📅 December 17, 2025 | ⏱️ 4-min read
Good Morning!
☕ The Executive Hook
Google just made the “static menu” obsolete. We are moving from apps that force you to search to interfaces that build themselves the moment you ask. But while the tech gets smarter, a new McKinsey report drops a harsh reality check: 88% of companies are using AI, yet less than half are actually seeing a dime of profit from it. The “Hype Phase” is officially over.
🤿 The Deep Dive: The screen that builds itself
In this example, the agent decides to respond with a custom component containing an interactive chart and a custom component containing Google Maps.
The News: Google just launched A2UI. This is a new project that lets AI agents build the screen you see, right while you are using it.
The Context: For the last 15 years, we have built apps with menus, buttons, and forms. We hope customers can find what they need. Google is changing the rules.
Generative UI: Instead of a fixed app, the AI builds the interface based on what you say.
The Shift: Imagine a customer types, “I want to return these shoes and buy the red ones.” The AI doesn’t send a link. It instantly builds a mini-app with a “Return” button and a “Buy Red Pair” switch, right in the chat.
Why it matters: This is the end of “searching” for things.
No More Menus: Customers don’t have to dig through settings to find a refund button. The button appears because they asked for it.
Less Work: You don’t have to build a different page for every single problem. You build safety rules, and the AI builds the page for the customer in that moment.
Source: Google for Developers
📊 CX By The Numbers: The AI Value Trap: Adoption is High, but Enterprise-Wide Impact is Low
DCX Stat: While 88% of organizations globally report using AI in at least one business function (signaling near-universal adoption), only 39% of respondents attribute any measurable level of EBIT (Earnings Before Interest and Taxes) impact to its use at the enterprise level.
Takeaway: This challenges the assumption that broad AI adoption directly translates to business value. For most companies, AI is currently stuck in the “experimentation and pilot” phase, failing to deliver scaled, measurable, bottom-line financial impact in CX and other functions due to data readiness, governance, and scaling challenges.
Source: McKinsey Global Survey, “The state of AI in 2025: Agents, innovation, and transformation”
🛠️ The AI Toolbox: Training videos that don’t sleep
The Tool: Synthesia “Action” Avatars
The Pitch:
We’ve had talking heads for a while. Synthesia’s new update lets you create AI avatars that move, walk, and perform actions in a scene.
The CX Use Case:
Stop spending $50k on a film crew for your agent training videos.
Scenario: You need to train 5,000 agents on a new refund process by Monday.
Execution: Type the script, select an avatar, and have it walk over to a virtual screen and point at the specific button in your software.
Benefit: You can update the video in seconds when the software changes, rather than re-shooting the whole thing.
⚡ Speed Round: Quick Hits
The “Multilingual” Revenue: A new Frost & Sullivan report identifies Generative Multilingual Support as the #1 growth opportunity for 2026. If you aren’t using AI to support customers in their native language (without hiring native speakers), you’re leaving money on the table. Frost & Sullivan
Tui’s SEO Pivot: Travel giant Tui is shifting budget from Google SEO to “Generative Engine Optimization” (GEO). They are optimizing their content specifically to be found by chatbots (ChatGPT, Gemini) rather than search bars. CX leaders need to ensure their help centers are “bot-readable.” The Guardian
Amazon’s Pricing War: AWS just aggressively pushed its Amazon Connect pricing model, focusing on a “per-minute” rate that includes AI features. They are trying to undercut the expensive “per-agent” seat licenses of legacy CCaaS providers. Forbes
📡 The Signal
The theme for today is “The ROI Gap.”
We have the tools (Google’s generative screens, Synthesia’s active avatars), but we are failing the strategy.
The Reality Check: The McKinsey data proves that “adoption” is a vanity metric. If 88% of companies are using AI but only 39% see EBIT impact, we have a massive deployment problem.
The Fix: We are stuck in “Pilot Purgatory.” We are using AI for fun experiments rather than structural changes.
My challenge to you: Look at your AI projects. If the primary metric is “user engagement” or “innovation credits,” kill it. If it doesn’t have a direct line to lowering cost to serve or increasing basket size, it’s just a toy. The goal for 2026 isn’t to use AI; it’s to profit from it.
See you tomorrow!
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