AI in CX is moving from experimental to operational - from "will it work?" to "here's how it works.
PLUS: From readiness assessments to hybrid AI-human systems - prompts that turn real-world deployments into strategic implementation plans
DCX AI TODAY
🗓️ July 17, 2025 ⏱️ Read Time: ~5 minutes
👋 Welcome
Had an interesting conversation with a CX leader yesterday who said her team's finally stopped asking "should we use AI?" and started asking "how do we make our AI not suck?" Feels like we've all crossed that bridge together.
📡 Signal in the Noise
Yesterday's funding news dropped some serious signals: Former OpenAI exec Mira Murati just raised $2 billion for AI safety while customer service automation startups are securing millions for human-AI collaboration. The money's flowing toward solutions that work with people, not against them.
🧠 Executive Lens
The contrast is striking—while mega-rounds chase AGI moonshots, the real customer service wins are happening in the trenches. Companies building AI that makes human agents superhuman are getting the traction and the funding. That's where the sustainable value lives.
📰 Stories That Matter
🚀 AWS doubles down on AI agents with enterprise-grade toolkit
Amazon Web Services unveiled AgentCore yesterday, a comprehensive platform for deploying autonomous AI agents at scale. The new suite includes AgentCore Identity for secure authentication, AgentCore Gateway for API integration, and a marketplace where companies can buy pre-built AI agents. AWS is positioning itself as the infrastructure backbone for the shift from reactive chatbots to proactive AI agents that can handle complex workflows independently.
Why This Matters: AWS is betting that autonomous agents—not traditional chatbots—will define the next generation of customer service automation.
Try This: Map out your most complex customer service workflows and identify which could benefit from full automation versus human oversight.
Source: Amazon Web Services
💰 Mira Murati's AI safety bet commands $2B at $12B valuation
Former OpenAI executive Mira Murati's new startup Thinking Machines Lab raised an unprecedented $2 billion early-stage funding round led by Andreessen Horowitz, valuing the company at $12 billion despite having no product or revenue yet. The investment reflects massive confidence in Murati's vision for safer, more reliable AI systems. Chipmaker Nvidia and corporate backers including ServiceNow, Cisco, and AMD joined the round.
Why This Matters: The massive investment in AI safety signals that enterprise customers are demanding more trustworthy AI systems—exactly what customer experience needs.
Try This: Evaluate your current AI tools for safety, reliability, and explainability features that would be essential for customer-facing applications.
Source: Tech Startups
🤖 Unify raises $40M to deploy AI agents for sales teams
Unify secured $40 million in Series B funding to expand its AI agent platform that helps go-to-market teams automate prospect research, lead qualification, and customer outreach. The funding round demonstrates growing investor confidence in AI agents that can handle complex, multi-step business processes while maintaining human oversight and quality control.
Why This Matters: The success of AI agents in sales shows the template for how similar technology can transform customer service workflows.
Try This: Identify repetitive tasks in your customer service process that could be handled by AI agents while human agents focus on relationship-building and complex problem-solving.
Source: Tech Startups
🌐 Build Concierge raises $5.1M for AI-powered customer engagement
UK-based Build Concierge closed a $5.1 million seed funding round at a £35 million valuation for its AI-driven customer engagement platform that automates calls, chats, emails, and bookings for service businesses around the clock. The company's success highlights the growing market for AI solutions that can handle multiple customer touchpoints while maintaining service quality.
Why This Matters: The funding validates the market demand for comprehensive AI customer engagement platforms that work across multiple channels.
Try This: Audit your current customer touchpoints and identify opportunities to create a unified AI-powered engagement system that works 24/7.
Source: Tech Startups
📊 Package.ai nets $14M to revolutionize delivery operations and customer service
Package.ai, an AI-based platform that manages delivery operations and customer service, raised a $14 million Series A round led by Susquehanna Growth Equity. The company's platform unifies logistics and customer engagement, breaking the traditional trade-off between operational efficiency and customer experience. Customers include major retailers like Ashley Furniture and Yale.
Why This Matters: Package.ai's approach shows how AI can eliminate the false choice between efficiency and customer satisfaction by integrating operational and service functions.
Try This: Look for opportunities to integrate your customer service data with operational systems to create more proactive and informed customer interactions.
Source: Axios
✍️ Prompt of the Day
Title: The AI Agent Readiness Assessment
You are a strategic consultant evaluating our organization's readiness to deploy AI agents for customer service. Analyze our current capabilities and create a comprehensive readiness assessment:
[Insert details about your current customer service setup, team, and technology stack]
Please evaluate our readiness across these dimensions:
1. Technical infrastructure (1-10 scale with gaps identified)
2. Data quality and availability for AI training
3. Process standardization and documentation
4. Team skills and change management readiness
5. Customer complexity and interaction patterns
6. Regulatory and compliance considerations
For each dimension, provide:
- Current state assessment
- Required improvements before AI agent deployment
- Estimated timeline and resources needed
- Success metrics to track progress
Create a 90-day roadmap with specific milestones for becoming AI agent-ready.
What this uncovers: A realistic assessment of your organization's ability to successfully deploy AI agents rather than rushing into automation
How to apply it: Use this as a foundation for building a strategic AI implementation plan rather than tactical tool adoption
Where to test: Start with a pilot department or use case to validate the readiness framework before organization-wide deployment
🛠️ Try This Prompt
Acting as a customer service transformation strategist, help me design a hybrid AI-human system inspired by successful companies like Package.ai and Build Concierge. Create a framework that includes:
1. AI agent responsibilities and autonomous decision-making boundaries
2. Human agent responsibilities and escalation triggers
3. Seamless handoff protocols that maintain context and customer satisfaction
4. Performance monitoring system that tracks both AI and human effectiveness
5. Continuous learning loop where AI learns from human interactions
Structure this as a detailed implementation plan with these phases:
- Phase 1: Baseline measurement and system architecture (Weeks 1-4)
- Phase 2: AI agent deployment with full human oversight (Weeks 5-8)
- Phase 3: Graduated autonomy with selective human review (Weeks 9-12)
- Phase 4: Full deployment with continuous optimization (Weeks 13-16)
Include specific metrics for success, failure scenarios and rollback procedures, and training requirements for both AI systems and human agents.
Also provide a cost-benefit analysis framework that accounts for both short-term implementation costs and long-term efficiency gains.
Immediate use case: Build a sustainable AI-human collaboration model based on proven successful implementations
Tactical benefit: Avoid the pitfalls of pure automation while maximizing the benefits of AI augmentation
How to incorporate quickly: Start with one customer interaction type and expand based on measured success metrics
📎 CX Note to Self
"The $2 billion bet on AI safety isn't just about preventing robot apocalypse—it's about building AI that customers actually trust. That's the real competitive advantage."
👋 See You Tomorrow
The funding landscape tells a clear story: investors are backing AI that enhances human capabilities rather than replacing them. The companies getting this balance right are the ones building the future of customer experience.
That's it for today. Hit reply with your thoughts. 👋
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Have an AI‑mazing day!
—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