AI Strategy Consulting

Stop Experimenting. Start Executing.

AI strategy consulting built for mid-market companies ($10M–$500M revenue) that need a prioritized roadmap, honest ROI projections, and a clear path from where you are today to working AI in production.

Start Your Strategy EngagementWhat This Produces
6–10
Weeks to Roadmap
4–8
Prioritized AI Opportunities
12–18
Month Implementation Plan
Board-Ready
Output Format

What This Is

AI Strategy Consulting for Mid-Market

AI strategy consulting for mid-market companies is a structured engagement that helps leadership cut through vendor hype, identify where AI can genuinely add value in your specific operations, and build a sequenced implementation plan that accounts for your organizational capacity, data readiness, and budget.

The mid-market context matters. Approaches designed for enterprise companies (multi-year programs, dedicated AI centers of excellence) don't fit companies with $10M–$500M in revenue. Neither do point-solution approaches designed for small businesses. Mid-market companies need a strategy that prioritizes ruthlessly — picking the 2–3 AI initiatives that will generate real ROI and doing those well, rather than spreading thin across every promising use case.

A well-executed AI strategy engagement produces three things: a ranked inventory of AI opportunities specific to your operations, a sequenced 12–18 month roadmap with owners, budgets, and milestones, and an organizational readiness assessment identifying what you need to fix before implementation begins (data gaps, talent gaps, process gaps).

This is different from a technology assessment (which evaluates your current tools) and from a vendor selection project (which evaluates options for a specific purchase). AI strategy starts with your business outcomes and works backward to what AI should do and how.

Ideal Clients

Who This Engagement Is For

Companies With AI on the Agenda, But No Plan

Leadership knows AI should be a priority. Board members are asking questions. But there's no internal consensus on where to start, what to buy, or how to sequence investments. This engagement produces that plan.

Past Failed AI Initiatives

You've invested in AI pilots that didn't scale, bought tools that aren't used, or hired for AI capability that isn't delivering. The strategy engagement includes root cause analysis and a reset with realistic scope.

PE-Backed or Acquisition-Stage Companies

Investors and acquirers increasingly require credible AI strategies. This engagement produces a board-ready AI roadmap with ROI projections that can withstand scrutiny.

Companies Facing AI-Enabled Competition

Competitors are using AI to undercut on price, speed, or service quality. You need to understand where you're at risk and where you can catch up or differentiate within 12–18 months.

Deliverables

What the Strategy Engagement Produces

AI Opportunity Inventory

A structured analysis of 4–8 AI use cases specific to your operations, with ROI estimates, implementation complexity ratings, and data readiness assessments for each.

Prioritized Implementation Roadmap

A sequenced 12–18 month plan with defined phases, owners, estimated budgets, and success metrics. Built to survive leadership scrutiny and budget reviews.

Organizational Readiness Assessment

An honest evaluation of where data quality, talent, and processes need to be improved before AI adoption can succeed — with specific remediation recommendations.

Vendor and Build vs. Buy Guidance

For each prioritized initiative, a recommendation on whether to buy a solution, build custom, or partner — with specific vendor options evaluated against your requirements.

Risk Register

A documented view of the key risks for each initiative: integration complexity, data gaps, change management requirements, and regulatory considerations.

Executive Presentation

A board-ready presentation that communicates the AI opportunity, prioritized roadmap, investment required, and expected returns in terms suitable for non-technical stakeholders.

Timeline

Strategy Engagement Timeline

Weeks 1–2

Discovery

  • Stakeholder interviews across business units
  • Process and workflow mapping
  • Current technology landscape review
  • Initial opportunity hypothesis
Weeks 3–6

Analysis

  • Data readiness assessment
  • Opportunity scoring and prioritization
  • Vendor and build options evaluation
  • ROI modeling for top opportunities
Weeks 7–10

Roadmap

  • Implementation roadmap development
  • Organizational readiness report
  • Risk register completion
  • Executive presentation and review

Engagement Model

How Pricing Works

Fixed-Fee Strategy Engagement

A defined 6–10 week engagement with fixed deliverables and a fixed fee. No hourly billing, no open-ended timelines. You know exactly what you'll get and what it costs. Scoped during an initial discovery call.

Duration: 6–10 weeks

Implementation Follow-On

Companies that want to proceed from strategy to implementation can engage us for a fixed-scope POC phase targeting the top-priority initiative from the roadmap. Most clients move directly from strategy to implementation to maintain momentum.

Typical start: 2–4 weeks post-strategy

Expected Outcomes

What Success Looks Like

Executive Alignment

Leadership consensus on AI priorities within the first 30 days of implementation

Roadmap Quality

Board-presentable AI strategy with ROI projections and implementation plan

Initiative Prioritization

Clear stack-ranked list of AI opportunities with rationale your team can defend

Readiness Gap Closure

Specific, actionable plan to close data and organizational readiness gaps

Implementation Launch

First initiative in development within 60 days of roadmap approval

ROI Visibility

Documented expected returns for top 3 initiatives with measurement plan

Honest Assessment

Risks and Constraints

Strategy Without Execution Commitment

An AI strategy that sits in a drawer delivers zero value. Engagements work best when there is genuine commitment to implementing the top-priority initiative within 6 months of roadmap completion. We discuss this upfront.

Stakeholder Availability

Strategy quality depends directly on access to the right people. Business unit leaders who are too busy to participate in discovery interviews produce weak requirements that lead to poor prioritization.

Data Readiness Surprises

Companies often overestimate the quality and accessibility of their data. When data readiness gaps are larger than expected, the roadmap may need to front-load data infrastructure work before AI initiatives can begin.

AI Hype Creating Unrealistic Expectations

Board members and executives exposed to AI marketing sometimes expect capabilities that aren't yet reliable in production. Managing expectations and ensuring the strategy is grounded in current realities is part of our role.

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FAQ

AI Strategy Consulting FAQ

Common questions about AI strategy engagements for mid-market companies

A well-executed AI strategy engagement produces three things: (1) a clear inventory of where AI can realistically add value in your specific operations, ranked by ROI and implementation difficulty; (2) a sequenced 12–18 month roadmap with defined milestones, owners, and budget requirements; and (3) an organizational readiness assessment identifying gaps in data, talent, and process that need to be addressed before AI adoption succeeds. You leave with a document that can go to your board or leadership team and a clear path to execution.
Mid-market companies face a distinct challenge: they're large enough that AI should be a strategic priority, but don't have the internal capability to evaluate vendor claims, sequence initiatives, or manage implementation risk without external expertise. Enterprise companies have Chief AI Officers and dedicated data science teams. Small businesses can start with simple point solutions. Mid-market companies need a structured strategic approach that fits their organizational complexity and budget.
Most mid-market AI strategy engagements take 6–10 weeks from kickoff to final roadmap delivery. The timeline includes: stakeholder interviews across key business units (2 weeks), process and data audit (2 weeks), opportunity analysis and prioritization (1–2 weeks), and roadmap development and presentation (1–2 weeks). We don't do multi-month strategy projects — the goal is to get to decisions and execution quickly.
We score opportunities on four dimensions: estimated ROI (revenue impact or cost reduction), implementation complexity (data readiness, integration difficulty, change management requirements), strategic alignment (how well it supports your stated business priorities), and time to value (how quickly you can see results). The output is a ranked list with clear rationale that your leadership team can debate and refine.
Yes. Most clients who engage us for strategy continue with an implementation engagement. We're intentional about this: the strategy is designed to be executable by us or by another team you choose. We don't create strategy documents that require our ongoing involvement to interpret. If you proceed with us, you get continuity — the same team that built the strategy executes against it.
AI vendor marketing significantly overstates what products can do in real production environments. Part of our value is translating vendor claims into honest assessments of what you'll actually get in your specific environment with your data. We regularly tell clients that a hyped solution won't work for their use case, or that a less prominent option is a better fit. Our recommendations are based on implementation experience, not vendor relationships.
At the strategy stage, we need access to process descriptions, current technology stack documentation, and key business metrics — not raw data or system access. We interview stakeholders to understand workflows and pain points. We may request sample data to assess quality and structure for specific use cases, but the strategy engagement doesn't require integration work.
Readiness indicators include: executive sponsorship for AI as a strategic priority, willingness to share information across business units (AI strategy can't be done in siloes), a realistic 12–18 month time horizon for implementation, and budget commitment for both strategy and at least one initial implementation. Companies that are exploring whether AI is worth pursuing at all are better served by a shorter discovery call rather than a full strategy engagement.

Ready to Move from AI Exploration to AI Execution?

Start with a free consultation. We'll discuss your priorities, assess fit, and scope an engagement designed to give you a clear, executable AI roadmap within 10 weeks.

Start Your Strategy Engagement