In 30–45 minutes, you'll understand:
Where AI can create leverage in your business
What not to automate
Which 1–2 use cases are worth funding this year
Most companies fail with AI because they skip diagnosis. This structured approach gives you answers with confidence.
Choose your path based on your most pressing question
Start with Step 1: AI Readiness to understand if you're early, mid, or late compared to peers.
Jump to Step 2: Constraint & ROI Identification to find where time is being wasted.
Go to Step 3: Execution Reality Check to understand what breaks when trying to scale.
Or follow the complete diagnostic journey below for full clarity
"Is my company even ready for this?"
Why this step matters:
Most companies fail with AI because they skip this step. Understanding your maturity level helps you avoid costly mistakes and set realistic expectations.
Discover how ready your organization is for AI transformation with our comprehensive 10-question assessment.
If you scored 0-40%:
You're in the early stage. Focus on data infrastructure and quick wins before attempting complex AI projects.
If you scored 41-70%:
You're mid-stage and ready for targeted automation. Companies at your level typically see 5-10× capacity gains from 1-2 well-chosen projects.
If you scored 71-100%:
You're advanced and ready for complex AI initiatives. Your challenge is execution and scaling, not capability.
Next step: Understand where AI can create the most value in your specific business.
"Where is time actually being wasted?"
Why this step matters:
AI doesn't create ROI. Constraint removal does. This step helps you find the 1-2 bottlenecks that are silently capping your growth.
Identify the biggest bottlenecks limiting your organization's performance and get actionable recommendations.
Interactive calculator showing the true cost difference between manual contract review and AI-powered analysis.
If your constraint is in Operations:
Companies with your profile typically have 1-2 automations that unlock 5-10× capacity. Document processing and workflow automation are often quick wins.
If your constraint is in Data/Systems:
AI won't help until you fix the underlying infrastructure. Most teams underestimate implementation complexity by 3-5×.
If your constraint is in People/Skills:
Technology isn't your blocker—adoption is. Start with augmentation (AI-assisted work) rather than full automation.
Next step: Understand what it actually takes to execute on these opportunities.
"What breaks when we try to scale?"
Why this step matters:
This is where 90% of AI initiatives stall. Understanding execution feasibility helps you choose the right approach and avoid getting stuck in analysis paralysis.
See exactly what $100K buys you: PowerPoint decks vs. actual AI implementation with measurable ROI.
If you need strategy and direction:
Traditional consulting might make sense for early-stage companies that need to build capability. But be prepared for 6-12 month timelines before seeing value.
If you need actual execution:
Companies that succeed with AI focus on implementation over strategy. Fractional teams deliver working solutions in weeks, not months.
If you're unsure:
Start small. Pilot one automation with clear ROI metrics. Scale what works, kill what doesn't.
You've completed the diagnostic journey. Now it's time to turn insights into action.
The tools give you data. But what does it mean for your business? And what should you do next?
Here's what companies at your stage typically experience: You've identified your constraints. You see the potential ROI. But you're uncertain about which 1-2 initiatives are actually worth funding—and which approach will work for your specific situation.
We'll review your diagnostic results and give you a prioritized roadmap. No sales pitch—just synthesis and judgment.
A 30-minute walkthrough of what your results mean—and which 1-2 automations are worth pursuing.
We'll take your tool results and map them to a prioritized ROI roadmap.
We'll pressure-test whether your top AI ideas are actually deployable.
People don't book meetings because they learned something. They book because ambiguity increased, stakes became clear, and the next step felt obvious.
You've already invested 30-45 minutes in diagnosis. The meeting is just interpretation—not persuasion.
The 3-step diagnostic journey takes 30-45 minutes and gives you a structured understanding of where AI can—and can't—help your business.
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