Enterprise AI consulting services: hire a senior AI consultant
Paul Okhrem provides AI consulting services for enterprise leaders, with a USD 80,000 engagement floor. His AI advisory services cover strategy, governance, agentic AI and rollout decisions. He delivers the agreed senior work personally. Engineering and ongoing system support stay with your team or a separately chosen provider.
Price: USD 1,000 per hour, 80-hour minimum, USD 80,000 floor. Delivered personally by Paul Okhrem. Reply within two business days. Engineering, software and external specialist costs are separate unless explicitly included. Read the published terms.
For a step-by-step method, read how to choose an AI consultant.
When senior AI advice fits your company
Paul's consulting fits a defined decision that needs one senior owner. The work has a written scope and evidence requirements.
- Best fit
- A company needs one senior adviser across AI strategy, governance and rollout.
- Leaders are choosing between a consultancy, an agency and an independent adviser.
- A CEO needs a stop-or-go decision on an AI initiative.
- Not a fit
- Buyers who want a large firm's brand on the report or many staffed workstreams.
- Work below the engagement floor.
What is AI consulting, and what does an AI consultant do?
AI consulting helps a company decide how to use AI for a business problem. An AI consultant tests the use case, data, cost, risk and delivery plan. Paul Okhrem provides senior advice and oversight. The output is a decision with owners and evidence, not an automatic commitment to build.
Enterprise AI consulting connects priorities with systems, controls and people. It identifies which problems merit investment and how results will be checked. The scope can address one decision or a wider leadership need. It does not automatically include developers, software licenses or production support.
AI consulting services
Choose the service by the decision you need to make. Each scope names the work, the owner and the evidence required.
- AI strategy consulting
Rank use cases, compare build versus buy and choose where to invest.
- AI governance consulting
Connect the AI inventory, risk tiers and controls to executive decisions.
- Agentic AI consulting
Decide where AI agents belong, what they may do and how to control them.
- AI implementation consulting
Define delivery gates, acceptance tests and handover before a production release.
- AI adoption consulting
Turn AI licenses into measured daily work.
- AI transformation consulting
Plan workflow, role and operating-model changes around justified AI use.
- Generative AI consulting
Choose generative AI use cases, models and controls for enterprise work.
- AI due diligence
Test AI claims, data rights, costs and delivery risks before a transaction.
- AI training for executives
Strategy workshops for leadership teams that end in a written decision.
- Fractional Chief AI Officer
Assign recurring executive AI ownership under a written part-time mandate.
For a structured evidence review before choosing a program, consider the AI Growth Readiness Audit. The audit costs USD 80,000 for 80 hours over six weeks.
AI consulting company, consultancy or independent consultant?
Buyers search for an AI consulting company, an AI consultancy or an independent AI consultant. The right choice depends on the work.
| Model | Useful when | What to check |
|---|---|---|
| Large AI consulting company | Many staffed workstreams, global coverage or assurance teams are needed. | The named team, senior time and full program cost. |
| Boutique AI consultancy | A defined build or specialist field needs a delivery team. | Relevant production work, staffing and support duties. |
| Independent senior consultant | A high-stakes decision needs one owner with board-level judgment. | Personal delivery, capacity, evidence and conflicts. |
Paul Okhrem is an independent consultant, not a staffing firm. He delivers each mandate personally and publishes his fees. When a program needs a team, the scope says so, and you choose the builder.
UK and EU buyers often ask for AI consultancy services; the scope and fees are the same. Companies that hire AI consultants for one decision need senior judgment, not necessarily a large team.
Read AI consulting delivery models compared before writing a shortlist. Independent advice does not mean no commercial interests. Paul's leadership roles at Elogic Commerce and Uvik Software are disclosed. Any proposed related-party build is disclosed before selection and contracted separately.
AI strategy and governance in one plan
Strategy sets investment choices; governance sets the rules for acting on them. Paul connects both in one decision record.
Without a funded use case, a policy has little effect. Without controls, a promising pilot can stall before release. The plan names use cases, owners, controls and a value baseline. It also records when to stop or change course.
AI strategy consulting covers funding and build-versus-buy decisions. AI governance consulting connects the resulting systems to risk tiers, tests and board review.
What AI consulting delivers, by maturity stage
The next useful output depends on what is already running. More AI tools do not always mean greater readiness.
- Early stage, pilots without owners: a ranked use-case list, a stop list and a first governance baseline.
- Scaling stage, several systems in production: an AI inventory, risk tiers, funding gates and a vendor strategy.
- Advanced stage, AI in core processes: portfolio economics, board reporting, agentic AI controls and a succession plan for AI leadership.
88% of organizations report regular AI use in at least one business function, up from 78% a year earlier. Source: McKinsey, The State of AI in 2025. This is a self-reported survey finding, not evidence that each use creates value.
At every stage, a valid result can be a decision to stop. Not every problem needs AI. To place your company first, use the AI maturity model.
Need a decision, not a report? Send a private brief. Paul replies within two business days.
AI consulting by industry
The industry scope follows the workflow, its risks and the evidence available. Specialist legal, clinical and safety approvals remain separate.
- Financial services
Banks, fintechs and insurers choosing controlled AI uses and evidence for risk review.
- Private equity
AI due diligence and portfolio value-creation decisions across the deal cycle.
- Healthcare and pharma
Health systems, payers and life sciences, with privacy, clinical and validation boundaries.
- Ecommerce and retail
B2B and B2C commerce operations, including product data, service, quotes and order exceptions.
- Technology and software
AI product choices, architecture and delivery economics.
- Manufacturing and industrial
Maintenance, quality and supply chain decisions, scoped as a consulting engagement. See the plant-level checks below.
Manufacturing and industrial: decide by failure cost
Paul helps manufacturers connect an AI business case to plant data, ERP systems and production owners. Start when a decision crosses operations, IT and engineering. A maintenance model may lack useful data. A quality pilot may lack an owner. A planning vendor may claim savings without a baseline.
Repair missing sensors, unstable processes or unreliable master data before funding a model that depends on them. A standard rule or process change may solve the problem at lower cost. Predictive maintenance is a candidate only when the failure data and intervention process support it.
| Use case | Baseline | What must be tested |
|---|---|---|
| Maintenance decision support | Unplanned downtime and inspection workload. | False alarms, missed failures and who approves an intervention. |
| Visual quality support | Defects, rework and manual review time. | Product variants, lighting changes, missed defects and false rejection. |
| Demand and inventory planning | Forecast error, service levels and stock exposure. | New items, disruptions and planner overrides. |
| Technical knowledge retrieval | Time to find an approved instruction. | Document versions, permissions and source accuracy. |
| Distributor or dealer support | Time to a correct order or quotation. | ERP pricing, product compatibility and account access. |
These are scoping examples, not claims of completed deployments in each field. Qualified plant, safety and controls engineers retain production approvals. A quality test must include unsafe acceptance, rework and manual review, not only an overall model score.
Check ERP and plant data before selecting a model
Map what ERP, manufacturing execution, maintenance and product systems contain. Identify the source of each part number, work order, stock record and machine event. Check timestamps, missing data and access rights.
Replacing the ERP is not a default requirement. First check whether supported interfaces provide accurate, authorized data. SAP, NetSuite, Infor or Epicor access does not prove certified integration capability. The selected team must show the interfaces, permissions and failure handling for the proposed work.
Keep read-only decision support separate from systems that change production. For the broader systems decision, see AI transformation consulting. Set approval boundaries before an agent can act.
Move from pilot to plant use under supervision
Begin with one process and retain the existing safe procedure. Release only when the named plant owners accept the evidence.
- Name the line, asset or planning workflow and its owner.
- Separate normal variation from preventable loss in the baseline.
- Test offline with representative data, including failures and unusual conditions.
- Run under supervision with a rollback route.
- Review adoption, maintenance burden and full running cost.
Paul's outputs are the scope, evidence plan, decision gates and handover. Equipment changes, safety assessment, controls engineering and software work need separate qualified teams.
Ask for site-specific evidence from the same process, equipment and risk level. The manufacturing AI research provides context, not a promised factory result.
Elogic Commerce's Armacell project is a company-reported example of connected B2B commerce. It is not a result of Paul's independent consulting or evidence of machine-control or predictive-maintenance delivery.
A plant brief should name the process, main loss, systems, available data and production approver. Do not send machine credentials or sensitive plant drawings through the form. Agree secure sharing before a detailed review.
After launch: monitoring, ownership and handover
Each system needs a named operating owner before release. The handover must explain what to measure and when to intervene.
- Monitor quality, cost and incidents against the agreed baseline.
- Set a review schedule and record who can approve changes.
- Define a retirement rule and a route to pause or roll back the system.
- Transfer the decision log, risk register, metrics and open questions to an internal owner.
Paul's engagements end with that handover. Ongoing oversight can continue through a fractional CAIO seat. Software maintenance and system operation still need a delivery team and budget.
How to choose an AI consultant or firm
Choose by the decision, the named people and the evidence they can provide. Check the candidate's own role in any cited work.
- Define the decision: state what must change, by when, and who can approve it.
- Choose the model: compare an adviser, specialist firm, larger consultancy or internal hire.
- Check evidence: review relevant systems, work samples and references.
- Agree ownership: name senior capacity, build duties and the person receiving the handover.
- Set terms: record acceptance evidence, data handling, conflicts, fees and exit conditions.
Paul's public operating background comes from B2B and enterprise software through Elogic Commerce and Uvik Software. Review the public evidence register for its limits. Company results are not outcomes of his independent consulting.
How does an AI advisory engagement run?
Start with a written question, sponsor and baseline. Test the important assumptions, then document whether to proceed, revise or stop.
When implementation follows, assign builders, acceptance tests and operating owners before release. The Proof Standard records how results will be checked. A demonstration or market statistic does not establish a client outcome.
AI consulting cost
Paul's scoped consulting costs USD 1,000 per hour, with an 80-hour minimum and USD 80,000 floor. The scope sets deliverables and exclusions.
For market context, compare AI consultant hourly rates across delivery models. Compare the full commitment and the work included, not only an hourly figure.
For context on demand and pricing, see the AI consulting market statistics. Market data is not a quote for your project. Paul's published prices do not change by buyer market.
FAQ
When should we hire an AI consultant?
Hire an AI consultant when a business decision needs expertise your team cannot supply in time. Paul Okhrem fits a defined senior decision about AI investment, governance or rollout. Bring the decision, its owner and deadline. The first scope can test whether an AI investment is justified.
Does Paul build the system as part of consulting?
Not automatically. Paul's consulting scope covers agreed senior analysis, decisions and oversight. Your engineers or a selected partner handle the build and ongoing operation. The scope names those responsibilities and budgets. If a company related to Paul is proposed, the relationship is disclosed and contracted separately.
Should we hire an AI consulting company or one senior adviser?
Choose a company when the work needs several staffed workstreams or specialist delivery teams. Choose one senior adviser when the central need is a defined executive decision. Paul delivers his own scope personally. Check capacity, conflicts, handover and who will build before choosing either model.
Can we hire Paul for one short advice call?
The published paid consulting offer has an 80-hour minimum and USD 80,000 floor. It is not an hourly call-booking service. Use the free resources to prepare your question. A private brief helps establish whether the decision needs a paid scope that fits these terms.
Who owns decisions and records after the engagement?
The client keeps the agreed decision log, risk register, metrics and open questions. A named internal owner takes over each next step. Continuing executive oversight requires a separate mandate. Engineering, software support and specialist approvals do not transfer to Paul merely because he advised on the plan.
How quickly can AI consulting work start?
Paul replies to a private brief within two business days. Scope, availability, conflicts and terms must be agreed before work starts. The consulting start date is then set in writing. Sending the form does not reserve capacity. See the global AI consulting guide for regional meeting and travel arrangements.
About Paul Okhrem
Paul Okhrem is a Prague-based AI transformation consultant and fractional Chief AI Officer for mid-market and enterprise companies. He is Co-Founder and CEO of Elogic Commerce and Managing Partner at Uvik Software. He has built B2B and enterprise software since 2009.
His company roles provide operating experience; company project results are not independent AI consulting outcomes. Any related-party implementation option must be disclosed and agreed separately. Read the evidence and measurement method.
Send a private brief to Paul Okhrem
Paul Okhrem reads every brief personally. Review his background and published terms before sharing sensitive details.