Agent Nation
What’s the term for transferring a case from an AI agent to a human when risk or complexity is high?
Escalation / human handoff
What’s the common name for using AI to draft first versions of emails, proposals, or reports?
Generative drafting (content generation)
What do we call personal or sensitive information that must be protected (names, IDs, health data)?
PII / sensitive data
What do we call a dedicated cellular network built for an enterprise site?
Private 5G (private mobile network)
What do we call the practice of building new skills so employees can work alongside AI tools and agents?
Upskilling / reskilling
What do we call tracking and reviewing an agent’s actions so you can see what it did and why?
An audit trail (agent observability)
What do we call a virtual model of a process used to simulate changes before applying them in real life?
A digital twin
When an AI model’s performance degrades over time because real-world data changes, what’s that called?
Model drift (data drift)
What’s the name for connecting multiple clouds and data centers with consistent policy and routing?
Multi-cloud connectivity (interconnect)
What’s the name for a cross-functional team that scales AI safely across the organization?
AI Center of Excellence (CoE)
What’s the name for giving an agent limited, time-bound access using tokens instead of a user’s password?
Delegated token-based access (e.g., OAuth)
In facilities and manufacturing, what do we call using sensor data + AI to predict failures before they happen?
Predictive maintenance
What do we call inputs intentionally designed to fool an AI model into making a wrong prediction?
Adversarial examples
In AI data centers, what do we call the high volume of traffic between servers inside the same facility?
East–west traffic
What do we call measuring AI success by business outcomes (speed, quality, revenue, risk), not just model accuracy?
Value-based KPIs (outcome metrics)
In a “manager–worker” multi-agent setup, what does the manager agent do?
Options:
Breaks work into tasks and delegates to specialists
In physical AI, where should decisions often be made to reduce delay for robots and machines?
Options:
At the edge (near the device)
If an AI tool relies on third-party plugins or models, what kind of risk increases?
Options:
Supply chain risk
Which architecture combines networking and security controls delivered from the cloud to users and sites?
Options:
Secure Access Service Edge (SASE)
When AI makes a recommendation, what should leaders keep clear to avoid confusion and risk?
Options:
Decision rights and accountability
What’s the safest way to let an agent run scripts or commands during a live demo?
Options:
Run it in a sandbox with limits and monitoring
Which is a better indicator of AI productivity than “hours saved” alone?
Options:
Cycle time + quality + risk reduction
What’s the best way to build trust in high-stakes AI decisions?
Options:
Transparency + monitoring + human oversight
For AI workloads, why is observability (metrics, logs, traces) important?
Options:
To detect performance issues and security anomalies quickly
Which mindset best supports long-term AI success?
Options:
Continuous improvement: monitor, learn, iterate