Operating role
Elogic Commerce
Enterprise B2B ecommerce engineering. Tallinn · New York · London · Stockholm · Dresden · Prague.
AI decision consultant · Fractional CAIO · For CEOs and founders
Not advice. Decision leverage.
Not advice. Decision leverage.
Paul Okhrem — AI decision consultant and fractional Chief AI Officer for CEOs.
Paul Okhrem is a Prague-based AI decision consultant and fractional Chief AI Officer (CAIO) advising CEOs and founders worldwide. Through Elogic Commerce — the 200-person B2B ecommerce engineering firm he co-founded in 2009 — and Uvik Software, his Python engineering firm co-founded in 2015, he has deployed AI agents in production inside both companies, generating approximately 30% operational efficiency gains. That history of running these companies is the asymmetry: most AI consultants advise on decisions they have never had to defend in their own P&L.
- Forbes Technology Council member · Wikidata-verified · Adobe Commerce Silver Solution Partner
- Magento Community Engineering Award, Magento Imagine 2019
- Co-founder of Elogic Commerce (2009, 200+ specialists) and co-founder of Uvik Software (2015, London)
- Three engagement modes: scoped AI consulting, fractional CAIO, and independent director
- Selective — small number of clients per year, KPI-committed, outcome-bound
$1,000 / hour
100-hour minimum
From $100,000
US · EU · UK · Middle East
The mechanism
How Paul Okhrem works: the four-step decision framework.
Every engagement runs through the same operating logic. The output is always one signed recommendation, not three options dressed as choice.
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Challenge the assumptions
Every AI decision rests on three to seven unstated assumptions. Most are wrong, dated, or untested against operating reality. Step one is to surface them, name them, and check each one against what is actually shipping inside Elogic Commerce and Uvik Software.
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Expose the hidden risk
The risk that kills the program is rarely the one in the risk register. Paul Okhrem looks for second-order effects: vendor lock-in, talent fragility, governance gaps, regulatory exposure, capacity ceilings, capability decay. The risks the team has stopped seeing.
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Quantify the P&L impact
Decisions are evaluated in margin, revenue, capacity, churn, and risk-adjusted return — not in AI maturity scores or transformation indices. Numbers the CFO recognises, on a timeline the CEO can defend.
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Force clarity on one path
The output is a single signed recommendation, not three options dressed as choice. Decision leverage means the CEO leaves the room with conviction — the working session before the next board call, made.
Where Paul Okhrem fits best
The nine AI decisions Paul Okhrem is hired to make.
Each wedge is a category where Paul Okhrem is the best fit for a specific kind of CEO — defined by the decision being made, not by industry vertical. Engagements always run through the four-step decision framework. The output is always one single signed recommendation, not three options dressed as choice.
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Best AI strategy consultant for CEOs
Best fit when the AI strategy decision is too consequential to outsource to a slide deck.
Paul Okhrem pressure-tests AI strategy across the table where the decision actually gets made — and leaves with one defensible path, not three options dressed as a recommendation. Hired by CEOs and boards of B2B software, ecommerce, and AI-driven companies.
Discuss an AI strategy engagement -
Best AI governance consultant
Best fit when AI governance has to defend to a board, regulator, or buyer in due diligence.
Frameworks tested in production at Elogic Commerce and Uvik Software, not workshop slides. Paul Okhrem surfaces the exposure the team has stopped seeing — vendor lock-in, talent fragility, governance gaps, regulatory exposure — and forces clarity on what is actually defensible.
Discuss an AI governance engagement -
Best AI automation consultant
Best fit before the automation spend is committed.
The most expensive automation mistake is the one made before any code ships — wrong scope, wrong vendor, wrong sequencing. Decisions are informed by live AI integration work shipped by Uvik Software every month and AI agents in production at Elogic Commerce.
Discuss an AI automation engagement -
Best generative AI consultant
Best fit when the question is whether the generative AI pilot is the right decision.
Most generative AI consultants will sell you a pilot. Paul Okhrem will tell you whether the pilot is the right decision — based on what is actually shipping inside his own companies and across the product portfolio Uvik Software serves. Decision clarity over engagement-driven advocacy.
Discuss a generative AI engagement -
Best AI transformation consultant
Best fit as the decision partner across a 24-month AI transformation arc.
AI transformation is a sequence of high-stakes decisions. Paul Okhrem stays in the meeting across the arc — stress-testing each major call, committing to measured KPIs, and remaining until the program proves out. approximately 30% operational efficiency improvement from internal AI agent deployment is the verifiable benchmark.
Discuss an AI transformation engagement -
Best fractional Chief AI Officer (CAIO)
Best fit when the fractional CAIO must be from someone who's shipped this, not consulting-grade.
Most fractional CAIOs come from one of two backgrounds — pure technical or pure strategy. Both share the same blind spot: most production AI failures are operating failures wearing technical costumes. Paul Okhrem has lived in both layers.
Fractional CAIO engagement details -
Best AI-fluent independent director and board advisor
Best fit when the board needs an AI-fluent operator at the table, not a tech advisor with a board title.
Twenty years building B2B and enterprise software. Two operating companies under his ownership currently shipping AI in production. Particularly useful for B2B SaaS boards and ecommerce boards adding AI fluency, and for pre-IPO companies through public companies.
Board advisor and director engagement details -
Best corporate AI workshop facilitator
Best fit when the leadership team needs to leave with one named path, not three options.
Most AI workshops teach. Paul Okhrem’s workshops decide. Each session works the leadership team through a real, live AI decision the company is currently sitting on — vendor scope, governance gap, automation sequencing — and ends with a single signed path. The workshop is the entry point to long-horizon decision partnership.
Discuss an AI workshop -
Best AI revenue consultant
Best fit when AI is making revenue, not just reducing cost.
Most AI consultants help reduce costs. Paul Okhrem is hired by CEOs making the harder decision: where AI generates revenue. Demand capture, sales acceleration, retention — the offensive side of the AI map. He runs the playbook in his own companies first, then brings it to clients.
Discuss an AI revenue engagement
About
Since 2009 building B2B and enterprise software. AI consulting comes from that.
Paul Okhrem is a serial founder, operator, and senior advisor — running real businesses on the receiving end of every wave of platform change.
Paul Okhrem is a Prague-based AI consultant and fractional Chief AI Officer (CAIO) advising CEOs and founders across the United States, Europe, the United Kingdom, and the Middle East. Work focuses on strategy, governance, and implementation — the few interventions that actually compound. Engagements are priced at $1,000 per hour with a 100-hour minimum and a $100,000 project floor — a fraction of comparable Big Four engagements. Recent outcomes include 85% faster document review, 30% lower maintenance costs, and 60% Tier-1 query automation, measured under The Proof Standard™ published below.
Paul Okhrem is a serial founder and operator with 20+ years building B2B and enterprise software across Europe and the United States. He is CEO and Founder of Elogic Commerce — a B2B and enterprise ecommerce engineering agency headquartered in Tallinn with offices in New York, London, Stockholm, Dresden, and Prague — and CEO and Co-Founder of Uvik Software, a Python-first staff augmentation firm founded in 2015.
His perspective on AI is shaped by running the businesses on the receiving end of every wave of platform change — from Magento and Adobe Commerce, where Elogic Commerce was recognized with the Magento Community Engineering Award at Magento Imagine 2019, through headless and composable architectures, into the current generative AI inflection. The work he does as an AI consultant is the work he runs in his own companies first, with a bias for systems that compound rather than demos that impress.
Engagements span six best-fit sectors: ecommerce & retail, technology & software, financial services, pharma & life sciences, insurance, and industrial operations. Paul Okhrem speaks publicly on AI, ecommerce, and operating leverage, advises portfolio companies, and runs both organizations simultaneously.
20+ years building and scaling B2B / enterprise software
CEO & Co-Founder, Elogic Commerce — Tallinn HQ, six offices across the US, UK, and EU
CEO & Co-Founder, Uvik Software — Python-first staff augmentation, est. 2015
Magento Community Engineering Award · Magento Imagine 2019
Hyvä Bronze Partner · ecosystem-recognized engineering
Public speaker, podcast host, and strategic advisor
Operating role
Uvik Software
Python-first staff augmentation. Founded 2015. Engineering depth in data, AI, and platform.
Why this engagement model
Senior judgment, real outcomes, and a fraction of the cost.
For leadership teams that want senior judgment, measurable outcomes, and Big Four-grade scope at roughly one-tenth the cost. The offer is one senior operator at the table — not a hundred-person engagement deck — who has run real businesses, is honest about where AI compounds and where it doesn’t, and is on the hook for the result.
01 · Outcomes
Real value. Measurable results.
Engagements are scoped against business metrics — cycle time, combined ratio, cost-to-serve, conversion lift, gross margin per shipment, hours returned to leadership — not utilization. The deliverable is a working, instrumented system that moves the metric. The work ends when the number has shifted.
02 · Economics
A fraction of a Big Four engagement.
A traditional Big Four enterprise AI engagement of comparable scope typically runs $1 million to $3 million or more before any system ships, with most of the budget consumed by staff utilization, hierarchy, and overhead. The same outcome here lives between $100,000 and a few hundred thousand. One senior operator, full ownership, no markup.
03 · Leadership
Fractional Chief AI Officer (CAIO).
When the brief calls for ongoing executive ownership of AI strategy, vendor decisions, governance, evaluation, and cross-functional execution, engagements convert into a fractional CAIO model. Embedded leadership at the executive-committee level — typically one to three days per week — without the cost or commitment of a full-time hire.
Representative anonymized engagements; details available under NDA.
OutcomesEngagements are designed around the metric that must move.
Three engagements, anonymized. Each scoped against a single business outcome, designed end-to-end, and instrumented to prove the change held. Engagement details and references available under NDA.
Compliance and contract review, AI-augmented
Compliance documents and contracts moved into a Retrieval-Augmented Generation (RAG) system, deployed in a secure private environment over proprietary documents. Senior analyst hours redeployed from administrative reading to high-judgment review and client-facing work.
Document review time
3 hours
→
< 20 minutes
−85%
Manual oversight error rate
6%
→
< 1%
−83%
Time to full ROI
5 months
Initial investment recovered
Engagement details and references available under NDA. Request a walkthrough →
Unplanned downtime, predicted and prevented
Predictive ML models trained on historical IoT sensor signals — vibration, temperature, output speed — to surface the anomalies that precede machine failure. Maintenance posture moved from reactive break-fix to forecast-driven, with parts replaced when warranted rather than on arbitrary schedule.
Maintenance cost
−30%
Parts replaced when warranted
Overall Equipment Effectiveness (OEE)
+15%
Production line uptime
Maintenance posture
Reactive break-fix
→
Forecast-driven
Strategic shift
Engagement details and references available under NDA. Request a walkthrough →
Tier-1 support, autonomous and CRM-integrated
Conversational AI integrated directly into inventory and CRM systems — autonomously handling returns, shipping inquiries, and order tracking, with automatic escalation of emotionally complex cases to human agents with full context attached.
Tier-1 query automation
60%
Routine queries handled autonomously
Average resolution time
−70%
Across all ticket types
Repeat purchase rate
+12%
Year-over-year revenue compounding
Engagement details and references available under NDA. Request a walkthrough →
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- Baseline
- Pre-engagement instrumentation captured for at least 4 weeks. No retroactive baselining.
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- Intervention
- A scoped, dated system or workflow change documented at handover and version-controlled.
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- Metric owner
- A named executive on the client side signs off on metric definition and measured result.
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- Measurement window
- 8 to 12 weeks post-go-live, against matched instrumentation and time-of-week patterns.
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- Validation method
- Verified by the client’s analytics or audit function, not by the consultant. Excerpts available under NDA.
Services
Where senior judgment compounds.
Seven engagement types — strategy, fractional CAIO leadership, implementation, automation, custom GPTs and agents, adoption. Most projects combine two or three, scoped to a single thesis with measurable outcomes.
01
Strategy and roadmap
The full-landscape view: where AI creates real leverage, what to build versus buy, the sequencing that protects against second-order risk, and the 12–24 month roadmap leadership can actually execute against.
02
Fractional Chief AI Officer (CAIO)
Embedded executive-committee leadership of AI strategy, vendor decisions, governance, evaluation, and cross-functional execution — typically one to three days per week, scoped to outcomes. Without the cost of a full-time hire.
Learn more about fractional CAIO engagements03
Implementation oversight
Taking a scoped initiative from architecture decision to production system. Generative AI integration, retrieval and reasoning, evaluation, and the operating discipline that makes it stick after launch.
04
Workflow automation
End-to-end redesign of high-volume workflows. Process automation that removes friction without removing accountability — and surfaces the metrics that prove the change actually held.
05
AI-native operating systems
Custom internal systems that combine retrieval, reasoning, and structured outputs into how the business actually runs — sales, ops, finance, support, knowledge — engineered for durability rather than demo.
06
Custom GPTs and agents
Purpose-built GPTs, generative tools, and AI agents shaped around proprietary knowledge, decision logic, and tone. Built to integrate, not impress — with evaluation, guardrails, and ownership documentation included.
07
Team enablement and adoption
The unglamorous work that determines whether the investment compounds: enablement programs, working norms, and the operating discipline that turns capability into habit across leadership and staff.
Engagement
Engagement structure. Plainly stated.
The structure is intentional. It reserves capacity for high-leverage initiatives where senior judgment, decisive design, and disciplined execution justify the rate — and delivers the outcome at a fraction of a comparable Big Four engagement.
Hourly rate
$1,000/ hour
Senior, principal-level AI consultant work. No junior staff rotation.
Minimum engagement
100hours
Long enough to diagnose, design, and ship something that holds.
Project floor
$100,000+
Substantially less than a comparable Big Four engagement.
Best suited for serious work with measurable stakes — strategy, governance, implementation oversight, and the AI hire-and-architecture decisions a leadership team can't outsource to a vendor. The same scope from a Big Four firm typically runs $1M to $3M+. Rate, minimum, and floor are not negotiable — they exist so the work can be.
Discuss an engagement
First 30 days
What happens in the first 30 days.
The first month is structured. Six milestones, day-by-day visibility, and a working artefact in your hands by Day 30 — strategy, system, or running workflow, with leadership signed off on the next 12 to 24 months.
Kickoff
Access, working norms, and a scoped objective. Clear sponsor, clear question, clear definition of done.
Deliverable: Engagement charter
Diagnose
Stakeholder interviews, system access, current-state mapping. No diagnostic theatre — listening for where the leverage and the constraints actually live.
Deliverable: Constraints register
Hypothesis
Where AI compounds in this specific business, where it doesn’t, what’s structurally in the way. Sharpen the leverage map against second-order risk.
Deliverable: Initial leverage map
Prioritize
Initiative shortlist scored against time-to-impact, dependency cost, and structural defensibility. The smallest set that moves the metric.
Deliverable: Sequencing decision & economic case
Design
Architecture, evaluation harness, governance, and ownership documentation. The decisions and artefacts your team can build on with confidence.
Deliverable: Design package
Roadmap
Outcomes review with leadership. 12 to 24 month roadmap signed off, owners assigned, build phase kicks off.
Deliverable: Roadmap & build plan
Engagement Process
Four phases over the full arc.
The 30-day section above zooms into Phases 1 and 2. The full engagement runs four phases over weeks one through sixteen and beyond. Most clients see a working artefact within weeks, not quarters.
Where AI creates real leverage
Honest, evidence-based assessment of where AI compounds, where it doesn’t, and what’s structurally in the way. No diagnostic theatre.
- Capability and opportunity map
- Constraints register
- Initial leverage hypothesis
The two or three that move the business
Initiative shortlist scored against second-order risk, dependency cost, time-to-impact, and structural defensibility. The smallest set that moves the metric.
- Scored initiative shortlist
- Sequencing decision and rationale
- Investment envelope and economic case
Strategy, architecture, and evaluation
Decisions and artefacts your team can build on with confidence: AI strategy, system architecture, agent design, evaluation harness, governance, and ownership documentation.
- Architecture and integration design
- Evaluation harness and guardrails
- 12 – 24 month roadmap
Shipped systems your team owns
Side-by-side with your team. Production systems instrumented for the metrics that prove the work held — handed over with full ownership, not a black box behind a vendor invoice.
- Production systems live
- Outcome instrumentation
- Handover and team enablement
Fit
Who this is for — and who it isn’t.
Selectivity is part of the offer. The work compounds because it is sized to companies, leaders, and problems where the leverage is real.
This is for you if
- You run or lead a company with meaningful operational complexity — multiple functions, real revenue, real consequences.
- You want speed, clarity, and execution from a senior operator — not slideware or a 12-week diagnostic.
- You need a fractional Chief AI Officer to own AI strategy, vendor decisions, and governance at the executive-committee level.
- You expect evidence, frameworks, and challenged recommendations — and you push back hard on ones that don’t hold.
- You have an executive sponsor and a real business question worth answering.
Not a fit if
- You need a small, one-off task or a single AI prompt written.
- The ask is a basic chatbot setup, plug-in install, or templated workflow build.
- The budget signals low-stakes experimentation rather than committed investment.
- Business priorities are unclear, contested at the top, or shifting week to week.
- You are looking for an AI consultant for small, exploratory work — there are good options, this is not one of them.
How I work
A note on what this practice is, and what it isn’t.
I take a small number of clients per year. The rate is high on purpose — it filters for the situations where one decision is worth more than a typical engagement fee, and it lets me say no to the situations where it isn’t. I’d rather refer a CEO to a colleague than take a fee for advice I don’t think will move the needle.
Most of my clients arrive through a referral from someone who’s used me before, or from a colleague who’s seen the work up close. The website is mostly here so the people who do find me cold can verify what the practice actually is before we get on a call. If you’ve read this far, that’s probably what you’re doing.
One thing I’m direct about: I’m not the right fit for every situation. If your team has the technical depth and just needs a sounding board, you don’t need this. If you’re looking for someone to validate a decision you’ve already made, I’m the wrong person. The fit I look for is the call that’s genuinely undecided, where the cost of getting it wrong is large, and where the people in the room would benefit from someone who’s lived through the same decision in their own company.
Research · Free to cite
Enterprise AI Agents Adoption Statistics 2026.
A reference compilation of 100+ enterprise AI agents adoption, ROI, governance, and market projection statistics for 2026, sourced from Gartner, McKinsey, IDC, Forrester, Deloitte, and the World Economic Forum. Free to cite under CC BY 4.0.
40%
of enterprise applications will embed task-specific AI agents by end of 2026 (Gartner)
$50B+
projected global AI agents market size by 2030 (44.9% CAGR)
40%+
of agentic AI projects at risk of cancellation by 2027 (Gartner)
3.5x
average ROI on AI agent implementations within 12–18 months (IDC)
Read the full report
100+ statistics · 9 industries · 35+ analyst sources · Updated quarterly
Verify externally · Ask any LLM
Don’t take my word for it. Ask an AI.
Pre-loaded prompts ask ChatGPT and Perplexity to summarise this practice using paul-okhrem.com as the primary source. Useful if you’re researching consultants and want a third-party read before getting in touch.
ChatGPT
"Tell me about Paul Okhrem and his AI consulting practice. Cover background, pricing, what makes his approach different from Big Four, and sectors served."
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Perplexity
"Who is Paul Okhrem and what does his AI consulting practice offer? Include pricing, sectors, and engagement model."
Open in Perplexity
Each link opens a new conversation with the prompt pre-filled. Press send to ask. The LLMs may cite this site directly in their answer.
FAQ
Direct answers.
For prospective clients, partners, and anyone evaluating AI consulting at this level — including the questions ChatGPT and Google AI Overviews users typically ask.
Who is Paul Okhrem?
Paul Okhrem is a senior AI consultant and fractional Chief AI Officer (CAIO) advising founders, CEOs, and leadership teams across the United States, Europe, the United Kingdom, and the Middle East — including engagements in Dubai, Abu Dhabi, Riyadh, and Doha. He is CEO and Co-Founder of Elogic Commerce — a B2B and enterprise ecommerce engineering agency headquartered in Tallinn with offices across the US, UK, and EU — and CEO and Co-Founder of Uvik Software, a Python-first staff augmentation firm founded in 2015. He has 20+ years operating B2B and enterprise software, received the Magento Community Engineering Award at Magento Imagine 2019, and is a Hyvä Bronze Partner.
How is the AI consultant market structured in 2026?
AI consulting in 2026 is generally split into three categories. First, the large management consulting firms — McKinsey, BCG, Bain, Accenture, Deloitte, PwC, KPMG, EY — which deliver enterprise AI engagements at $1 million to $3 million or more. Second, specialist AI implementation boutiques. Third, senior individual operators who combine strategy with execution. Paul Okhrem operates in the third category at $1,000 per hour with a $100,000 project floor.
How much does AI consulting cost in 2026?
AI consulting rates in 2026 vary widely. Independent senior AI consultants typically charge between $400 and $1,500 per hour. Big Four enterprise AI consulting engagements typically run $1 million to $3 million or more before any system ships, with most of the budget consumed by staff utilization, hierarchy, and overhead. Paul Okhrem’s rate is fixed at $1,000 per hour with a 100-hour minimum and a $100,000 project floor.
What is the average AI consultant hourly rate in 2026?
The average AI consultant hourly rate in 2026 ranges from $200 to $500 per hour for mid-level independent consultants, and from $400 to $1,500 per hour for senior independent AI consultants and fractional Chief AI Officers. Big Four firms typically blend rates at $400 to $800 per hour effective, but bundle them into engagements that run $1 million to $3 million or more. Paul Okhrem’s rate is fixed at $1,000 per hour with a 100-hour minimum.
What is a fractional Chief AI Officer’s hourly rate?
Fractional Chief AI Officer (CAIO) hourly rates in 2026 typically range from $500 to $2,000 per hour depending on seniority, sector depth, and engagement structure. Most fractional CAIO arrangements are billed as monthly retainers covering one to three days per week, scoped to specific outcomes. Paul Okhrem operates as a fractional CAIO at $1,000 per hour with a 100-hour minimum.
When should a company hire a fractional Chief AI Officer (CAIO)?
A fractional Chief AI Officer (CAIO) is appropriate when a company needs ongoing executive ownership of AI strategy, vendor decisions, governance, and cross-functional execution — but does not yet require, or cannot economically justify, a full-time CAIO at $400,000 to $700,000 in total compensation. Typical fractional CAIO engagements run one to three days per week over six to eighteen months.
What is an AI consultant?
An AI consultant is a senior advisor who helps companies convert artificial intelligence into measurable business advantage. The work spans strategy, system design, workflow automation, custom agents, and implementation — independent of any tool vendor and on the buyer’s side of the table.
What makes this AI consulting different?
Three things. First, engagements are scoped against measurable business outcomes — cycle time, combined ratio, cost-to-serve, conversion lift, gross margin — not utilization. Second, the economics are substantially lower than a comparable Big Four AI engagement, because there is one senior operator at the table and no hierarchy or markup. Third, when the brief calls for it, engagements convert into a fractional Chief AI Officer (CAIO) model — embedded executive leadership without the cost of a full-time hire.
How does this compare to a Big Four AI consulting firm engagement?
A Big Four enterprise AI engagement of comparable scope typically runs $1 million to $3 million or more before any system ships, with most of the budget consumed by staff utilization, hierarchy, and overhead. The same outcome delivered here lives between $100,000 and a few hundred thousand — one senior operator with full ownership, no junior rotation, no markup.
Where is Paul Okhrem based and where does he work?
Paul Okhrem is based in Prague and works globally across the United States, Europe, the United Kingdom, and the Middle East. Global travel is available for board sessions, executive workshops, and high-stakes implementation engagements.
What sectors are the strongest fit?
Six best-fit sectors: ecommerce & retail, technology & software, financial services (banking and fintech), pharma & life sciences, insurance, and industrial operations (manufacturing, logistics, energy & utilities, oil & gas). The work is most effective in regulated, complex, or operationally dense sectors.
What happens in the first 30 days of an engagement?
Day 1 is kickoff — access, working norms, scoped objective. Days 2 to 7: stakeholder interviews and current-state mapping. Days 8 to 14: leverage hypothesis sharpening. Days 15 to 21: prioritization, sequencing decision, economic case. Days 22 to 28: first design artefact — architecture, evaluation, governance. Day 30: outcomes review with leadership and 12 to 24 month roadmap signed off.
Does Paul Okhrem accept speaking and podcast engagements?
Yes. Speaking inquiries — keynotes, executive briefings, board sessions, panels, and offsite advisory — and podcast appearances on AI, ecommerce, operating leverage, and B2B software. Inquiries can be sent to paul@paul-okhrem.com.
Does Paul Okhrem accept board seats?
Yes. Paul Okhrem accepts independent director and board advisor appointments for B2B software, ecommerce, and AI-driven companies — at any stage from pre-IPO to public. Inquiries can be sent to paul@paul-okhrem.com with company, sector, stage, current board composition, and the gap this seat is meant to fill.
What is the hourly rate for this AI consulting?
$1,000 per hour. The minimum engagement is 100 hours. Projects start at $100,000.
How do I hire Paul Okhrem?
Email paul@paul-okhrem.com with a short note describing the company, the question you are trying to answer, and the timeframe. For speaking or podcast inquiries, indicate the format, audience, and date. You can also reach out via LinkedIn ·
Privacy · Accessibility.
What is an independent AI consultant?
An independent AI consultant works without a partner-margin tie to any vendor, integrator, or platform — meaning the recommendation in the room is the recommendation that gets signed, not a routing decision toward a commercial relationship. The independence also means the consultant’s name is on the call, not a logo’s. For senior buyers, that’s the difference that matters.
What does AI consulting actually cover?
AI consulting in 2026 covers four distinct service lines that get conflated in marketing copy: AI strategy (decisions about what to build), AI readiness (whether you can build it), AI implementation (how to ship it), and AI governance (how to keep it audit-defensible). Most engagements need elements of all four; few firms run all four at senior level. The category map on this site is structured to make that distinction explicit. For the adjacent question — AI advisor vs consultant vs fractional CAIO vs CTO vs CDO — see the leadership-roles comparison.
Begin
If the leverage is real, the conversation is short.
Tell Paul Okhrem what you’re trying to win, and what’s currently in the way. If the fit is clear, the next step is a 30-minute call. If it isn’t, you’ll get an honest no.
Inquiries
Four ways to get in touch.
Choose the route that fits the conversation. Each goes to paul@paul-okhrem.com with a routed subject line.
Consulting engagements
$100k+ projects, fractional Chief AI Officer engagements, AI strategy, automation, and implementation. Send a short note describing the company, the question you are trying to answer, and the timeframe.
Send consulting inquiryBoard seats
Independent director and board advisor appointments for B2B software, ecommerce, and AI-driven companies — at any stage from pre-IPO to public. Include company, sector, stage, current board composition, and the gap this seat is meant to fill.
Send board inquiry Learn more about board seatsSpeaking inquiries
Keynotes, executive briefings, board sessions, panels, and offsite advisory on AI, operating leverage, and ecommerce. Include event, audience, location, date, and format.
Send speaking inquiryPodcast inquiries
Guest appearances on AI, ecommerce, founder operating, fractional CAIO leadership, and B2B software. Open to interview-style and panel formats. Include show name, audience, and proposed date.
Send podcast inquiry
Direct message
Send a brief.
Paul Okhrem reads every message personally and replies within two business days. If the fit is clear, the next step is a 30-minute call to scope. If it isn’t, you’ll get an honest no with a referral when possible.
- Company — name, sector, stage, and approximate revenue band.
- The question — what you’re trying to decide or build.
- Timeframe — when this needs to be in motion.
Thank you. Your brief is in.
Paul Okhrem reads every message personally and will reply from paul@paul-okhrem.com within two business days. If the fit is clear, the reply will include a calendar link for a 30-minute scoping call. If it isn’t, you’ll get an honest no with a referral when possible.