agents and sub-agents without writing a single code. IT helps you build customer engagement bots and handle multi-turn complex workflows seamlessly. 

Support on autopilot: pagergpt’s AI agents are trained with multiple datapoints to translate into a powerful self-service that helps autopilot your support. Your customers can harness information and solve their problems independently. 

Smart escalation: For complex support that needs human assistance, pagergpt facilitates smart escalation instantly to help resolve the problems at scale. 

AI copilot: Your customer support agents can use AI copilot for every activity they perform to address an issue. AI copilot can help them fetch the real-time context of a user query, summarize a note, translate a message, and provide help, making solving customer queries seamless and effortless.  

Shared live inbox: Your agents can collaborate over a customer query, share information, use mentions for immediate help with resources, and leverage instant notifications to speed up the resolution rates of tickets. 

Lead capture: You can use pagergpt’s AI customer support agent to build excellent client prospects. pagergpt can be harnessed as a lead capture tool, driving thriving customer success. 

Multichannel support: AI agents built what pagergpt can be synced across your business channels where your customers stay. You can provide help across MS Teams, Slack, WhatsApp, websites, knowledge bases, and anywhere you like. 

Multi-lingual AI support: pagergpt never lets you stop for an unfamiliar language your support doesn’t understand. You can build more engaging support by helping your customers get answers in over 90 languages and speed up issue resolutions. 

Deep analytics and customer history: With pagergpt, you can tap data across multiple channels to build deeper customer behavior analytics. Analyze purchase history, website interactions, and customer service logs to find complex patterns and improve customer service performance. 

AI is rapidly reshaping how businesses connect with customers, moving from reactive automation to intelligent, proactive engagement. The next wave of innovation will focus on deeper personalization, predictive intelligence, and human-like experiences powered by agentic AI.

Multimodal and conversational experiences

Future AI agents will understand voice, text, and visual inputs simultaneously. This multimodal capability will create more natural and interactive customer experiences across devices and platforms.

Predictive and proactive engagement

AI will shift from responding to anticipating customer needs. Predictive AI agents will detect intent, forecast behavior, and act before issues occur — improving satisfaction and retention.

Collaboration among AI agents

Businesses will deploy interconnected AI agents that work together across sales, support, and marketing. These collaborative systems will share knowledge to deliver seamless, end-to-end engagement.

Humanized and emotion-aware interactions

Advancements in sentiment detection will help AI agents understand tone, emotion, and urgency. This emotional intelligence will make conversations more empathetic and human-like.

Compliance and ethical AI

As AI adoption grows, ensuring transparency, bias prevention, and data protection will become critical. Future AI agents will include built-in compliance frameworks for GDPR, SOC 2, and ethical use.

Data-driven customer intelligence

AI analytics will evolve from reporting to real-time decision-making. Businesses will use insights from AI-driven interactions to predict trends, optimize strategies, and design more personalized engagement models.

AI agents are redefining customer engagement by turning every interaction into a personalized, intelligent, and proactive experience. They empower brands to respond instantly, predict needs, and build stronger relationships at scale. As customer expectations continue to rise, adopting agentic AI isn’t optional—it’s essential for growth, efficiency, and loyalty.

pagergpt opens up enormous opportunities for your business, no matter which vertical you are operating in. To build a robust AI agent and drive real AI customer engagement, connect with pagergpt. Schedule a demo today.