AI Roll Ups Redefine Customer Experience
PLUS: Run an AI readiness audit on your CX stack and benchmark human vs. AI resolution quality
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Digital content is cheaper and easier to make than ever, but you still need two things: talent and AI-powered personalization.
Dojo Partners : AI Powered Content and Automated CX
🗓️ August 28, 2025 ⏱️ Read Time: ~5 minutes
👋 Welcome
Today’s AI headlines might sound like VC jargon - roll ups, agentic flows, vertical integrations - but they have real consequences for CX leaders. Because while everyone’s talking about the tech, the smartest companies are rethinking how the whole experience engine is built.
🔎 Signal in the Noise
AI in CX is shifting from “new tool” to “new operating model” built on trust, scale, and accuracy.
🎯 Executive Lens
This is your early signal: CX is becoming infrastructure. AI is being embedded deep inside service orgs, not just layered on top. Leaders who treat AI as a one-off add-on will miss the bigger game - platform consolidation, experience trust, and customer permission.
📌 Stories That Matter
🧠 AI investors are navigating ‘peak ambiguity’ by targeting CX service roll ups
General Catalyst’s Hemant Taneja says the next frontier for AI isn’t startups - it’s reviving existing service companies with AI under the hood. That includes contact centers, back-office operations, and field services. He warns of unintended consequences like job loss without reskilling, but makes it clear: CX isn’t being replaced - it’s being rebuilt.
Why this matters: CX leaders should expect their partners - from BPOs to tech platforms - to become AI-native whether they’re ready or not.
Try this: Look at your current vendor stack. Who’s best positioned to integrate AI, and who’s falling behind?
Source: Financial Times
🤖 Google builds AI Mode agents to automate customer support tasks
Google just launched “AI Mode” - a premium feature that uses its Gemini assistant to handle support tasks like reservations and FAQs directly inside third-party platforms. It’s part of their $250/month subscription, so this isn’t for the masses - yet. But it’s a hint at what embedded, seamless AI flows might look like.
Why this matters: Google is teaching customers to expect smart, invisible support without switching apps or waiting.
Try this: Pilot your own AI concierge flow in a single channel (chat, SMS, voice) to see where drop-off and delight meet.
Source: CX Today
📊 Almost half of US firms have deployed AI in CX personalization
A new study shows 49% of U.S. firms now use AI to power real-time personalization - especially in digital touchpoints. But only a smaller group report measurable ROI, usually when AI is tied to enterprise data and experience strategy - not just A/B testing headlines.
Why this matters: Personalization isn’t new, but AI makes it scalable. The catch? It only works when your data and orchestration layers are mature.
Try this: Map where your personalization efforts start and stop, then layer in predictive AI to close the gap.
Source: CMSWire
🛡️ Brands can win loyalty through responsible data use amid CX trust deficit
Consumers are willing to share data, but only when they feel safe. A new Press Ganey Forsta report found that trust in how brands handle data matters more than speed or even outcome. The biggest loyalty killer? Feeling manipulated or in the dark.
Why this matters: CX teams often focus on experience delivery - this reminds us that experience design must also include data design.
Try this: Build a “trust moments” map in your journey - where are you asking for data, and what reassurance are you offering in return?
Source: Business Wire
📈 Younger consumers embrace AI, but accuracy remains king
A Decagon survey found Gen Z is fine with AI-led support, but across every age group, what matters most is getting the right answer. Fast is good. Human is fine. But helpful wins. Nearly 70% said they’d pay more for exceptional support.
Why this matters: AI must deliver accuracy first. Novelty or generational savvy comes second.
Try this: Compare first-contact resolution rates between your AI flows and your human agents - and ask your customers what “exceptional” really means to them.
Source: Customer Experience Dive
✍️ Prompt of the Day
Build your CX AI readiness map
You are a CX technology advisor helping me assess our current platforms for AI readiness.
INPUT:
Here is a list of the tools we currently use in our CX stack:
[Paste your tools here, e.g., Salesforce (CRM), Zendesk (Support), Sprinklr (Social), Qualtrics (VoC), Ada (Chatbot)]
TASK:
For each tool, provide the following in a table:
1. Platform Name
2. Primary Use Case (e.g., CRM, ticketing, survey, chatbot, analytics)
3. Current AI Capabilities (none, basic automation, predictive, generative, agentic)
4. Personalization Depth (rules-based, machine learning, real-time)
5. Integration Level (siloed, partial, fully integrated with other CX systems)
6. AI Scalability (low, medium, high - based on current use and potential)
7. Risk/Concern (privacy, hallucination, model control, latency, compliance)
8. Recommended Action (retain, enhance, consolidate, replace)
OUTPUT:
A structured table with your analysis and a short executive summary of the overall AI maturity of our CX stack.
What this uncovers: Shows where you can build vs. buy vs. sunset.
Tactical benefit: Helps prioritize vendor consolidation and tech investments.
Where to test: Start with your top 5 CX platforms or partners.
🧪 Try This Prompt
Test AI accuracy versus humans
Act as a CX performance analyst.
You are comparing customer support performance between AI and human agents.
Given the following categories:
- Task type (e.g., password reset, billing question, account update)
- Channel (chat, email, phone, SMS)
- Resolution accuracy
- Handle time
- CSAT score
- FCR rate (first contact resolution)
- Escalation rate
Please generate a side-by-side table comparing:
- AI-only support
- Human-only support
- Hybrid (AI-assisted human agent)
Summarize key insights:
- Where is AI outperforming humans?
- Where do humans add unique value?
- What are hybrid models doing best?
- What should we scale, fix, or test next?
Use simulated data if no input is provided.
Immediate use case: See where AI is ready to take over, and where it’s not.
Tactical benefit: Builds confidence with data, not hype.
How to incorporate quickly: Start with low-stakes tasks and add voice of customer feedback.
🧭 CX Note to Self
AI that fumbles is worse than no AI at all. Don’t just ship fast - ship helpful.
👋 See You Tomorrow
Today’s stories weren’t about future hype - they were about present decisions. AI is being woven into the foundations of how we design, deliver, and scale experiences. Whether you're running a contact center, leading digital transformation, or advising execs on strategy - this shift is yours to shape.
So here's your challenge:
What’s one legacy system, team, or process in your org that could be radically improved - not replaced - by embedding AI in a smart way?
Hit reply and tell me where you're experimenting. Or forward this to your team and ask them the same question. Let’s get specific.
—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. 👉 FREE 32 Power Prompts That Will Change Your CX Strategy – Forever
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