Insights

Gamma experts share their thoughts on how AI will influence CX going forward. Artificial intelligence has become the catalyst forcing organisations to rethink operations. Customer journeys are being redesigned, and teams are rethinking on how best they can work together. In terms of customer experience (CX), it isn’t simply just another layer of technology added on. AI within CX has become a key topic for debate. Exciting in potential, yet daunting in practice. With customer

In this blog, you’ll learn: How AI is transforming CX, and why future-ready networks are critical. The role of robust infrastructure in delivering reliable AI-powered CX. Why assessing and strengthening digital foundations protects customer trust and maintains competitiveness. Modern customer experience is increasingly shaped by AI. We’re seeing its usage within the likes of automated service agents and predictive decision-making. But no matter how advanced these tools become

Omnichannel customer service—which aims to deliver one seamless, continuous experience across all channels—has become the gold standard in recent years. Today, 73% of customers switch between at least three channels in their journey, while 80% say the experience matters as much as the product itself. However, only 45% say they’re “satisfied” with the quality of support they receive. To meet rising customer expectations, companies are turning to AI-driven solutions to boost bo

More than ever, quality of service makes the difference for a contact center. But how do you ensure that every customer interaction lives up to expectations, when you’re managing high call volumes? This is what Automated Quality Monitoring (AQM) is all about, revolutionizing the way companies evaluate and improve their customer conversations. Based on artificial intelligence, AQM automatically analyzes 100% of interactions across all channels. AQM puts an end to time-consumi

AI is rapidly transforming customer service, redefining how businesses interact with their customers. Among its many applications, the intelligent virtual agent stands out as one of the most strategic and impactful tools. Gartner predicts that by 2029, agentic AI will autonomously resolve 80% of common customer service requests without human intervention. Available across multiple channels, this digital assistant understands natural language, adapts to context, and delivers r

If your AI is closing tickets but not solving problems, it’s doing more harm than good. It’s hard to deliver great service if you aren’t actually resolving a customer’s issue. Most customers wouldn’t count a dropped call or a timed-out chat as resolution, and you shouldn’t either. But many companies say it is – and charge you for it, too. Resolution isn’t deflection. It’s not a half-baked handover or a conversation that simply ends. A true resolution is when the problem is fu

After all, recent studies show that 66% of customers expect that companies will understand their needs. This is why companies that orient their operations towards this are 60% more profitable than the rest. The main components of good CX are: Understanding the target customer’s mindset before making the purchase. Mapping the customer journey from awareness to fulfillment. Removing pain points across channels for conversion and retention. Successfully managing the digital cust

A lot goes into running a thriving contact center, like resolving customer issues, end-of-call wrap-ups, answering customer questions, and agent training. Fortunately, technology is advancing rapidly, and artificial intelligence (AI) is paving the way for call centers to become more efficient and better serve customers. Zoom’s State of AI in Customer Experience (CX) 2025 report reveals that 64% of companies that are using AI for call centers enjoy a positive ROI, while 79% sa

Product teams often feel like they’re drowning in data but starving for insights. Turning raw behavior into clear, actionable direction is still slow, manual, and fragmented. Session replays are widely used, yet reviewing them takes time, offers limited coverage, and often delays decisions. Tara changes this. By automatically analyzing visual user behavior, she surfaces patterns, explains what’s going on, and suggests what to do next, all within minutes. Instead of searching

Product teams don’t suffer from a lack of data. They suffer from a lack of time, clarity, and follow-through. You ship features, launch experiments, and roll out updates… then the real work begins. Someone has to watch sessions. Someone has to find issues. Someone has to make sense of what’s happening. Someone has to decide what matters. Someone has to turn insights into actions. That “someone” is usually you. Tara AI changes that. She is an AI product analyst that joins your

Organizations are investing in AI solutions to improve their support operations and customer experience, but only 25% of AI projects have delivered their promised ROI, according to an IBM survey of over 2000 CEOs. While there are many reasons AI projects fall short, data privacy and security concerns are often a major culprit. In many cases, a support team evaluates and pilots an AI solution based on features, but their security, compliance and legal teams shut the project d

Based on the hype around AI, you’d think the majority of businesses are actively using AI in every part of their business and especially in their support operations. In reality, most have yet to move beyond the planning or pilot phase, with projects frequently stalling due to many factors such as AI hallucinations and security and compliance issues. A recent Deskpro survey of over 220 support and IT leaders found that while 37% of organizations have deployed some level of AI

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