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Improving's AI Maturity Model: 3 Waves, 8 Stages
Most organizations are in Wave 1 right now. Build the foundation in Wave 1 before advancing to Wave 2.
Understanding AI Maturity: The 2 Core Stages of Wave One
Zero AI
No AI in active use means every workflow is still running at human speed. Getting to Stage 2 requires less technology than it does a clear decision to start.
Reality Check:
No LLM or AI assistant in any team's workflow
AI adoption remains stuck in evaluation
No AI policy, standards, or governance exists because nobody has needed one yet
Off the Shelf
AI tools are live, but the org has no consolidated view of what's in use, who authorized it, or what it's touching. That’s an audit finding waiting to happen.
Reality Check:
Different tools across teams, no coordination
Legal or security has started asking questions nobody can answer
Leadership treats "we use AI" and "we have an AI strategy" as the same thing
How Improving Works With Organizations in Wave 1
The large firms sell scale. Boutiques sell specialization. We sell trust. Which is why 98% of clients rate their Improving engagement as meeting or exceeding expectations.
AI Tool Landscape Audit
Gain complete visibility into AI usage, data access, and governance gaps with our comprehensive AI tool audit.
Governance & Policy Foundation
Build AI guardrails your teams can actually use, with practical policies for AI usage, data handling, and vendor risk.
AI Readiness Assessment
Benchmark your organization against our field-tested AI Maturity Model and get a step-by-step roadmap to advance with confidence.
Build, scale, and accelerate AI with the right technology partners: Microsoft | AWS | Google Cloud | Anthropic
Same Stage, Different Reality
Developer
"I write code" vs. "I build systems, some of which AI produces"
AI functions primarily as an autocomplete tool with no memory and every session starts from zero. The work gets faster in moments but there is no compounding effect on system-level decisions.
Platform / Infra Engineer
"I build infrastructure" vs. "I govern infrastructure AI runs on"
AI shows up sideways. Someone's personal Copilot license. ChatGPT-generated Terraform pasted into a PR. The platform team finds out after the fact, if at all. Governance is reactive because there was nothing to govern proactively.
Support / Business Function
"I resolve tickets" vs. "I manage a team where AI handles first pass"
AI as a personal shortcut. One person uses a chatbot to draft responses faster. The person next to them has never touched it. No shared standard. The productivity gain is real but invisible at the org level.
CIO / Exec Sponsor
"I fund tools" vs. "I run an AI-informed operating model"
AI as a line item. Licenses funded in pockets. No aggregate view of where AI touches the business, what it's returning, or what exposure it creates.
Wave 1 in Practice
From Siloed Acquisitions to One Governed Data Foundation
A Fortune 500 health insurer operating in 40 U.S. states had no shared standard for how newly acquired companies stored, shared, or governed their data, the same visibility gap Wave 1 describes, just showing up in data instead of AI tools. Improving built a unified enterprise-wide data strategy that replaced years of siloed technical debt with one governed foundation every team and every acquisition could build on.
40 States
Fortune 500 footprint unified onto one data platform
8+ Canonicals
Shared business data definitions established across departments
Our Practitioners Teach What They Build - Watch Them Do It
Every session is led by an Improving practitioner, the same people delivering AI engagements for enterprise clients. Deep technical content, real delivery experience, open to everyone.
Building Trust at Scale for Growth and AI: What to Do First, Next, and Later in Data Governance
Preston Mesarvey
Technical Director
Governance That Actually Works: How Well-Designed AI Systems Make Responsibility Visible
Devlin Liles
Chief AI Officer
Define the Need, Solve the Problem: An AI-First Playbook for Developers
Claudio Lassala
Technical Director
What Comes Next
The Tool Ceiling
Off-the-shelf AI tools can deliver 10–20% productivity gains, but they rarely transform how teams work. Every interaction starts cold, with no memory of what came before.
The Governance Gap
Proprietary code, customer data, and credentials entering third-party model APIs, prompt injection, there are many risks that are manageable now. But a liability the moment workflow automation starts in Wave 2.
Organizations with strong AI governance are 2.25x more likely to succeed on AI projects (Gartner, 2024). That gap is cheap to close at Wave 1, and by Wave 2, it decides whether the workflow works at all. The governance question shifts from "who's using what tool" to "who authorized this automated action."
Ready to Move from AI Initiative to AI Impact?
Tell us where you are and we'll tell you exactly how we can help. No generic proposals, no sales pitch, just a direct conversation about your situation.
Devlin Liles
Chief AI Officer & CCO
David O'Hara
Regional Director
Tim Rayburn
VP of Consulting