Know Exactly Which AI to Build
Before You Spend a Dollar.
Our AI Strategy Sprint gives you a clear, prioritized roadmap: the right AI investments, in the right order, with realistic ROI projections.
Why AI Strategy Is Not Optional
Most businesses approach AI one tool at a time: someone on the marketing team buys a writing assistant, ops tries an automation tool, and the CEO is using a different chatbot entirely. Each individual choice might seem reasonable in isolation, but without a strategy, the result is a collection of disconnected tools that don't compound, don't integrate, and don't produce the business impact that AI is actually capable of delivering.
A proper AI strategy answers the questions that tool-by-tool adoption skips: Which business problems should we prioritize? Where will AI deliver the fastest ROI? What data do we have, and is it sufficient? Which workflows should be automated versus augmented? Where does regulation or compliance limit our options? What do we build versus buy? And critically: in what order do we do all of this so that early investments create a foundation for the next ones?
The companies that extract significant value from AI are not the ones that moved fastest, they're the ones that moved in the right direction. A clear strategy prevents wasted investment, organizational friction from poorly planned rollouts, and the all-too-common outcome of spending money on AI that nobody ends up using.
Is This For You?
Who Needs an AI Strategy Sprint
You know AI is worth pursuing but you're not sure which business problems to prioritize first or what a realistic starting point looks like.
You've tried AI tools and gotten underwhelming results. You're not sure if the problem was the tools, the approach, or how they were applied.
You need to present a credible AI investment case to leadership, with real numbers, timelines, and a plan that holds up to scrutiny.
You're deciding which AI capabilities to build or buy in the coming year and want to make sure the budget goes toward what will actually move the needle.
Deliverables
What's Included in the Strategy Sprint
The AI Strategy Sprint is a focused, structured engagement. You receive a complete document + live executive briefing.
Current State Analysis
Full assessment of your workflows, data assets, existing tools, and team AI readiness.
AI Opportunity Map
Every AI opportunity in your business, ranked by ROI and feasibility so you know what to build first.
Build vs. Buy Recommendations
For each opportunity: should you build custom AI, buy an existing tool, or do both? We tell you exactly why.
12-Month AI Roadmap
A prioritized, phased implementation plan covering month 1, quarter 1, and year 1.
Budget & ROI Projections
Realistic budget requirements and ROI projections for each initiative, in actual numbers, not vague percentages.
Regulatory Compliance Review
Data governance, privacy regulations, and compliance requirements mapped to each planned AI system in your region.
AI Strategy Sprint
Full AI roadmap document · Executive briefing session · Tailored to your business
Custom pricing for every engagement · Scales with company size and scope
Fully deductible from implementation cost if you proceed with us
Our Assessment
Key Areas We Assess in Your Business
These are the main dimensions we look at, not a fixed checklist. Every assessment is scoped to your specific situation, and the areas we dig into depend on what you're trying to solve.
Data Readiness
What data you have and how it can power AI models.
Process Efficiency
Which workflows waste the most time and money.
Team AI Literacy
How ready your team is to adopt and use AI tools.
Technology Stack
What systems you use and how AI-compatible they are.
Competitive Position
How your competitors are using AI and where you're exposed.
ROI Potential
Where AI will pay back fastest in your specific business.
What a 12-Month Roadmap Actually Looks Like
Every roadmap is built around your business, but the structure follows the same logic: prove value fast, then build on it.
Month 1: Quick wins that prove the case
One or two low-risk, high-frequency tasks get an AI assist first: usually document drafting, data entry between systems, or first-line email handling.
Baseline metrics are recorded before anything changes, so improvement can be measured honestly instead of estimated later.
The team is briefed on what's coming and why. Adoption starts on day one, not after launch.
Months 2–3: The first serious build
The highest-ROI opportunity from your opportunity map goes into development, with success criteria agreed before a line of code is written.
Quick wins from month 1 get reviewed against their baselines. What worked expands; what didn't gets adjusted or dropped.
Data gaps identified in the assessment start getting fixed, so later initiatives aren't blocked by missing or messy data.
Months 4–12: Compounding, not collecting
Systems built in earlier phases get connected: the lead-scoring model feeds the outreach workflow, the support AI feeds the product feedback loop.
Each new initiative reuses infrastructure, data pipelines, and lessons from the previous one, so cost per initiative drops over time.
Quarterly reviews adjust the plan against results and against what's newly possible, because AI capabilities won't sit still for 12 months either.
Frequently Asked Questions
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Get the AI Roadmap Your Business Actually Needs
Know exactly what AI can do for your business, and exactly what it will cost, before you commit to anything.
30-min call · No sales pressure