If you're a mid-market CEO or COO, you've probably been pitched AI solutions every week for the past year. AI chatbots, AI analytics, AI everything. Here's the problem: most companies don't need another AI tool. They need someone to tell them which tools actually matter and how to deploy them without creating chaos.

That's what AI consulting is. It's helping you figure out where (and if) AI fits into your business and building the systems to make it work.

This guide covers everything you need to know: what AI consultants actually do, the three main types of engagements, when hiring one makes sense, what to expect to pay, and how to avoid getting burned.

What is AI Consulting?

AI consulting is professional advisory and technical services that help companies assess, plan, and implement artificial intelligence initiatives. Unlike software vendors who sell specific AI tools, AI consultants are hired to solve business problems using AI. That could be strategy, governance, hands-on implementation, or all three.

AI consultants work across the full spectrum: from C-suite advisory ("Should we invest in AI?") to hands-on engineering ("Build us a lead generation automation system"). Most mid-market companies hire AI consultants because they lack internal expertise, need an external perspective, or want to move faster than they could by hiring full-time staff.

The best AI consultants start with your business goals, then work backward to identify where AI creates measurable value.

What AI Consultants Actually Do

AI consulting covers a wide range of activities depending on what stage you're at:

For Companies Just Starting:

• Assess AI readiness across people, process, technology, and data

• Identify high-ROI use cases specific to your industry

• Build strategic roadmaps with prioritised initiatives

• Design governance frameworks (policies, ethics, risk management)

• Educate executives and boards on AI opportunities and risks

For Companies Implementing AI:

• Design and build AI-powered systems (automation, analytics, predictions)

• Integrate AI tools into existing workflows and data infrastructure

• Evaluate vendor solutions and build vs. buy recommendations

• Conduct technical due diligence for AI investments or acquisitions

• Train internal teams to maintain and scale AI systems

For Companies Scaling AI:

• Embed with teams for long-term strategic and technical support

• Standardise AI approaches across departments or portfolio companies

• Build Centers of Excellence for internal AI capabilities

• Optimise existing AI systems for performance and cost

• Provide fractional AI leadership (CTO, Chief AI Officer roles)

The Three Types of AI Consulting Services

Not all AI consulting engagements look the same. There are three main models, each suited to different needs and timelines.

1. AI Advisory (Retainer-Based)

What It Is: Ongoing strategic support, typically structured as a monthly retainer for 6-12+ months. Think of it as hiring a fractional AI leadership team. You get strategy, governance, and accountability without the overhead of full-time employees.

Typical Deliverables:

• AI Audit Report (current state assessment + opportunity catalogue)

• AI Strategy Roadmap (0-6 months, 6-12 months, 12+ months phasing)

• Governance Framework (usage policies, vendor evaluation criteria, ethics guidelines)

• Monthly advisory sessions (2-4 hours) + ad-hoc guidance via email/internal chat

Who It's For:

• Companies with limited or no internal AI expertise

• Organisations exploring multiple AI use cases but unsure where to start

• Businesses that need both strategic direction AND accountability to execute

• PE firms standardizing AI across portfolio companies

Example: A global health and wellness company engaged us for AI and growth advisory. We conducted technical and strategic assessments, built and recommended a 12 month adoption and implementation roadmap, and helped prioritise investments. The retainer model allowed us to work with the entire company across departments systematically over 12 months.

Pricing: Monthly retainer with minimum commitment (typically 6-12 months). Investment level depends on resourcing, organisation size, number of stakeholders, and complexity of your AI landscape.

When to Choose Advisory: You know AI matters but don't know where to start. You need someone in your corner for the long haul.

2. Sprint-Based Projects (Fixed-Scope)

What It Is: Fixed-price, implementation or build project-based work for specific, well-defined AI challenges. These are 4-12 week engagements where you get a working system, a completed audit, or a strategic workshop. Then we hand it off internally, or discuss a maintenence engagement.

Common Sprint Projects:

• AI Transformation Roadmap: Assess current business state and processes to identify and scope high-impact projects

• Lead Generation Automation: Build systems that find, enrich, and route prospects automatically

• CRM Integration & Data Orchestration: Sync data across platforms, eliminate manual data entry

• AI Operational Efficiency: Recommend, build and implement operational pipelines to streamline busywork

• AI-Powered Analytics: Custom dashboards, predictive models, automated reporting

• Technical Due Diligence: Evaluate AI/ML systems before acquisition or major investment

• Executive Workshops: Half-day or full-day sessions on AI strategy for leadership teams

Who It's For:

• Companies with a specific problem and clear success criteria

• Organisations that can articulate the "what" even if not the "how"

• Businesses that need rapid delivery (4-12 weeks)

• Teams ready to own and maintain the solution after handoff

Example: A commercial real estate firm hired us for an 8-week Sprint project to automate their lead generation. We built a system integrating property data APIs, contact enrichment tools, and their CRM. Result: a fully automated prospecting and outreach engine, 10x increase in qualified pipeline, 100% reduction in prospecting time and fully automated meeting prep.

Pricing: Fixed-price based on project scope. Investment depends on complexity (number of systems to integrate, data volume, custom logic required) and timeline. Projects can range from workshops and technical audits through to complex multi-system integrations.

When to Choose Sprint: You have a clear problem, realistic timeline (4+ weeks), and internal capacity to maintain the solution long-term.

3. Embedded Engagements (6-12+ Months)

What It Is: Long-term team augmentation where AI consultants integrate with your team to deliver complex, multi-phase initiatives. You're not hiring contractors. You're embedding senior expertise directly into your operations.

Typical Engagements:

• Building internal AI/ML platforms from the ground up

• Implementing enterprise-wide automation across multiple departments

• Portfolio-level strategy and execution for PE firms

• Multi-product AI integration requiring sustained technical leadership

Who It's For:

• Companies making significant AI investments ($500K+ over 12 months)

• Organisations with multi-phase roadmaps requiring sustained effort

• Businesses building internal AI teams but can't hire fast enough

• PE firms needing shared AI resources across portfolio companies

Team Structure: Usually 1-2 SeidrLab team members embedded part-time or full-time. Common roles: Fractional AI Lead + Technical Delivery Lead, or Engineering Lead + rotating specialists.

Pricing: Monthly engagement based on team size and scope. Minimum 6-month commitment, typically 9-18 months for complex builds. Investment reflects the seniority and number of embedded team members plus the strategic value of the initiative.

When to Choose Embedded: You have a big, multi-phase initiative, you need strategic + technical execution, and you're committed to long-term partnership.

When Should You Hire an AI Consultant?

Not every company needs an AI consultant. Here are the scenarios where hiring external expertise makes sense:

✅ Hire an AI Consultant When:

1. You Lack Internal AI Expertise

Your team is smart and capable, but nobody has built AI systems before. An AI consultant brings proven patterns, avoids costly mistakes, and upskills your team along the way.

2. You Need to Move Fast

Hiring a full-time AI team takes 3-6 months. An AI consultant can start next week. If speed matters (competitive pressure, board mandate, market opportunity), external help accelerates timelines.

3. You Have Multiple Options and Need Guidance

You're evaluating 5 different AI vendors, considering a build vs. buy decision, or unsure which use case to prioritise first. Consultants provide an independent perspective without vendor bias.

4. You Need Both Strategy and Execution

Many companies can articulate "we need AI" but struggle to define what that means operationally. AI consultants bridge the gap between boardroom strategy and production systems.

5. Your AI Pilots Keep Failing

If you've tried AI initiatives that didn't stick, an external advisor can diagnose why. Wrong use case, poor data quality, lack of governance, inadequate change management. They can design a path that works.

6. You're Facing a Time-Bound Decision

Due diligence for an acquisition, RFP response requiring AI capabilities, or board deadline for AI strategy. Consultants compress timelines when you can't wait.

❌ Don't Hire an AI Consultant When:

You Don't Have Budget or Authority to Execute

If you can't commit meaningful budget and you don't have decision-making authority, save your money. AI consulting only works when you can act on recommendations.

You Just Want to "Learn About AI"

Hire a consultant to solve a problem, not to get educated. There are cheaper ways to learn: online courses, books, workshops.

You Expect Miracles Without Organisational Change

AI doesn't magically fix broken processes. If you're not willing to change workflows, train teams, or allocate internal resources, consulting won't help.

How Much Does AI Consulting Cost?

AI consulting pricing varies widely based on engagement type, scope, and consultant seniority. Understanding what drives cost helps you evaluate proposals and budget appropriately.

What Determines AI Consulting Costs?

Engagement Type

• Advisory retainers are ongoing monthly commitments (typically 6-12+ months)

• Sprint projects are fixed-price with defined scope and timeline (4-12 weeks)

• Embedded engagements are long-term team augmentation (6-18+ months)

Scope and Complexity

• Number of systems that need to integrate

• Volume and quality of data to process

• Custom logic and automation requirements

• Industry-specific compliance needs (finance, healthcare)

• Geographic requirements and data residency

Team Composition

• Principals and senior consultants command higher rates than junior staff

• Specialist expertise (ML engineering, enterprise architecture) costs more

• Team size (solo advisor vs. full delivery team)

• Level of hands-on delivery vs. strategic guidance

Timeline and Urgency

• Aggressive deadlines require more resources running in parallel

• Compressed timelines increase cost per deliverable

• Standard timelines allow for more efficient resource allocation

Your Organisation's Readiness

• Strong internal data infrastructure reduces discovery time

• Existing technical team that can collaborate accelerates delivery

• Clear requirements and decision-making authority prevents delays

• Legacy systems or technical debt increases integration complexity

Costs Beyond the Engagement Fee

Third-Party Software and Services

Some consultants include software licensing in their fee, others pass it through. Ask upfront whether the engagement fee covers tools like data platforms, API access, or cloud infrastructure.

Ongoing Maintenance and Support

Who supports the system after the consultant leaves? Options include:

• Retainer for ongoing consultant support

• Transition to internal team (requires hiring or training)

• Managed service arrangement

• Hybrid model (internal team with consultant backup)

Training and Knowledge Transfer

Critical for long-term success. Confirm whether the engagement includes:

• Documentation of systems and processes

• Training sessions for internal teams

• Transition period for handoff

• Post-launch support window

How to Evaluate Pricing Proposals

Red Flags:

• Consultant won't provide ballpark ranges before the first call

• Vague scope with no clear deliverables

• Junior consultants doing the work after senior person sells the engagement

• No discussion of post-engagement maintenance

• Fabricated urgency to sign a contract

Good Signs:

• Clear breakdown of deliverables and timeline

• Transparent about what's included vs. extra

• Discussion of risks and mitigation strategies

• References to similar projects with comparable scope

• Willingness to start with a smaller pilot before full commitment

The Right Question Isn't "How Much?"

Ask "What does this investment deliver in measurable terms?" A well-scoped AI consulting engagement should articulate clear ROI: time saved, revenue increased, costs reduced, risks mitigated.

If a consultant can't connect their fee to tangible business outcomes, keep looking.

AI Consulting vs. Hiring Full-Time: What's the Difference?

This is the most common question we hear. Here's the breakdown:

AI Consultant Advantages

• Speed: Start immediately vs. 3-6 month hiring process

• Lower Risk: No long-term employment commitment, easier to scale up/down

• Broader Expertise: Get a full team (strategy + technical + delivery) not just one person

• Proven Patterns: Consultants bring cross-industry experience and tested frameworks

• No Onboarding Overhead: They know what to do from day one

Cost Comparison: A full-time AI hire includes salary plus benefits, recruiting fees, onboarding time, and employment overhead. Consultants include a full team (strategy + technical + delivery) rather than a single specialist, with faster time to value.

Full-Time Hire Advantages

• Deep Context: FTEs build institutional knowledge over years

• Cultural Fit: Part of your team, aligned with company values long-term

• Lower Long-Term Cost: If you need AI support for 3+ years, FTE is cheaper

• Ownership: Internal teams own the roadmap and make faster decisions

The Best Approach: Hybrid

Many companies start with a consultant to build the strategy and initial systems, then hire full-time staff to scale and maintain. The consultant de-risks the investment and trains your first internal hire.

Example Hybrid Path:

1. Months 1-6: AI Advisory consultant builds strategy + governance framework

2. Months 4-9: Sprint project to implement first high-ROI use case

3. Month 7: Hire first internal AI lead (using consultant's assessment to inform role)

4. Months 10-18: Embedded consultant works alongside new hire to build internal capability

5. Month 19+: Transition to fully internal team, with consultant available for periodic advisory

For a detailed implementation roadmap, see The 4-Phase AI Adoption Framework.

How to Choose an AI Consultant: 10 Questions to Ask

Not all AI consultants are created equal. Use these questions to separate the pros from the pretenders:

1. "Can you show me 3 projects with specific, measurable outcomes?"

Look for measurable results: "10x pipeline increase," "$500K cost savings," "40% time reduction." Avoid vague claims like "improved efficiency."

For detailed guidance on evaluating consultants, see How to Choose an AI Consultant: The 2026 Buyer's Guide.

2. "Who will actually do the work?"

Beware the bait-and-switch. If the partner sells you, make sure the partner delivers. Not a junior consultant learning on your dime. If this is their model, ask to meet and interview the execution team before signing.

3. "What's your technical approach?"

AI consultants should be able to articulate their methodology. Do they have a repeatable framework, or are they building everything from scratch each time?

4. "What happens after the engagement ends?"

Good consultants plan for handoff from day one. Ask about documentation, training, and ongoing support options.

5. "Have you worked in our industry before?"

Industry experience helps, but isn't always required. Great consultants bring cross-industry patterns and adapt to your context.

6. "What's your stance on build vs. buy?"

Technology-agnostic consultants recommend what works. It's a red flag if they only push one vendor or platform.

7. "How do you handle scope changes?"

Fixed-price projects should have clear scope change order processes. Retainers should have flexibility baked in. Understand the process before you sign.

8. "What if this doesn't work?"

Transparent consultants discuss and identify risks upfront and have contingency plans. If they guarantee success, walk away.

9. "Can I talk to a reference client?"

Any reputable consultant should be able provide references on request. If they refuse, that's a red flag.

10. "What's your typical engagement timeline?"

Realistic timelines demonstrate experience. Beware promises of "AI transformation in 2 weeks."

For a complete evaluation framework with 10 critical questions and a scoring system, see How to Choose an AI Consultant: The 2026 Buyer's Guide.

What Makes SeidrLab Different?

There are hundreds of AI consultants. Here's why mid-market companies choose us:

1. Strategy + Execution in One Partner

We don't just hand you a PowerPoint deck and leave. We build the strategy with you, then implement it. No handoff gaps, no coordination overhead.

2. Boutique Expertise, No Junior Consultants

You work directly with partners who've built processes and systems for organisations like Domain, The Iconic, WeTransfer, and Weatherzone. Small team means senior attention on every engagement.

3. Transparent Pricing, No Surprises

Fixed-price Sprints. Clear retainer scopes. Transparent pricing ranges. We spell out what's included and what's extra before you sign.

4. Technology-Agnostic Recommendations

Our core stack prioritises what's cost-effective and scalable, but we adapt to your skills and environment. We've built with Google, Microsoft, Amazon, you name it. We recommend what works for you, prioritising your outcomes, not specific tooling.

5. Production-Grade from Day One

Every project starts from battle-tested patterns. You get enterprise-quality systems 30-50% faster than building from scratch. We don't re-invent the wheel, favouring off the shelf if it's faster and cost effective.

Frequently Asked Questions About AI Consulting

What's the difference between AI consulting and data science consulting?

AI consulting focuses on strategy, governance, and deploying AI tools to solve business problems. Data science consulting emphasises analytics, predictive modeling, and statistical analysis. There's overlap, but AI consulting is broader. It includes ML/AI systems, automation, and strategic advisory, not just data analysis.

Do I need existing data infrastructure to hire an AI consultant?

No. Part of an AI consultant's job is assessing your data readiness and helping you build the necessary infrastructure. That said, AI only works if you have data. Consultants can't create value from nothing.

How long does it take to see ROI from AI consulting?

Advisory engagements: 3-6 months to implement first high-ROI initiative identified in roadmap. Sprint projects: Immediate (system delivered in 4-12 weeks). Embedded engagements: 6-12 months as multi-phase systems go live. Quick wins can happen in weeks; transformational change takes quarters.

Can AI consultants work with our existing tech stack?

Yes. Good consultants are tool-agnostic and integrate with Salesforce, HubSpot, Microsoft, Google Workspace, AWS, Azure, and most modern platforms. They should assess what you have and build around it.

What if we decide AI isn't the right move for us?

That's a valid outcome. Honest consultants will tell you if AI isn't ready for your business yet, or if you can achieve the same outcome with spreadsheets. You'll walk away with a clear assessment and know when to revisit the decision.

How hands-on are AI consultants during implementation?

Advisory: Mostly strategic. 2-4 hours/month of scheduled sessions plus ad-hoc guidance. Sprint: Very hands-on. Consultants design, build, test, and deliver working systems. Embedded: Fully integrated. Consultants work alongside your team daily/weekly as part of your operations.

What happens if the consultant leaves mid-project?

Reputable firms have redundancy. Ask about team continuity and what happens if your lead consultant departs. For solo consultants, this is a real risk. Consider established firms for critical projects.

Next Steps: How to Get Started with AI Consulting

If you're convinced AI consulting makes sense for your business, here's what to do next:

Step 1: Clarify Your Goal

Write down the specific problem(s) you're trying to solve or the outcome(s) you want. Examples:

• "We need an AI strategy our board will approve"

• "Automate lead generation to grow pipeline 3x"

• "Evaluate whether to build or buy an AI analytics platform"

• "Streamline customer service with an AI chatbot"

The clearer your goal, the easier it is to scope the right engagement.

Step 2: Assess Your Readiness

Ask yourself:

• Do we have budget allocated for external expertise?

• Can we dedicate internal time for interviews, reviews, and feedback?

• Do we have decision-making authority to act on recommendations?

• Are we willing to change processes, not just add tools?

If you answered "no" to any of these, address those barriers first.

Step 3: Identify 2-3 Potential Consultants

Research firms with:

• Case studies in your industry or similar use cases

• Published pricing or transparent scoping processes

• Senior team members (not just junior consultants)

• Clear methodology or frameworks (not "we'll figure it out")

Step 4: Schedule Discovery Calls

Most consultants offer a free 30-60 minute discovery call. Use it to:

• Explain your challenge and desired outcome

• Assess their approach and expertise

• Understand pricing and timeline

• Determine cultural fit and communication style

Come prepared with your 10 questions (see "How to Choose" section above).

Step 5: Request Proposals

Ask your short list for proposals with:

• Detailed scope and deliverables

• Timeline with milestones

• Pricing (fixed or range) and payment terms

• Team composition (who will do the work)

• Success criteria and handoff plan

Compare on value, not just price. The cheapest option often costs more in the long run.

Step 6: Make a Decision and Commit

Choose a partner, sign the contract, and commit internal resources. AI consulting only works if you're all-in. Treat your consultant as a strategic partner, not a vendor.

Conclusion: AI Consulting is About Results, Not Hype

AI consulting done right is about identifying where AI creates measurable business value, then building the strategy, governance, and systems to capture that value.

The best AI consultants start with your business goals, your team's capabilities, and your appetite for change. Then they work backward to design an approach that fits.

If you're a mid-market company exploring AI, you don't need a 200-page report. You need someone to tell you the truth: where AI helps, where it doesn't, and what to do next. That's what AI consulting should deliver.

Ready to explore AI for your business? Contact us to discuss your specific challenge. No sales pitch. Just an honest conversation about whether AI consulting makes sense for you.

Related Resources

• The 4-Phase AI Adoption Framework for Mid-Market Companies

• How to Choose an AI Consultant: The 2026 Buyer's Guide

About SeidrLab

SeidrLab is a boutique AI consultancy helping mid-market companies ($1M-$100M ARR) turn AI from hype into measurable results. We combine strategic advisory with hands-on technical delivery across three service models: AI Advisory (retainer), Sprint-Based Projects (fixed-scope), and Embedded Engagements (long-term team augmentation). Our clients include professional services firms, real estate companies, private equity portfolio organisations, and technology businesses.