AI process audit with transparent business-case assumptions
In three weeks you receive a process map, prioritized use cases, financial assumptions, risks, and a roadmap. AI is evaluated together with data, architecture, and ownership, with no promise that it is always the first priority.
7–12 interviews · 3 weeks · 30–50 page report · transparent formulas · 2 weeks of support
Need leadership across the whole IT function, not only an AI audit? Explore the Fractional CIO service.
Fractional CIOMost AI rollouts end with a slide deck
Teams don't know where to start. Vendors sell LLMs as magic. Inside the company a dozen processes would save real hours — nobody maps them.
Hype before audit
Solutions are picked by tech, not by process. Implementation happens, impact doesn't.
No internal owner
Without a person who understands both business and architecture, the project stalls at pilot.
Metrics added later
ROI is estimated by feel. A year later there's no way to prove the investment paid off.
Three weeks. Seven interviews. One document that changes the trajectory.
I don't use the words «methodology» or «framework». Below — literally what happens on each day of the project, which artifacts come out at the end of each week, and where things can go wrong.
First 2 days — kick-off with the CEO (90 min) and collection of primary documents: org chart, products, IT landscape, revenue by line, key metrics. If documents aren't ready — we assemble them in a 1-hour joint call and I structure them myself.
Days 3–7 — a series of 7–12 45-minute interviews with leaders of commercial, ops, finance, IT and HR. Recorded (with consent), auto-transcribed, structured notes in a single template.
In parallel — read-only access to 1–2 key systems or screenshots/demo from the IT lead. I don't touch production data.
- 01Full transcript of all interviews tagged by topic
- 02Map of functional blocks with process owners
- 03Registry of identified pain points (typically 30–60 items)
- 04List of items that still need clarification
The main risk is unavailability of key people. If the CEO is in but the CFO is «busy with quarter close» — we reschedule, and I escalate to the owner on day one. Without interviews with key functions the audit makes no sense.
That's it. No magic, no black boxes. If any stage raises questions — happy to walk through it on a discovery call.
Not a presentation, but a decision package for launch
After the audit you keep working materials that help approve the budget, choose a vendor, and control implementation.
30–50 page report
Process map, bottlenecks, implementation priorities, risks, recommendations, and an executive summary for the owner.
Payback calculation
Open formulas: cost, expected effect, payback period, sensitivity, and assumptions behind the estimate.
Roadmap
What to launch in the first 90 days, what to plan for 6–12 months, and which dependencies and metrics to control.
Project launch package
Draft requirements, vendor selection criteria, integration risks, and questions to ask before signing the contract.
— what the company loses per year
Retail distribution, anonymized example: 7,000 active SKUs, 4 sales channels, average inventory of 120M ₽. Nobody is slacking — people heroically carry the process by hand. But money leaks in three places: manual analytics, stock-outs of best-sellers, write-offs and markdowns.
“Every Monday I spend half a day pulling stock numbers from three systems. By lunch they are already stale.”
Show the loss base calculation
| Loss source | Per year |
|---|---|
| Manual analytics (5 people × 10 h/wk × 1,800 ₽) | 4,644,000 ₽ |
| Margin lost to stock-outs | 6,912,000 ₽ |
| Write-offs and markdowns | 7,800,000 ₽ |
The base audit includes one 60–90 minute review of a selected initiative or draft technical brief within 30 days after handover.
A full independent review of the technical brief, budget estimate, and vendor proposal can be ordered separately before implementation starts.
From scattered data into a clean PIM record. In seconds.
A real task: a new product arrives from a supplier scattered across pieces — specs, certificates, regulatory marking, photos, target markets. All of it has to be merged into a single master-data record.
TechMontage Service LLC
Tax ID 7728456789 · +7 (495) 234-56-78
84/32 Profsoyuznaya St., Moscow
Commercial proposal No. CP-2026/318
dated May 14, 2026
Dear partners, please find below our quote
for component supply request
dated 2026-05-11:
1. SKF 6205-2RS1 radial bearing
240 pcs · RUB 487/pc excl. VAT
delivery lead time: 14 business days
2. Reinforced oil seal 25×42×7
500 pcs · RUB 92.50
in stock, shipment in ~3 days
3. 8205 thrust bearing, 80 pcs
price with 5% discount — RUB 1,124/unit
manufacturing lead time: up to 21 days
Payment: 50% advance, 50% on shipment.
Prices valid until 2026-06-30.
Delivery via Delovye Linii — paid by buyer.
Manager: Ivanov I.S.
i.ivanov@tehmontaj.ruExtracting and normalizing master data — seconds instead of manual entry. The review_required field marks places where the AI deliberately asks for human review (e.g. compliance of regulatory marking with the national track-and-trace system) instead of guessing.
Who the audit is for: four roles, four different AI questions
The same project is usually evaluated by several leaders. The audit translates AI opportunities into each role's language: economics, operational impact, architecture, and risk control.
Owner or chief executive
You need to know where AI can create financial impact, and where the team is simply chasing a trend.
Operations leader
Manual approvals and gaps between sales, warehouse, support, and finance consume management time.
IT leader
The business asks for AI, but there is often no brief, no data readiness, no architecture, and no vendor criteria.
Finance leader
ROI is estimated by feel, while implementation budget competes with other investment initiatives.
+Good fit if…
- Growing company or brand, 30–500 people
- Goal is ROI, not «trying out AI»
- You have processes and data: sales, support, logistics, document flow
- Decision-maker: founder / CEO / commercial director
−Not a fit if…
- You want a «magic chatbot in a week»
- Not a single process is digitized yet
- AI «because competitors have it», no real task
- Implementation budget under €10k
Describe your company and one process — I will come back with initial hypotheses on where AI can create value without a large project.
Checklist: 20 processes where AI can create value in a mid-market company
A practical shortlist for owners and functional leaders. It helps you see which processes are worth checking before buying platforms, hiring vendors, or funding expensive pilots.
The full version includes 20 processes, data-readiness signals, typical impact, and the first question to ask the process owner.
Where AI impact becomes visible fastest
Five mid-market business contexts with recurring manual work, documents, requests, and operational leakage. These are model scenarios for an audit: the numbers are calculated from your own data during the project.
Retail / online store
Retail impact is easy to express in money: sales, stock, write-offs, markdowns, product launch speed, and support workload.
Choose the closest business size — the cards will show a rough annual savings or revenue-uplift range for that scale.
Demand forecasting and replenishment
10–25% fewer stock-outs, 5–15% lower excess stock
RUB 2–8M/yr
Some products run out in stores while others sit in inventory and later move through markdowns or write-offs.
Forecasting by product, store, season, promotion, and stock position; recommendations for orders, transfers, and minimum stock.
Stock-outs, turnover, write-offs, markdown share, and working capital tied up in inventory.
Sales by product and store, stock levels, deliveries, write-offs, promotions, and 12–24 months of seasonality.
Product cards and storefront content
50–70% less time per product card
RUB 0.8–3M/yr saved + faster sales launch
New products take too long to reach the website or marketplaces because specs, certificates, photos, and descriptions are assembled manually.
An assistant prepares a draft product card, description, attributes, review questions, and a list of missing data.
Time from supplier materials to publication, manual edits, and the share of product cards with errors.
Price lists, specifications, certificates, photos, marketplace requirements, product master data, and edit history.
Customer support assistant
25–45% of requests resolved without an operator
RUB 1.5–7M/yr
Operators repeatedly answer questions about availability, delivery, returns, order status, and exchange rules.
An assistant connected to the knowledge base, orders, and stock answers routine questions and escalates complex cases to humans.
Share of requests handled without an operator, average response time, repeat contacts, and shift workload.
Support history, knowledge base, order statuses, return rules, inventory, and escalation reasons.
Choose an industry and company size, then request a calculation: I will come back with 2–3 hypotheses on which processes are worth checking first.
The numbers in these cards are preliminary discussion ranges, not a promised result and not a list of completed client cases. In the audit report, each scenario includes source data, calculation formula, implementation cost, risks, payback horizon, and a clear condition under which the project should not be launched.
Enter your assumptions — no result is shown until you calculate
This is an opportunity-sizing aid, not a payback promise. During the audit, assumptions are replaced with actual volumes, implementation cost, and sensitivity ranges.
Formula: employees × routine hours × 47 working weeks × hourly cost. Impact = 62% of that base plus recovery of 40% of an assumed 18% loss from error and rework.
Sensitivity: lower actual automation or recovery reduces savings proportionally and extends payback.
Do not start without a process owner, baseline data, a measurable success metric, and an acceptable integration and security approach.
No savings or payback result is shown before you click calculate. The 62%, 18%, and 40% values are explicit illustrative assumptions, not a forecast for your company.
Process map with AI implementation points
A fragment of a typical deliverable map. Nodes are processes, red rings are bottlenecks, numbered markers are AI recommendations.
- 01Map of 12–18 key processes with metrics
- 023–5 priority AI implementation points
- 03Technical solutions and stack per point
- 04Cost, timeline and risk estimates
- 05KPIs and a plan to measure impact
- 06A one-slide summary for the board
Questions before starting
What remains with the company after the audit?
A 30–50 page report, process map, use-case register, transparent financial model, risk assessment, 6–12 month roadmap, and vendor-selection materials.
Must the company implement AI after the audit?
No. A valid outcome may be to fix the process, data, architecture, or ownership first. Each initiative includes a condition under which it should not be launched.
Is production-system or personal-data access required?
Usually not. Process descriptions, aggregated measures, screenshots, and system demonstrations are normally sufficient. Any access model is agreed and minimized in advance.
Can another vendor implement the recommendations?
Yes. The package supports an independent vendor selection. A separate review of the specification, estimate, and vendor proposal is also available before launch.
How is the result accepted?
Deliverables, questions to be answered, and acceptance criteria are agreed before work starts. Commercial and legal terms are documented in the contract.
Determine whether you need an AI Audit or a broader IT diagnostic
Confidential. Response within 1 business day.