01
Strategic posture
Should AI be in this business, in this function, at this time. Most posture failures are "we should use AI" without naming the decision AI is supposed to improve.
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AI workflow and governance review
AI Consulting for Workflows, Data Rules, and Decisions That Need Control
$10M+Paid media. Managed.
200+Shopify stores. Built.
300+Websites. Shipped.
+703%One campaign. Public.
9Case files. Documented.
Updated June 2026. Workflow. Data boundary. Human review.
Use this when AI ideas are piling up but no one has named the workflow, data boundary, review owner, or business result. SC names what should move, wait, or stop.
Reviewed by Stan Tscherenkow Last Reviewed June 7, 2026
Founded 2019
Roseville, California
Principal-led scope
buyer decision
AI consulting has to name the workflow, the data boundary, and the review owner.
Use this when the business needs AI to improve visibility or operations without losing human control. Stan Consulting connects search visibility, workflow, data boundaries, and owner review.
Key takeaways
What this page settles in one read.
- Decisions in writing, not slide decks or discovery calls.
- Five layers in the diagnostic: posture, boundaries, governance, integration, measurement.
- No vendor commissions. No platform partnerships. Independent recommendations.
- Entry at $999 (Conversion Second Opinion) for a single-decision diagnostic.
- Scales to AI System Build ($25K-$75K, 60-120 days) when end-to-end implementation is the move.
Offer clarity
What you can buy here.
AI Consulting is for operators with AI pressure but no clear workflow, data boundary, review rule, or business case.
The review decides which AI use cases should move, which need governance first, and which should stay out of the business process.
- Use-case map
- Workflow review
- Governance rules
- Owner handoff
The framework
The 5-Layer AI Decision Diagnostic.
02
Decision boundaries
Which decisions AI informs (advisory), which it owns (autonomous), which it stays out of (human-only). The boundary decision is the structural one most teams skip.
03
Governance and risk
Policy, access, audit trail. Who can use which tool with what data. The structural answer to the question regulators and clients will eventually ask.
04
Workflow integration
Where AI augments existing systems versus replaces them. Integration compounds; isolation stays manual.
05
Measurement and accountability
The number that says it is working, defined before the project ships. Without measurement, the project runs indefinitely on intuition.
The method behind every engagement
The SC Method™ · how this works
Stan Consulting reads a business situation across five layers. Every engagement starts here. The number anchors. The method extends.
- 01
Site
The page the buyer lands on, hierarchy and trust.
- 02
Account
Paid surface, funnel mechanics, structure, spend.
- 03
Numbers
Tracking, attribution, the actual revenue trail.
- 04
Offer
What is being sold, the price, the proof.
- 05
Follow-up
What happens after the click, the form, the call.
Step 01Send the URLs and the account access.
Step 02Stan Consulting reads the five layers.
Step 03You get the three things to fix first.
Visual diagnostic
The read follows the path from AI idea to controlled business decision.
AI work needs visibility, workflow, data boundaries, and human review. Stan Consulting checks where the business should be found, what should be automated, and what must stay controlled.
01Visibility signalHow the business appears in ChatGPT, Google AI, and AI search.
02Workflow signalWhere AI removes repeated work without creating risk.
03Governance signalWho reviews outputs, data, and commercial decisions.
Simple process
No maze. Three moves.
Use the intake path
Share the workflow, AI idea, data source, tool pressure, review concern, and business result the team is trying to improve.
Get the diagnostic
Stan Consulting reviews the situation and names whether the step is consulting, governance, automation, visibility, workflow build, or no AI at all.
Move on the fix
You get the next owner decision and implementation sequence without a vendor-led tool demo masquerading as strategy.
Decision lens
AI consulting vs. AI strategy vs. vendor implementation.
| Axis | AI Consulting | AI Strategy | Vendor implementation |
|---|---|---|---|
| What you receive | Decisions in writing across all 5 layers | Decisions on posture + boundaries only | Working systems and tool subscriptions |
| Independence | No vendor commissions, no platform partnerships | No vendor commissions | Vendor-aligned by design |
| Coverage | Posture, boundaries, governance, integration, measurement | Posture + boundaries (layers 1-2) | Tool deployment + training |
| Best when | Full advisory layer is missing | Strategy is the only gap | Decisions are made, execution is the constraint |
| Price | From $999 (CSO entry) to $75K (System Build) | Scoped after diagnostic for the 2-week engagement | $30K-$300K depending on platform |
| Output ownership | Buyer owns the decisions and the path | Buyer owns the strategy document | Buyer owns the integration and the lock-in |
| Time to outcome | 72 hours to 120 days depending on scope | 2 to 4 weeks for the strategy read | 30 to 180 days for working integration |
Why buyers trust the page
Clear scope before more spend.
The deliverable is the decision about where AI belongs. The tool that fits is named after the decision is named, not before.
Stan Consulting holds no platform partnerships and accepts no vendor commissions. The recommendation that pays the consultant is the only recommendation that exists.
The same person who reads the situation writes the decisions. No junior account team between you and the judgment.
Questions before contact
What buyers usually need to know.
Who should use this AI consulting step?
Use it when the business is trying to decide where AI belongs, what data it can touch, which workflow should change, and where human review cannot be removed.
What do we get?
You get use-case map, workflow review, governance rules, owner handoff, plus the next action that should happen first.
How much does it cost?
From $999 is the visible starting point or pricing band for this service. Variable work is priced after the asset, account, timeline, and owner involvement are clear.
How fast can this start?
Advisory engagement. Response comes through the intake path after the context is submitted.
Do we need a call first?
Not as the first move. Submit the situation first so the conversation starts with the real page, campaign, store, or decision instead of a blank sales call.
What if we already have an agency or internal team?
That is common. The work can review the current setup, direct the internal team, or define what the outside vendor should fix first.
How is this different from an AI strategy engagement?
AI Consulting covers all five layers: posture, boundaries, governance, integration, and measurement. AI Strategy is the upstream slice covering posture and boundaries only. Consulting is the right entry for most businesses; strategy alone fits when the rest is already decided.
Do you implement AI tools yourself?
Yes through the separate AI Workflow Build, AI Automation, and AI Visibility Build engagements. The consulting layer decides what to implement. Implementation is a separate paid scope so the decision layer stays independent.
What if the answer is "do not use AI for this"?
That is a legitimate output. Real consulting names what AI should stay out of, in writing, with the reason. A consultant who never returns a "no" is selling vendor adoption.
How fast can we start?
Single-decision diagnostic (Conversion Second Opinion, $999) ships in 72 hours after access is granted. Multi-layer engagements are scoped after intake through the AI consulting review request.
Is this for technical teams or business leadership?
Business leadership. The consulting layer is about decisions, not architecture. Technical implementation is downstream and steps to internal engineering or named build engagements.
External references
What the research says.
- Companies that scope AI use cases against a specific business decision report materially higher value capture than those organizing AI work by tool category. McKinsey · The state of AI in 2024
- AI value capture depends on the operating model around the model: who decides, who reviews, who owns the outcome. Harvard Business Review · Building the AI-Powered Organization
- Effective AI governance requires written policy, documented decision boundaries, and named accountability before deployment scales. NIST AI Risk Management Framework
- AI-readability of business entities is becoming a leading indicator of AI search citation and downstream commercial recognition. Stanford HAI · AI Index Report
This service answers these pains
If this sounds like the read, these pages are why.
Name the AI decisions before buying another tool.
Use the intake path when AI pressure is high but the workflow, data boundary, review owner, and business result are still unclear.
Start AI consulting review