Use the AI Adoption Maturity Ladder to find the next step that fits.

Many organizations know AI matters, but they do not know what stage of adoption they are actually in.

Some teams are curious but scattered. Some have tools in place but no shared habits. Some have trained employees but have not captured repeatable use cases. Others are already discussing automation before they have reviewed the workflow, the data, the context, or the human review points.

The AI Adoption Maturity Ladder gives leadership a plain-English way to talk about that reality.

It is not a scorecard, certification, audit, or maturity badge. It is a planning aid that helps a team understand what kind of support fits the way people are actually using AI today.

Why the ladder matters

Tool access does not equal adoption.

A team can have access to ChatGPT, Microsoft Copilot, Claude, Gemini, or other AI tools and still lack the habits needed for practical AI adoption. People may be experimenting, but the organization may not yet have shared guardrails, reusable prompts, role-aligned examples, workflow clarity, or a practical way to decide what comes next.

The maturity ladder helps leadership ask better questions:

• Are people still learning what AI can and cannot do?
• Do teams know what information should not be entered into AI tools?
• Are there clear human review and output-checking habits?
• Are useful use cases being captured from real work?
• Are workflows understood before automation is discussed?
• Is adoption supported by managers, champions, governance routines, and measurement?

The goal is not to rush to the highest level. The goal is to choose the next step that fits the team’s current maturity, risk, workload, and internal capacity.

The six levels of practical AI adoption

The Sixth City AI Adoption Maturity Ladder has six levels:

1. AI Awareness
2. AI Readiness
3. AI Literacy
4. AI Workflow Adoption
5. AI Operational Integration
6. AI Adoption Capacity

These levels are not rigid boxes. A team may be at one level for general AI use and another level for a specific department or workflow. The ladder is most useful when it helps leadership see where support is needed next.

Level 1: AI Awareness

At this stage, the organization knows AI matters, but there is no shared approach yet.

People may be curious, uncertain, skeptical, or experimenting on their own. Leaders may feel pressure to act, but the organization does not yet have a practical roadmap, shared vocabulary, or clear ownership for AI adoption.

Typical signs include:

• scattered curiosity about AI;
• informal experimentation;
• no common language for AI use;
• unclear ownership;
• uncertainty, fear, or unrealistic expectations;
• leaders know AI matters but do not yet know where to begin.

Useful support at this stage may include:

• AI Strategy & Advisory;
• an AI leadership briefing;
• an AI maturity discussion;
• introductory AI awareness sessions;
• early AI opportunity mapping.

The practical question at Level 1 is: Where should we start without overcommitting?

Level 2: AI Readiness

At this stage, the organization begins looking at whether people, workflows, data, documents, business context, and guardrails are ready for practical AI use.

This is where teams often discover that the issue is not only training. The organization may need to clean up documents, prepare context, clarify approved-use boundaries, identify sensitive-data concerns, and understand where AI could realistically support work.

Typical signs include:

• leadership wants direction;
• workflows and documents are messy;
• business knowledge is scattered;
• governance is unclear;
• teams need safe-use rules;
• internal tools may already be used informally;
• people are unsure what information AI tools can or cannot use.

Useful support at this stage may include:

• AI Readiness Diagnostic;
• AI Readiness & Context work;
• data and content cleanup planning;
• context preparation;
• workflow and information mapping;
• governance and guardrail review.

The practical question at Level 2 is: What needs to be clarified before training, broader use, or automation makes sense?

Level 3: AI Literacy

At this stage, people begin learning how to use AI safely, practically, and responsibly in real work.

AI literacy is more than knowing how to write a prompt. Teams need to understand output review, sensitive-data awareness, source checking, role-aligned examples, and the difference between low-risk practice and higher-risk use cases.

Typical signs include:

• employees need plain-English training;
• leaders need shared vocabulary;
• managers need ways to reinforce responsible use;
• output quality is inconsistent;
• people are unsure how to check AI results;
• AI use is still casual, uneven, or hidden.

Useful support at this stage may include:

• AI Training;
• safe-use workshops;
• prompting fundamentals;
• role-based AI learning paths;
• AI output review checklists;
• AI Skills and Confidence Assessment;
• the Governed AI Adoption Pilot.

The practical question at Level 3 is: How do we help people use AI in useful, responsible, repeatable ways?

Level 4: AI Workflow Adoption

At this stage, AI starts to become part of recurring work through role-aligned use patterns, reusable prompts, simple artifacts, and manager-supported follow-through.

This is where useful examples need to be captured. Teams should begin asking which prompts are worth reusing, which workflows need review, which use cases are safe enough to repeat, and which ideas should wait.

Typical signs include:

• teams can name practical AI use cases;
• employees are building reusable prompts or work patterns;
• managers need adoption support;
• AI use is becoming more role-specific;
• people are sharing examples of what works;
• some workflows need redesign before AI should be added more deeply.

Useful support at this stage may include:

• AI Workflow Opportunity Inventory;
• AI Artifact Build Plan;
• reusable prompt and knowledge systems;
• manager enablement support;
• workflow-specific training;
• client-owned prompt repositories;
• Champion Council or AI Council routines.

The practical question at Level 4 is: Which AI habits and use cases are worth repeating, refining, or scaling?

Level 5: AI Operational Integration

At this stage, validated workflows may begin turning into AI-supported processes, automations, internal assistants, or agent-like concepts.

This level should come after readiness, training, workflow review, and guardrails are clearer. Automation should not be the first move when the workflow is unclear, the data is messy, or human review points are not understood.

Typical signs include:

• practical workflows are being redesigned;
• internal knowledge systems are improving;
• some automations may be ready for pilots;
• governance needs to mature;
• teams need clearer process ownership;
• leadership wants to know which AI-supported workflows are realistic.

Useful support at this stage may include:

• AI Automations & Agents;
• AI Workflow Redesign Sprint;
• Automation Readiness Review;
• agent use-case concept brief;
• pilot-to-production planning;
• automation governance checklist.

The practical question at Level 5 is: Which workflows are ready for AI-supported process change, and what still needs human review?

Level 6: AI Adoption Capacity

At this stage, AI becomes a managed organizational capability with governance, measurement, shared learning, and sustained adoption support.

The organization is not just experimenting. It has repeatable habits, governance routines, learning loops, use-case review, manager support, and a way to observe practical capacity signals.

Typical signs include:

• AI use is shared, measured, and governed;
• teams have repeatable learning loops;
• culture supports responsible experimentation;
• leaders understand both technical and human adoption needs;
• capacity signals are tracked and discussed;
• successful patterns are refined instead of assumed.

Useful support at this stage may include:

• AI Capacity Gain Tracker;
• AI adoption scorecard;
• AI Council Starter Kit;
• ongoing advisory and optimization;
• Change Management & Cultural Enablement;
• sustained learning systems;
• AI Skills Master or client-owned adoption systems.

The practical question at Level 6 is: How do we keep useful AI adoption governed, measured, and sustained over time?

How the ladder supports the Governed AI Adoption Pilot

For many small and lower-midmarket teams, the Governed AI Adoption Pilot is the practical bridge between early maturity and repeatable adoption.

A pilot can help a small team:

1. Clarify current readiness and concerns.
2. Learn practical and responsible AI use.
3. Practice with real work examples.
4. Reinforce guardrails and human review.
5. Build role-aligned use patterns or simple artifacts.
6. Capture useful use cases and adoption barriers.
7. Give leadership a clearer view of what should come next.

The pilot does not require the organization to be mature before starting. It helps leadership see what maturity level the team is actually operating from and what support may be needed next.

How to use the ladder without overusing it

The maturity ladder should help conversations, not complicate them.

Use it to:

• name the current adoption stage;
• identify the next practical support need;
• decide whether training, readiness, workflow review, or advisory support fits best;
• avoid jumping into automation before workflows are understood;
• explain why governance and human review matter;
• create shared language between leaders, managers, and AI champions.

Do not use it to:

• label a team as behind;
• imply adoption is guaranteed;
• claim ROI or productivity gains;
• replace legal, compliance, cybersecurity, privacy, or regulatory review;
• force every client into the same path;
• make software feel mandatory before work habits are clear.

Tool versus service

A service is the facilitated engagement, advisory support, training, pilot, or scoped work Sixth City AI provides.

A tool is the worksheet, diagnostic, tracker, planning aid, map, or working asset used inside that work.

The AI Adoption Maturity Ladder is a tool. It may be used inside services such as AI Strategy & Advisory, AI Readiness & Context, AI Training, the Governed AI Adoption Pilot, AI Automations & Agents, and Change Management & Cultural Enablement.

The ladder helps organize the conversation. The service provides the facilitation, judgment, planning, training, or follow-through needed to move forward.

Related tool and service links