AI Delivers Millions While 67% of Companies Have Lost Control
PLUS: AI deployment success measurement + Quick ROI calculation framework
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September 17, 2025 Read Time: ~4 minutes
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🎯 Today's Big Takeaway
Companies are finally sharing real numbers that prove AI actually works. But here's the catch: most of them have no idea how to manage what they've built.
📊 Today's Hot Takes
Stories That Matter:
• Google standardizes AI-driven purchases with new Agent Payments Protocol
• Agentic AI generates millions in B2B sales, redefining customer journeys
• CallMiner research reveals dangerous AI governance gap despite widespread adoption
• Gartner predicts human agents remain essential through 2028 for Fortune 500
• MIT Sloan warns leaders need new playbooks to manage agentic AI
Prompts & Tools:
• 🎯 AI deployment success measurement framework
• ⚡ Quick ROI calculation for customer-facing AI
📡 Signal in the Noise
Something interesting is happening. Every story today has actual performance numbers attached. We're not talking about AI demos anymore—we're talking about AI that's making money and changing how customers interact with businesses.
🎯 Executive Lens
The companies winning right now aren't the ones with the fanciest AI. They're the ones who can point to a spreadsheet and say "here's exactly how our AI made customers happier this quarter." That's a pretty big shift from where we were even six months ago.
Stories That Matter
🤖 Google just made AI shopping a real thing
The News: Google launched something called the Agent Payments Protocol—basically letting AI agents actually buy stuff for you. They've got 60+ partners including Mastercard, PayPal, and Coinbase backing this thing.
Why CX Pros Should Care: Think about it this way—your customers already ask AI for product recommendations. Now that same AI can complete the purchase without any human handoff. Your checkout flow better be ready for robots, because they're coming.
Pros: No more cart abandonment because customers got distracted or confused during checkout; AI never sleeps so you're basically open 24/7; routine purchases (like subscriptions) become completely frictionless; conversion rates could go through the roof.
Cons: You lose those moments where humans build relationships with your brand; security becomes way more complex; shopping might turn into a commodity where price is the only differentiator; you'll get way less data about what customers actually want.
What CX Leaders Should Do Next:
• Pull up your analytics and find where people abandon their carts—that's where AI purchasing could help most
• Start thinking about how to make your product pages speak to AI, not just humans
• Test AI-assisted buying for your most predictable transactions first
Source: TechCrunch
🤖 One company is projecting $50M from AI sales agents
The News: Harvard Business Review dug into how B2B sales teams are using AI to run entire sales cycles. One company thinks they'll hit $50 million in new revenue just from AI doing lead qualification and personalized outreach.
Why CX Pros Should Care: This isn't about cutting costs—it's about AI creating revenue you couldn't generate before. When AI can handle complex, multi-touch sales conversations, it changes everything about how customers experience your sales process.
Pros: You can personalize outreach at a scale that would be impossible with humans; AI never forgets to follow up; every interaction is consistent; your best salespeople can focus on the relationships that really matter.
Cons: B2B buyers might prefer talking to humans about complex deals; AI could make decisions that hurt long-term relationships; you need tons of data to train AI properly; some customers will figure out they're talking to AI and feel deceived.
What CX Leaders Should Do Next:
• Map out which parts of your sales process are repetitive enough for AI to handle
• Figure out where AI should hand off to humans—and make sure that handoff is smooth
• Start measuring relationship quality, not just conversion rates
Source: Harvard Business Review
🤖 Most companies are using AI without any safety net
The News: CallMiner just dropped some sobering research: 80% of CX organizations are using AI, but 67% don't have proper governance. That's like driving without a seatbelt.
Why CX Pros Should Care: We're all rushing to deploy AI because it works, but most of us aren't thinking about what happens when it breaks. And it will break. When AI makes a bad decision about a customer relationship, who's accountable?
Pros: This creates a huge opportunity for companies that get governance right; you can move fast while competitors worry about regulations; most of your competition is vulnerable to AI mistakes right now.
Cons: Your AI deployments are probably riskier than you think; one bad AI decision could damage customer trust for years; regulations are coming whether you're ready or not; you might be creating problems you don't even know about yet.
What CX Leaders Should Do Next:
• Do an honest audit—can you explain how your AI makes decisions that affect customers?
• Set up metrics that track customer trust, not just operational efficiency
• Create clear escalation paths for when AI does something questionable
Source: CallMiner Research
🤖 Gartner says human agents aren't going anywhere
The News: Despite all the hype about AI replacing customer service, Gartner predicts no Fortune 500 company will eliminate human agents by 2028. Complex problems still need human judgment.
Why CX Pros Should Care: This gives you permission to stop worrying about AI taking over and start thinking about how AI makes your people better. The future isn't human vs. AI—it's humans with AI superpowers.
Pros: You don't have to gut your team to be "AI-first"; empathy and complex problem-solving remain competitive advantages; hybrid human-AI teams could be way better than either humans or AI alone.
Cons: Your labor costs aren't disappearing; managing hybrid teams is complicated; customers might get confused about when they're talking to AI vs. humans; you need to figure out what each does best.
What CX Leaders Should Do Next:
• Stop thinking about AI as a replacement and start thinking about it as an upgrade
• Define which interactions absolutely need human empathy
• Measure success by customer satisfaction, not just how many people you laid off
Source: CIO Dive
🤖 MIT says we need completely new playbooks for AI management
The News: MIT Sloan and BCG just published research showing that traditional management doesn't work for agentic AI. 69% of experts agree these systems move too fast for normal oversight.
Why CX Pros Should Care: The AI you're deploying isn't just advanced software—it's something that operates at a speed and scale that breaks traditional management. You need new frameworks for everything from quality control to risk management.
Pros: Companies that figure out AI management first will have a massive advantage; this validates investing in new processes and training; new career opportunities are opening up in AI oversight.
Cons: Your current management practices probably won't work; you need to invest in training and new systems; you might fail while learning how to manage autonomous AI; customer experience could suffer during the transition.
What CX Leaders Should Do Next:
• Honestly assess whether your current oversight can handle AI that makes autonomous decisions
• Start developing quality assurance specifically for AI systems
• Train your managers on what's different about managing AI vs. managing people
Source: MIT Sloan Management Review
💰 Quick hits:
• Thomson Reuters launched a bot that takes 10 minutes but eliminates errors—proving sometimes slower AI beats faster AI
• Banks are already using agentic AI at 70% adoption—they're moving from reactive to proactive customer engagement
• Simon AI is using real-time data like weather to create thousands of personalized campaigns automatically
🎯 Prompt of the Day
Title: AI deployment success measurement framework
You're helping me create a framework to measure whether our AI deployment is actually improving customer experience. For [YOUR AI INITIATIVE], develop a comprehensive measurement plan:
Step 1: Define baseline metrics before AI implementation (response time, resolution rate, customer satisfaction, employee efficiency)
Step 2: Identify leading indicators that show AI is working (usage rates, escalation patterns, first-contact resolution)
Step 3: Set up lagging indicators that prove business impact (customer retention, cost per interaction, employee satisfaction)
Step 4: Create feedback loops to track customer sentiment about AI interactions versus human interactions
Step 5: Build reporting that shows both operational efficiency and customer experience improvements
Focus on metrics that prove AI makes customers happier, not just operations faster.
CX Use: This framework helps you prove that AI investments are improving customer experience rather than just cutting costs, giving you data to support further AI initiatives or course-correct failing ones.
⚡ Try This Prompt
Calculate the ROI of our customer-facing AI by evaluating:
Step 1: Implementation costs including technology, training, and change management
Step 2: Operational savings from reduced handle time, fewer escalations, and improved first-contact resolution
Step 3: Revenue impact from faster response times, improved customer satisfaction, and reduced churn
Step 4: Hidden costs like customer frustration from AI failures or additional human oversight needed.
Create a simple before-and-after comparison showing total business impact.
Quick win: This calculation reveals whether your AI is actually paying for itself through better customer outcomes, helping you make data-driven decisions about scaling or adjusting your AI strategy.
💭 CX Note to Self
The best AI deployments don't just work—they prove they work with numbers that matter to customers.
👋 See You Tomorrow
AI isn’t theory anymore. The gap? Governance. Most teams can deploy; few can explain, audit, or course-correct. Advantage goes to those who can.
—Mark
💡 P.S. Want more prompts? Grab the FREE 32 Power Prompts That Will Change Your CX Strategy – Forever to start transforming your team, now. https://dcx.kit.com/32prompts