Ada's AI Agents Outperform Humans in Customer Support

📖 NEW case study — ada CX's story Before writing a line of code, Ada's founders worked as customer service agents for seven companies. Today, Ada's customers achieve 80%+ autonomous resolution rates exceeding human teams — processing 1.5+ trillion tokens monthly for brands like Pinterest, Square, and IPSY. Through our case study series, Launching AI products that win, we’re talking to SaaS and AI leaders to uncover how they successfully built and commercialized leading AI products and features. We sat down with CEO and Co-founder Mike Murchison to unpack how the challenges of scaling customer service at his previous company inspired the idea for an Agentic Customer Experience (ACX) platform, which became Ada. Discover key founder lessons along with: ✔️ Why your product identity should be rooted in outcomes, not technology ✔️ How to align your pricing model with what your customers value ✔️ The value of AI agent resolution depth > resolution rate Get the full case study: https://lnkd.in/gFEcXaNn

Most companies lose customers not because of bad products, but because of bad experiences. That's where AI is making a real difference. With our new Gemini Enterprise for CX, businesses can connect every touchpoint across the customer lifecycle and turn interactions into actual growth. Here's what this looks like in practice: 🛒 A Shopping Agent guides customers through complex decisions in real time. 🔍 Vertex AI Search surfaces the right information instantly, whether that's for the customer or the agent supporting them. 🎯 Customer Experience Insights turn conversation data into actionable signals so you know what's working and what's costing you retention. The shift I'm seeing with our customers: AI isn't just automating tasks anymore. It's handling entire journeys, from the first search to post-purchase support, with context and continuity. Not as an experiment. As a new operating model for customer experience. Where in your customer journey do you see the biggest opportunity for AI to make a real impact? I'd love to hear what you're working on. 💬 https://ow.ly/OjnJ50YxiJi

Why AI-First Customer Support Is Replacing Ticketing Systems (And What to Do About It) 🚀 The era of traditional ticketing systems is slowly coming to an end. AI-First Customer Support is transforming how businesses interact with customers. 💬 Instead of waiting 24–48 hours for a ticket response, AI can resolve many issues instantly — anytime, anywhere. ⚡ Modern AI understands customer intent, keeps conversation context across channels, and can even take action automatically. 💡 This shift moves support from reactive problem solving to proactive customer experience. 💰 Companies are also seeing massive cost savings — reducing support costs from about $22 per ticket to just cents per AI interaction. 📈 The result: faster resolution, happier customers, and scalable support without increasing headcount. Businesses that embrace AI-first support today will lead tomorrow’s customer experience. #AI #CustomerSupport #CustomerExperience #DigitalTransformation #AIChatbots #Automation #BusinessInnovation #TechTrends #FutureOfWork

A phenomenal and succinct video by Michelle Mondonedo and Shannon Kohler on AI readiness for software providers. A highly recommended watch.

Just got back from Enterprise Connect last week, and one thing was clear: everyone is talking about CX and AI. But one stat stuck with me. Around 95% of generative AI projects fail. Not because the technology isn’t capable. Most of the time, it’s because the projects start without clear KPIs, no defined path to ROI, and no real plan for how the technology actually improves the customer or employee experience. The 5% that succeed look very different. They start small. They define success early. They measure outcomes. And they understand that small improvements, compounded over time, can completely transform how a business serves its customers. AI in the contact center doesn’t have to be a massive, risky overhaul. Sometimes it’s as simple as improving routing, automating repetitive interactions, or giving agents better information in real time. At 1Touch Communications, our role is to bring trusted partners to the table and help organizations evaluate what actually makes sense for their business. No hype, just the right technology and a clear path to results. If your team is exploring AI or CX improvements this year, I’d be happy to compare notes and share what we saw at Enterprise Connect. Side note: Thank you to our supplier Nextiva for having us at their booth and for the proof that I can dance (badly).

Most multi-channel customer journey builders have an Execution Gap: you have the strategy in your head, but translating it into a high-performing, multi-channel map takes hours of manual work. We built our new Agent - Merlin AI Flow Assist to bridge that gap instantly. Now, you can describe your goal in plain English, and Flow Assist Agent builds the logic directly in your MoEngage canvas: ✍️ Prompt-to-Flow Orchestration: Transform a single sentence into a multi-stage, cross-channel journey. 🧠 Agentic Reasoning: Flow Assist clarifies your intent - asking for specific triggers and delays to ensure logic is airtight. 📲 Instant Multi-Channel Setup: Instantly generates optimized multi-channel flows with smart nodes and seamless channel orchestration. Check out Flow Assist in Action below👇 #AgenticAI #MarketingAutomation #ProductUpdates

GenAI is changing Customer Experience. But not in the way most teams think. Most companies use GenAI to automate responses. Smart companies use GenAI to accelerate customer learning. There’s a difference. Automation asks: “How do we respond faster?” Customer learning asks: “What are customers repeatedly struggling with?” In AI workflow systems, we observed something powerful: When GenAI interactions were structured to extract patterns - not just generate replies - We uncovered: • Repeated friction points • Confusing onboarding steps • Hidden feature gaps • Misaligned expectations Instead of treating AI as a support layer, we treated it as a real-time insight engine. That changed roadmap decisions. GenAI shouldn’t just reduce support load. It should reduce product blindness. The real opportunity isn’t better chatbots. It’s faster product feedback loops. #ProductManagement #GenAI #CustomerExperience #AIProducts #ProductStrategy #SaaS

We’re excited to welcome Magic Mind to our growing partner portfolio! 🚀 Their team is now leveraging KODIF’s agentic AI platform to power a smarter CX experience — resolving a high volume of subscription and order-related inquiries automatically, freeing up human agents to focus on higher-impact conversations. Even better? They’re unlocking real-time insights on customer behavior and trends through Kodif’s analytics — turning support into a true growth engine. From mental performance to operational performance ⚡ Welcome to the world of sharper minds — and now, sharper CX.

The PLG didn’t die with AI. It evolved. For years, PLG was simple: let the product speak for itself. Free trial, automated onboarding, grow. But users no longer have patience to discover value on their own. With AI everywhere, they expect the product to understand them before they understand the product. That doesn’t kill PLG. It forces it to adapt. What I see in SaaS that actually scales: PLG is no longer “let the user explore.” It’s “adapt the experience to real user behavior, in real time.” 1. Onboarding that changes based on who you are — not one flow for everyone. The product detects your profile and shows you a different path. 2. Behavior triggers, not time-based triggers — not “3 days after signup, send this email.” But “when the user reaches this point without completing X, activate this message.” 3. Drop-off detection before it happens — the system reads the signals that someone is about to leave and acts on its own. The tools I use and recommend: Amplitude — to understand what users actually do inside the product. Customer.io — to build behavior-based sequences. Appcues — for adaptive in-app onboarding by segment. Mixpanel — for cohort analysis and free-to-paid conversion. n8n — to automate flows between tools without touching engineering. Skene — analyzes your codebase, maps user flows, and generates PLG loops from the repo. Not just a dashboard — it acts on insights. The product that grows on its own in 2026 isn’t the one with the best static onboarding. It’s the one that learns from every user and adjusts before they decide to leave. That’s exactly what I build with my clients.

Customer experience is being rewritten in real time. The companies winning today aren’t just experimenting with AI, they’re driving results with it. They’re building service organizations where technology and people work as a unified system, delivering better quality, and measurable outcomes. Hear directly from leaders doing exactly that at Crescendo Live San Francisco 2026: 🎤 Morgan Donaldson, Cntrl+ Inc.+ 🎤 Hemant Taneja , General Catalyst 🎤 James Green, SQUIRE 🎤 Kevin Rury, Taskrabbit 🎤 Oliver Hart, POLYWOOD® 🎤 Christopher Toshiro Jocson, Good Eggs …and more CX innovators shaping the next generation of service. From venture perspective to operational execution, these conversations will unpack what it really takes to scale AI in customer experience, without losing the human expertise that makes great service possible. 🤝 Because the future of CX isn’t AI or people. It’s AI orchestrating Superhuman teams to deliver outcomes in weeks, not months. ✨ Request your spot: https://lnkd.in/dAWUxNrM