How We Think About Technology Transformation
A disciplined framework for identifying, evaluating, and deploying technology where it actually creates value.
The 4-Question Filter
Before deploying AI anywhere, we run every use case through four questions:
Is this high-volume and repetitive?
AI thrives on pattern recognition at scale.
What's the cost of being wrong?
Low-stakes = automate. High-stakes = augment with human review.
Is there clean, accessible data?
A centralized, company-specific knowledge base is a massive multiplier.
Does this solve a problem the team actually has?
Start with the pain point, not the tool.
The Maturity Framework
Crawl-Walk-Run-Fly: meet every company where they are.
| Stage | Where They Are | What We Prescribe |
|---|---|---|
| Crawl | No AI usage. Data scattered. Team skeptical. | Data infrastructure cleanup. Staff training. 1 low-risk pilot. |
| Walk | Some experimentation. No measurement. | Standardize 2-3 tools. Define KPIs. 90-day pilot. |
| Run | Multiple tools in production. Measurable impact. | Scale proven cases. Cross-pollinate. Custom models. |
| Fly | AI in core operations. Competitive advantage. | Proprietary data moats. AI-native business models. |
“A core principle: meet your end user, customer, and company where they are. Pushing technology on a team that isn't ready creates resistance, not results.”
Trust, But Verify
AI is a phenomenal research and productivity accelerator. It's also confidently wrong about 10% of the time. The discipline is simple: use AI to do the first 80% of the work, then verify the last 20% yourself. Check the source. Click the link. Confirm the number. The teams that internalize this principle get the speed benefits without the credibility risk.
Ready to Apply This Framework?
Start with a Technology & AI Readiness Assessment for your business or portfolio.
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