Kore.ai

AI is advancing quickly. But trust still lags. On April 7 at 11:30 AM EST, Cobus Greyling hosts AI Activations with Soo-Jin Lee to unpack what it takes to design AI people can actually trust. We will cover: • Why AI feels smart but not intuitive • Balancing brand voice with real user behavior • Designing for edge cases and failure paths Save your spot: https://lnkd.in/gsBW5gJm

Out-of-the-box topic models look impressive until they hit real-world data. Labels drift. Context gets lost. And teams end up doing the work AI was supposed to eliminate. The issue isn’t modeling. It’s alignment. In this session, Prakash Anto walks through how a taxonomy-led approach to Topic Discovery changes that, anchoring AI to how your business actually thinks: products, intents, contact reasons. From there, every conversation is mapped with clarity, surfacing sentiment, resolution, and volume trends in near real time. See how that shift plays out in practice: https://lnkd.in/gPKRJwQz

Getting agents live was never the hard part. Managing them effectively is. At HumanX 2026, Cathal McCarthy (CSO, Kore.ai) is hosting a Peer Xchange roundtable: Managing Your Agent Workforce A room of leaders digging into what actually happens after deployment because this is where things get real. The harder questions start showing up: Who’s accountable? Is governance helping or slowing you down? Are your agents actually driving outcomes? If you’re past the pilot stage, this is a conversation worth being in. Register here - https://lnkd.in/gNB2Fs7E

Designing AI that works is one thing, but designing AI that people can actually trust and engage with is another. On April 7 at 11:30 AM EST, join Soo-Jin Lee behind conversational experiences at Amazon, Google, Netflix, and Wells Fargo for a closer look at what it takes to bridge that gap. If your AI is something people actually use, this session is worth your time. Register here: https://lnkd.in/gsBW5gJm

Most voice AI sounds good but very little of it works when things actually get complex. Rescheduling an appointment is simple. Resolving a billing dispute across systems, policies, and handoffs? That’s where things break. Because at that point, it’s no longer about speech. It’s about orchestrating context, decisions, and workflows in real time. The enterprises getting this right aren’t locked into one approach. They’re building on platforms flexible enough to adapt without rebuilding the stack every time. That’s what enables reliability at scale. We break this down in our latest AI Pulse session - https://lnkd.in/gBtGRQ3e

AI in healthcare sounds great in theory. But what does it look like in practice? At HIMSS 2026, we unpacked how teams are improving access, cutting admin work, and moving from pilots to real-world use. If you missed it, its now available on demand. Gary Fingerhut (Kore.ai) and Michael Duke (Guidehouse) break it down in 20 mins. Watch here: https://lnkd.in/gp9C-U6U

Everyone is building AI. But few are closing the loop. From a single intent through reasoning, context retrieval, tool orchestration, to full workflow completion. That’s where orchestration becomes the product. And trust becomes the constraint. Some domains are ready. Some don’t hold under real-world conditions.

Invoice fraud isn’t a new problem. But the way it’s evolving is. It’s no longer just about fake invoices. It’s near-perfect replicas, small changes in payment details, and issues that slip past even careful checks. And the reality? Most finance teams are still relying on manual verification to catch it. Which, over time, just doesn’t scale. In this piece, Sreeni Unnamatla explains how agentic AI turns reactive checks into continuous, context-aware validation. https://lnkd.in/e___hAia

If your AI stack is growing but outcomes aren’t really compounding, there’s a good chance you’re actually scaling the wrong layer. We’re seeing a consistent pattern: teams are building more agents, more copilots, more automation but the underlying search layer remains fragmented and that’s exactly where things break. In a recent conversation between Uma Sandilya and Rowan Curran, one point stood out: most AI problems are actually search problems underneath. This piece gets into the layer most teams overlook: search and retrieval, the foundation that actually determines whether AI can actually reason, decide, and act with confidence. Because when context is weak, everything built on top of it becomes unreliable. https://lnkd.in/gAKY8x2u

Nice to see Kore.ai on the curve, alongside the platforms moving agentic AI from idea to execution 🙌🚀 Right where the shift is actually happening💪