How Well Are Your Operations Teams Leveraging AI?
A scored profile of how your back-office and operations functions are actually using AI — from forecasting to exception handling to vendor management.
- A scored profile across 6 dimensions — see exactly where you're strong and where the gaps are.
- Your biggest opportunities, mapped to specific next moves.
- A personalized video walkthrough from Shawn (optional) — a real read on your results.
Most operations orgs don't lose ground on AI because the tools are bad — they lose ground because the leverage never compounds. Invoices get keyed in by hand, exceptions land in shared inboxes, vendor renewals catch the team off guard, and the forecast gets rebuilt from last quarter's spreadsheet. An honest read on operations AI leverage looks past the demos at what actually moves the back office: how much of the team's day is reclaimed from manual processing, how fast off-normal conditions get detected and routed, whether contract renewals get negotiated with data instead of memory, and whether the AI features your ERP already ships with are actually turned on.
This free assessment scores your operations org across six dimensions — forecasting and demand planning, exception handling, vendor and contract operations, document and data processing, workflow automation coverage, and tooling and standardization — and returns a clear leverage profile in about six minutes. It's built from 27 years of technology leadership across Fortune 500 and growth-stage companies — the same lens a fractional Chief AI Officer would bring to your first conversation about operational throughput, exception rates, and procurement ROI.
What operations AI leverage actually measures
Operations is a broad function — financial operations, supply chain, vendor management, procurement, real estate and facilities, internal IT operations — and the question isn't whether one corner has AI but whether the cross-cutting pattern holds. The assessment scores six dimensions independently so you can see where AI is already paying off and where the gaps are: Forecasting & Demand Planning (is AI shaping the numbers leadership runs on), Exception Handling & Process Anomalies (are off-normal conditions detected and routed by AI before humans notice), Vendor & Contract Operations (is AI in the loop on renewals, vendor scoring, and spend analysis), Document & Data Processing (do invoices, contracts, and structured data move through AI extraction instead of human keystrokes), Workflow Automation Coverage (which workflows have AI in the loop and how honestly that's been mapped), and Tooling & Standardization (do ERP-native AI features, RPA + AI hybrids, and vendor maturity add up to a coherent stack). The final question maps which operational workflows to automate first.
Why most operations AI investments underperform
The pattern is consistent across mid-market operations orgs: an ERP with AI features nobody turned on, a contract repository that nobody searches, a finance system that exports to Excel for reporting, and a procurement function running on calendar reminders and tribal memory. Each system captures partial data; none of them roll up to a single trusted view of operational throughput. Teams double-enter information, managers pull conflicting dashboards, and AI features inside the ERP stay disabled because no one owns them. The orgs that capture real value treat AI leverage as an integration and accountability problem first — connect two or three high-leverage workflows, prove the lift, and earn the right to roll out more. A leverage profile turns a vague AI ambition into a sequenced plan, and it tells you whether your constraint is tooling, integration, adoption, or decision speed.
What you get at the end
You'll see an overall Operations AI Leverage Score, a band that describes where you stand (from Pre-Foundation through Execution-Ready), a per-dimension breakdown, and a map of your highest-value automation opportunities across forecasting, exception handling, vendor operations, document processing, workflow automation, and tooling. From there you can request a personalized video walkthrough — a short, recorded read on your specific results and what a fractional Chief AI Officer engagement would do for your operations function. No generic sales deck.
Frequently asked questions
What is an operations team AI leverage assessment?
It's a structured evaluation of how much of your operations function is being amplified by AI today and where the biggest unreclaimed leverage is. Rather than measuring AI knowledge, it measures the practical workflows — forecasting, exception handling, vendor and contract operations, document processing, workflow automation, and tooling integration — that determine whether AI is moving operational throughput or quietly sitting as shelfware.
Operations is broad. Does this work for finance ops, supply chain, procurement, or facilities?
Yes — and that's the point. The dimensions are scored on the cross-cutting pattern that holds across financial operations, supply chain, vendor management, procurement, real estate and facilities, and internal IT operations. The questions are framed in language any back-office leader can answer regardless of which functional area they own, and the opportunity map covers the full surface area so you can flag the workflows specific to your function.
How is this different from an AI readiness assessment?
A general AI readiness assessment looks at the whole company's preconditions. This one is scoped to the things a COO, head of operations, CFO, or VP of procurement actually controls and is measured on: forecast accuracy, exception rates, renewal savings, document processing throughput, workflow automation coverage, and the AI features inside the operations stack. The questions, scoring, and opportunity map are framed in the language of operations — throughput, exceptions, spend, renewals, SLA — not generic AI strategy.
How long does it take?
About six minutes. It's 18 scored questions across six dimensions, two short financial-context questions, an engagement-pace question, and a final workflow-mapping question. Your progress auto-saves, so you can leave and resume without losing answers.
Who should take this?
COOs, heads of operations, CFOs, VPs of procurement, financial operations leaders, supply chain leaders, and senior operations executives weighing AI investment who want a clear-eyed read on where the leverage actually is — and what to fix first if the AI you've already bought isn't producing results. It's also useful for fractional COOs and PE operating partners scoping operations AI work for a portfolio company.
What do most operations orgs score?
Most operations orgs land in the Emerging Leverage or Pre-Foundation bands on the first run — usually because the AI features inside the ERP aren't turned on, exception handling still runs through shared inboxes, or the forecast is still a spreadsheet exercise. That's not a failing grade; it's a useful diagnosis, and it tells you where the next dollar of operations AI investment should go.