How AI Agents Improve Customer Experience

60% of support tickets are repetitive. And, customers expect immediate responses. That creates pressure on teams and frustration for customers. This is why support is one of the most practical and now proven places to apply AI. AI can handle common, repeat questions instantly, in your tone, using your knowledge base and CRM data. That frees up humans to focus on situations that require judgment, empathy, and creativity. One of our customers, The Knowledge Society (TKS) Society, did exactly that. Every enrollment season, they saw a surge of messages across email, Facebook Messenger, and WhatsApp. The busiest time of year was also the most overwhelming for their team. They implemented the Customer agent to answer common enrollment questions around the clock. Today, close to 80% of inquiries are handled automatically. Their team now spends more time on complex conversations and less time copying and pasting the same answers. The (ISSA) International Sports Sciences Association also scaled with Customer Agent. They were managing multiple support channels across different tools. The experience was fragmented for their team and inconsistent for customers. By introducing an AI agent to handle repetitive questions across channels, they cut response times in half and created a more consistent experience. Over 8,000 companies are already using HubSpot’s Customer Agent, with resolution rates above 67%. This is the real opportunity with AI in support.

Every delightful customer interaction begins with the marketer, and it can only be as powerful as the #CRM and #metadata underpinning it. With agents supporting them at every step of the customer journey creation process, marketers and #customerengagement teams can now create superior experiences shaped by intelligent and emotionally resonant conversations. At a cognitive level, the human brain no longer perceives AI as a “chatbot.” It perceives a relationship. This emotional shift fundamentally changes how consumers relate to brands, fostering deeper loyalty and trust. When customers interact with agents in a way that feels natural, their engagement deepens. The implications go far beyond engagement. Every AI-driven interaction generates a wealth of contextual data, far richer than what brands could ever collect from a single web form or survey. In one conversation, an agent can gather insights about a customer’s preferences, behaviors, and intent, building a more complete, dynamic customer profile. This continuous intelligence loop allows brands to maximize the value of every interaction. Let’s bring this to life with an example... Imagine Melanie, one of your many potential customers. She’s been thinking about joining Posh Fitness, a popular gym chain in her city. Instead of filling out a form, she decides to engage with the agent on their website. As they chat, it quickly feels more like a friendly exchange than a transaction. Melanie shares her fitness goals, whether she wants to lose weight, gain muscle, or improve flexibility, and the agent listens closely, asking the right questions to understand her needs and intent. The agent gathers valuable insights through this conversation that a simple web form could never capture. Melanie mentions her dietary restrictions, her preference for a supportive personal trainer style, and that she loves outdoor workouts but needs a flexible schedule due to her busy life. In just a few minutes, the agent collects a wealth of data about Melanie: her goals, preferences, and availability—all essential to crafting a personalized experience. And because the conversation feels human-like and emotionally resonant, it creates an immediate connection to Posh Fitness. By collecting this richer data early in the relationship, Posh Fitness can offer tailored recommendations and build Melanie’s loyalty well before she signs up. This isn’t just about closing a sale. It’s about building trust and delivering personalized experiences that evoke emotions and feel deeply human. Brands that will thrive in the era of #Agentic #AI are those that recognize the shift from transactional interactions to relationship-driven engagement. This isn’t just about personalization; it’s about creating experiences and dialogues that feel alive—where AI and marketers co-create journeys that adapt in real time, amplifying the impact of every customer moment.

AI + HI = Improved CX In today’s digital world, businesses strive to deliver exceptional customer experiences (CX) to stand out. While artificial intelligence (AI) has revolutionized CX by enabling automation, personalization, and efficiency, it cannot fully replace the human touch. AI enhances CX by processing vast amounts of data in real time, predicting customer preferences, and providing instant responses through chatbots, recommendation engines, and self-service options. It reduces wait times, offers 24/7 support, and ensures consistency across interactions. However, AI alone has limitations—it lacks emotional intelligence, creativity, and the ability to handle complex, nuanced customer concerns. Human agents bring empathy, critical thinking, and problem-solving skills that AI cannot replicate. When combined with AI, human agents become more efficient, as AI handles routine tasks, provides insights, and allows them to focus on high-value interactions. Impact on BPO KPIs 1. First Call Resolution (FCR) Improvement: • AI-driven knowledge bases and predictive analytics equip human agents with real-time solutions, reducing repeat calls. • Virtual assistants handle routine inquiries, allowing human agents to focus on complex issues. 2. Reduction in Average Handling Time (AHT): • AI-powered tools like speech analytics and automated summaries minimize the time agents spend on after-call work (ACW). • Virtual assistants can gather customer information before handing over to a live agent, speeding up resolutions. 3. Increased Customer Satisfaction (CSAT): • AI ensures faster response times and personalized interactions based on past behavior. • Human agents, equipped with AI-driven insights, can provide more empathetic and accurate solutions, improving overall satisfaction. 4. Enhanced Agent Productivity and Utilization: • AI automates repetitive tasks such as data entry, ticket classification, and FAQs, freeing up agents for complex interactions. • Sentiment analysis tools help agents adjust their approach in real time for better engagement. 5. Lower Cost Per Contact: • AI-driven self-service options reduce the volume of inbound calls and chats, lowering operational costs. • Intelligent routing ensures the right agent handles the right query, optimizing workforce efficiency. 6. Improved Net Promoter Score (NPS): • Personalized AI-driven recommendations and proactive outreach enhance customer engagement. • The combination of AI efficiency and human empathy fosters long-term customer loyalty. The synergy of AI and HI leads to an improved CX by ensuring speed, accuracy, and emotional connection. AI-driven insights empower human agents to offer proactive solutions, while human empathy ensures customers feel valued. AI and HI are not competitors but collaborators. Businesses that successfully integrate both will deliver superior CX, optimize BPO performance, and achieve sustainable growth in an increasingly digital world.

While everyone's talking about AI replacing human agents, something more interesting is happening: technology and humans are forming a powerful partnership that's transforming customer experience. AI isn't stealing your agents' jobs – it's making them superheroes. At Callzilla - The Quality-First Contact Center, we've been implementing Agent Assist tools that give agents real-time support during customer interactions. The results speak for themselves: • Agent gets asked an impossible question? AI whispers the answer • Customer mentions an uncommon tech issue? Relevant articles appear automatically • Agent struggling to categorize the call? AI suggests the perfect reason code • About to make a mistake? AI catches it before it happens This creates a 'best of both worlds' scenario where technology handles routine tasks while agents focus on what humans do best: • empathy • genuine connection • creative problem-solving When to Automate vs. When to Humanize: • Let AI Handle: Repetitive tasks, basic info lookups, initial problem identification • Keep It Human: Complex problems, emotional situations, VIP customers who expect the red carpet treatment Pro tip: Give customers choice. Instead of forcing one path, ask: "We can have an agent available in 5 minutes, or you can chat with our AI assistant now who handles most issues. What works better for you?" Your tech should be: • Serving up answers faster than expected • Reducing agent cognitive load, not adding to it • Supporting natural conversation, not rigid scripts • Suggesting solutions, not just documenting problems AI doesn't replace your agents – it creates 'super agents' who resolve issues faster, with less effort, and greater accuracy. It's not about choosing between humans OR technology. It's about humans AND technology working together. The companies seeing the best results have figured out this perfect pairing – and their customers can't get enough. What's your experience with human-AI partnerships in CX?

AI agents are on the verge of transforming digital commerce beyond recognition and it’s a wake-up call for many companies, including Shopify, Intercom, and Mailchimp, as I outline in my new post https://lnkd.in/gZKzPURM In this new world, your AI agent will book flights, negotiate deals, and submit claims—all autonomously. It’s not just a fanciful vision. A web of emerging infrastructure is rapidly making these scenarios real, changing how payments, marketing, customer support, and even localization will operate: (1) Agentic payments – Traditional card-present vs. card-not-present models assume a human at checkout. In an agent-driven economy, payment rails must evolve to handle cryptographic delegation, automated dispute resolution, and real-time fraud detection. (2) Marketing and promotions – Forget email blasts and coupon codes. Agents subscribe to structured vendor APIs for hyper-personalized offers that match user preferences and budget constraints. Retailers benefit from more accurate inventory matching and higher customer satisfaction. (3) Agent-native customer support – Instead of human chat widgets, we’ll see agent-to-agent troubleshooting and refunds. Businesses that adopt specialized AI interfaces for these tasks can drastically reduce response times and improve support experiences. (4) Dynamic localization – The painstaking process of translating websites becomes obsolete. Agents handle on-the-fly language conversion and cultural adaptations, allowing businesses to maintain a single “universal” interface. Just as mobile reshaped e-commerce, agent-driven workflows create a whole new paradigm where transactions, support, and even marketing happen automatically. Companies that adapt—by embracing agent passports, machine-readable infrastructures, and new payment protocols—will be the ones shaping the next era of online business. More in the third post of my series on AI agents and their impact on the internet https://lnkd.in/gZKzPURM Also available as a NotebookLM-powered podcast episode (highly recommended)

As the Head of Capgemini Business Services's, I’ve had the privilege of working with numerous industry leaders to navigate the complexities of customer service. Our latest research from the Capgemini Research Institute highlights a critical insight: while nearly 60% of consumers view customer service as crucial to their brand perception, less than half (45%) are satisfied with their experiences. This gap presents a significant opportunity for transformation. In the GBS industry, we often face operational challenges that hinder our ability to deliver seamless customer experiences: Interdepartmental Coordination: A staggering 74% of executives say this is a major barrier, leading to fragmented and inconsistent experiences. Underutilized Customer Insights: Only 50% of organizations use customer service data in decision-making processes, missing key opportunities to enhance CX and operations across departments. High Agent Churn: Just 16% of customer service agents are satisfied in their roles, highlighting the need for better support and engagement. To drive satisfaction and loyalty, organizations need to improve collaboration between departments and make better use of customer insights across the business. AI is a game-changer here, and those that have implemented Gen AI are already seeing the benefits. AI can improve response times and cut operating costs. Generative and agentic AI can also enhance the experience for agents by providing real-time customer data from across departments like sales and marketing. Virtual agents are taking over repetitive tasks, and most agents (70%) are seeing a lighter workload, allowing them to focus on more valuable interactions. I believe that by leveraging AI and building a connected enterprise, businesses can transform customer service from a support function into a key strategic driver of value and growth. Read more in the comments below: https://lnkd.in/e6RhY2bN

There's one use case for AI agents not being talked about enough: volatile or seasonal industries. Think about what crypto, fintech, travel, and even retail have in common. Their surges in volume (some random, some not) and customer inquiries make it extremely challenging for traditional CX systems to keep up. But where legacy systems struggle, AI systems step up. Here's how: 1. Scalability When inquiry volumes spike, AI agents can handle the influx without missing a beat. There are no delays from hiring surplus human agents to handle more volume, making AI agents both cost- and process-efficient. 2. Consistency Whether it's 1K or 1M customer inquiries, AI agents guarantee the same level of accuracy and precision every time. Humans need downtime, AI doesn't. 3. Prioritization Customer inquiries come with varying degrees of complexity. While AI agents take care of the low-hanging fruit and repeatable tasks, human agents can focus on the high-touch cases that demand personal attention. Take Coinbase’s customer support, for example. They handle $226B in quarterly trading volume in 100+ countries. Their margin of error is slim, and CX mistakes could cost billions. Instead of leaning on human CX alone, they use AI agents to: • Handle thousands of messages per hour • Reduced customer service handling time • Improve search relevance for their help center The enterprises we work with at Decagon experience the same benefits using AI customer service agents—scalable support, no gaps in performance, and higher customer satisfaction. Just because your industry is volatile doesn't mean your CX should be.

Context Engineering: The Psychology of Exceptional Customer Experience with AI Agents A context engineering guide that will help you implement an AI Agent that customers actually love. Here's what nobody talks about: Great customer experience isn't about solving problems faster. 🤝 It's about being known. When your AI agent remembers that Sarah prefers email updates, hates small talk, and always asks about enterprise pricing—that's not just efficiency. That's recognition. And recognition builds trust. Context Engineering is the psychology of digital relationships. It's teaching AI agents to hold space for customers the way humans do: → Remember what matters to them → Build on past conversations → Anticipate their needs → Speak their language The difference? Customers stop seeing your AI as a roadblock and start seeing it as an ally. Most companies are still building "smart answering machines." The breakthrough companies are building AI that customers genuinely prefer over human support. Not because it's faster. Because it knows them better. Context engineering transforms AI from a tool customers tolerate into a relationship they value. That's the real competitive advantage. What makes you feel truly "known" in a customer service interaction?

For the past few months, I’ve been setting up AI agents for our customers. As we launched AI on chat, I understood something I didn’t expect... Chat AI agents are going to fundamentally change the way shoppers interact Here’s how my thinking evolved: 👉 Initial thought: AI agents were here to improve customer experience with instant responses. 👉 Next idea: Once set up, they could start turning support conversations into sales 👉 The real insight: There’s more than that. When I shop, I start with ChatGPT, telling it what I want to buy and getting personalized recommendations. I then provide feedback to narrow down the options. Once I’ve found what I want, I leave ChatGPT and head over to the merchant’s website. I beleive the in store experience we have when speaking with a store associate can finally have its digital equivalent. Drift pioneered this for B2B SaaS a few years ago, but back then you could only chat with SDRs, which eventually felt limited. Now, AI agents enable a whole new level of depth, that’s comparable to the quality of conversation you’d have with an associate, if not better. I think merchants need to provide this kind of experience on their websites. Having an AI agent on chat isn’t just about responding to existing conversations. 𝗜𝘁’𝘀 𝗮𝗯𝗼𝘂𝘁 𝗲𝗻𝗰𝗼𝘂𝗿𝗮𝗴𝗶𝗻𝗴 𝗺𝗼𝗿𝗲 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 𝘁𝗼 𝘀𝗵𝗼𝗽 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻, which will likely result in 10x more conversations and an overall better shopping experience. I’m working with the GLAMNETIC team to implement this, and I’ll keep sharing my learnings as we move forward.

The true shift in CX is yet to come. By 2030, it will fundamentally reshape how brands interact with consumers. The real transformation in customer experience won't just be improved service or personalized experiences. It will be about creating AI Agents that become the primary interface between brands and customers. Just as websites were indispensable in the late 90s, AI Agents will become the new digital storefront by 2030. These aren't just chatbots or virtual assistants—they're the brand personified, capable of handling everything from customer service to personalized shopping experiences to product education. Imagine a future where every major brand has its own sophisticated AI Agent: ➝ A running shoe company's AI Agent might analyze your previous shoe style and running goals to suggest the right shoe and create a personalized training plan to help you achieve your targets. ➝ A beauty brand could use image recognition to assess your skin type and tone, recommend products tailored to your needs, and even provide virtual try-on experiences for different makeup looks. ➝ A smart home device manufacturer could proactively diagnose issues with your devices, guide you through setup processes, and suggest automation routines based on your daily habits. The quality of a brand's AI Agent will become as crucial as its website is today. Brands will pour resources into creating AI Agents that aren't just functional but engaging, personable, and aligned with their brand identity. This shift will redefine brand loyalty. Customers might find themselves loyal not only to a brand's products, but to the experience and relationship they have with the brand's AI Agent. In 2030, we might find ourselves judging brands not by their logos or ad campaigns, but by the personality, capability, and trustworthiness of their AI Agents. The most successful brands will be those whose AI Agents become trusted advisors and companions in their customers' lives. The future of CX will be defined by AI Agents becoming the service—the primary way customers engage with and experience brands. Are brands ready for this AI Agent-first future?