Chief Operating Officer
Risk & Business Continuity
What You Do Today
Ensure operational resilience — business continuity planning, supply chain risk management, operational risk assessment. You're the person responsible for keeping the company running when things go wrong.
AI That Applies
AI-powered operational risk monitoring that predicts disruption likelihood, models business impact scenarios, and monitors supply chain health indicators.
Technologies
How It Works
The system ingests supply chain health indicators as its primary data source. Predictive models weight dozens of input variables against historical outcomes, producing probability scores that rank cases by risk level. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context. The resilience planning decisions.
What Changes
Risk monitoring becomes predictive. The AI identifies that a critical supplier's financial health is deteriorating or that a weather system threatens multiple distribution centers.
What Stays
The resilience planning decisions. Which risks to mitigate, how much redundancy to build, and how to balance resilience against cost — those are strategic choices.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for risk & business continuity, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long risk & business continuity takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your board chair or lead independent director
“What's our current false positive rate, and how much analyst time does that consume?”
They shape expectations for how AI appears in governance
your CTO or CIO
“Which risk scenarios do we not monitor today because we don't have the capacity?”
They own the technology infrastructure that enables AI adoption
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.