Your Customers are About to Expect AI—Here's the $254M Proof
PLUS: Turn Customer Complaints Into AI Training Gold
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📅 September 24, 2025 | ⏱️ 3-min read
🎯 The big picture
Here’s what happened while you were sleeping: over $250 million in fresh AI funding just hit the market across multiple deals, all focused on customer-facing technology. This isn’t just venture capital getting excited—this is serious money betting that AI for customer experience is about to become table stakes.
📊 Today’s lineup
CVS just bet $33.7M on human-AI collaboration
Marriott flew 75 customers to HQ to test their AI chatbot
Healthcare gets an AI receptionist that sounds human
A new AI training suite promises to solve the “our agents don’t know how to use AI” problem
Auto dealers get 24/7 AI scheduling
1️⃣ CVS just bet $33.7M on human-AI collaboration
What’s happening:
• AmplifAI just closed a $33.7M Series B led by CVS Health Ventures, with participation from LiveOak Ventures and Dallas Venture Partners.
• Their platform unifies human and AI agent performance in one system, ensuring humans handle complex interactions while AI manages routine contacts.
• Since 2018, they’ve delivered measurable results: 100%+ increase in sales conversion, nearly 10% reduction in cost per contact, and 20%+ improvement in resolution rates.
What’s so interesting: Everyone’s deploying AI agents, but AmplifAI figured out the hardest part: making humans and AI work together seamlessly. They’re not replacing people—they’re making both humans and AI more effective by treating performance as one unified system.
What’s next: The hybrid approach is winning. If your AI strategy is either “replace humans” or “ignore AI,” you’re missing the point. The future belongs to companies that optimize human-AI collaboration.
Go deeper: Business Wire
2️⃣ Marriott flew 75 customers to HQ to test their AI chatbot
What’s happening:
• Marriott hosted their first-ever “members’ day” at their Bethesda headquarters, bringing in 75 top loyalty customers.
• They tested a prototype AI chatbot for the Marriott Bonvoy app that personalizes hotel searches and bookings.
• Nearly the entire C-suite attended to gather direct customer feedback on the AI experience before any public rollout.
What’s so great about this: This is brilliant customer research disguised as a VIP event. Instead of building AI in a vacuum, Marriott is getting feedback from their most valuable customers before launch. The fact that they flew people to headquarters shows they’re serious about getting this right.
What’s next: Stop building AI features based on what you think customers want. Start copying Marriott’s playbook: invite your best customers to test your AI before you roll it out. The feedback you get will save you months of costly mistakes.
Go deeper: Skift
3️⃣ Healthcare gets an AI receptionist that sounds human
What’s happening:
• NextGen Healthcare just launched Navigator AI, an AI customer service agent powered by Luma Health.
• It handles medication refills, appointment scheduling, directions, and practice hours in English and Spanish.
• The AI knows when to transfer to humans and offers automatic follow-up if calls get dropped.
What’s so interesting: Healthcare has been notoriously slow to adopt customer-facing AI because of privacy concerns and the high stakes. But staff shortages are forcing the industry’s hand. If healthcare practices can trust AI with patient interactions, every other industry should be paying attention.
What’s next: Voice AI that doesn’t suck is finally here. If your phone system still makes customers want to scream, this technology is ready for you too. The healthcare use case is just the beginning.
Go deeper: Destination CRM
4️⃣ A new AI training suite promises to solve the “our agents don’t know how to use AI” problem
What’s happening:
• Comm100 unveiled three AI solutions: AI Knowledge, AI Quality Assurance, and AI Onboarding.
• The tools automatically maintain knowledge bases, review every customer interaction (not just samples), and create interactive training scenarios.
• They work independently but create an “intelligent ecosystem” when deployed together.
What’s so great about this: Finally, someone’s addressing the elephant in the room: most support teams have no idea how to work with AI effectively. These tools don’t just deploy AI—they teach your team how to use it and ensure quality at scale.
What’s next: The days of “figure out AI as you go” are ending. Invest in proper AI training infrastructure now, or watch your competitors leave you behind with better-trained teams.
Go deeper: PR Newswire
5️⃣ Auto dealers get 24/7 AI scheduling
What’s happening:
• Kenect, a provider of AI technology for auto dealerships, just launched Voice AI.
• The AI functions as a virtual receptionist available 24/7 to handle inbound calls, answer routine questions, and schedule service appointments.
• It includes intelligent call routing based on inquiry type, customer status, or repair order, integrated directly with dealership management systems.
What’s so interesting: Auto dealerships are notorious for poor customer service, especially in service departments. This AI addresses a real pain point—customers calling after hours or during busy periods when staff can’t answer. It’s a practical solution for an industry that desperately needs better customer experience.
What’s next: Industry-specific AI solutions are the future. Generic chatbots don’t understand your business, but specialized AI that knows dealership workflows and terminology can actually move the needle on customer satisfaction.
Go deeper: Destination CRM
⚡ Quick hits
• Prosper AI raised $5M to tackle healthcare’s $450B admin crisis with voice AI → shows how AI is moving beyond customer service into operational efficiency.
• AppZen secured $180M led by Riverwood Capital for their agentic AI finance platform → signals enterprise finance is ready for AI automation at scale.
• Omnisend launched AI-powered assistants and enhanced SMS capabilities → ecommerce marketing automation is getting smarter and more personalized.
💡 CX Prompt Tip of the Day
Turn Customer Complaints Into AI Training Gold
Act as an AI training specialist reviewing this customer complaint: [insert complaint].
Your task:
1. Extract the specific knowledge gap this complaint reveals
2. Create a training scenario an AI agent could learn from this situation
3. Write a “golden response” that would have prevented this complaint
4. Suggest 3 similar scenarios to test the AI’s understanding
Format as: Problem → Training Scenario → Golden Response → Test Cases
Keep it practical and immediately actionable.
Quick win: Use this on your top 5 complaint types this week. You’ll build an AI training library that actually reflects real customer pain points, not theoretical scenarios.
🤔 CX reflection
Question of the day: If over $250M in AI funding just dropped in one day, what does that tell you about how fast your customers’ expectations are about to change?
See you tomorrow!
Mark