This is the first article in a six-part AI Adoption Maturity Ladder series from Sixth City AI.
Most organizations know AI matters.
That is not really the issue anymore.
The harder issue is that many organizations do not know where they actually are in the AI adoption process. One team may be experimenting with ChatGPT. Another may be waiting for leadership to say what is allowed. A manager may be wondering whether AI can help reduce workload. Someone in IT or compliance may be worried about data exposure. Employees may be quietly asking whether AI is going to affect their jobs. Leadership may feel pressure to “do something” before anyone has defined what that something should be.
If this describes you, you are not alone.
This is where AI adoption can get messy.
In my mind, this is why organizations need a practical way to talk about AI maturity. Not a complicated scorecard. Not a certification. Not another abstract framework that sounds impressive in a meeting but does not help people move the needle and make better decisions.
They need a plain-English way to ask:
Where are we really, and what is the next practical step that fits?
That is the purpose of the AI Adoption Maturity Ladder philosophy that guides our work at Sixth City AI. Where are you today, and how do we get you started or unstuck?
The ladder helps leaders understand whether their organization needs awareness, readiness work, training, workflow adoption, automation review, or sustained adoption support before making bigger AI investments.
The six rungs are:
- AI Awareness
- AI Readiness
- AI Literacy
- AI Workflow Adoption
- AI Operational Integration
- AI Adoption Capacity
These rungs are not rigid boxes. A company may be at one level overall and at a different level inside a specific department, team, or workflow. That is normal. If you are watching it closely, it should be changing by the week, not the quarter or year.
A leadership team may still be at AI Awareness. A marketing employee may already be experimenting with prompts. Operations may have workflow ideas. IT may be focused on data risk. HR may be watching employee anxiety build quietly in the background.
That unevenness is exactly why the ladder matters.
The goal is not to climb the ladder as fast as possible. The goal is to stop skipping rungs, because each rung builds on the last.
Level 1: AI Awareness
The first rung is AI Awareness.
At this stage, the organization knows AI matters, but there is no shared approach yet.
People may be curious, skeptical, excited, anxious, dismissive, or quietly experimenting on their own. Leaders may feel pressure to respond, but the organization does not yet have a shared vocabulary, practical roadmap, clear ownership, or agreed-upon guardrails.
That does not mean the organization is failing.
The truth is, AI Awareness is not failure. It is the moment before an organization chooses whether AI becomes scattered experimentation, performative strategy, or practical adoption.
That distinction matters.
A Level 1 organization is usually not doing nothing. In many cases, it is already doing something. The problem is that the activity is scattered.
Some employees are trying tools on their own. Some are watching videos or reading newsletters. Some are using AI quietly because no one has told them whether they can or cannot. Some are avoiding it completely because they do not trust it, do not understand it, or do not want to risk making a mistake.
Leadership may be having conversations, but those conversations are often disconnected from the real work people do every day.
That is where the risk starts.
AI Awareness becomes dangerous when the organization mistakes awareness for readiness, tool access for adoption, or urgency for strategy.
Tool Access Does Not Equal Adoption
One of the biggest mistakes organizations make is assuming that giving people access to AI tools means the organization has adopted AI.
It has not.
A company can give employees access to ChatGPT, Microsoft Copilot, Claude, Gemini, or another AI tool and still have no practical AI adoption.
A Copilot license does not equal adoption.
A lunch-and-learn does not equal adoption.
A few employees using ChatGPT does not equal adoption.
A leadership meeting about AI does not equal adoption.
Those may all be useful pieces of the journey, but they are not the same as adoption.
Practical AI adoption requires shared habits. It requires guardrails. It requires basic training. It requires people to understand what AI can and cannot do. It requires human review. It requires some agreement around what information should not go into AI tools. It requires leaders and managers to understand how AI might actually fit into real work.
Without those pieces, tool access can create the illusion of progress.
My concern is that a lot of organizations are going to confuse activity with maturity.
People may be using AI, but that does not mean the organization knows how AI is being used. People may be generating useful outputs, but that does not mean anyone has reviewed the risk. People may be saving time individually, but that does not mean the business has created a repeatable, responsible, useful adoption pattern.
A company can have AI activity and still be at AI Awareness.
Activity is not maturity.
Level 1 Is a Sensemaking Stage
The most useful way to think about Level 1 is this:
AI Awareness is the organization’s first serious sensemaking stage.
This is where people are trying to understand what AI means before the organization has decided what AI should mean for its own work.
Leaders may be asking:
- Are we behind?
- Should we buy something?
- Should we train everyone?
- Should we write a policy?
- Should we ban tools?
- Should we automate something?
- Who owns this?
Employees may be asking:
- Am I allowed to use AI?
- Is this going to affect my job?
- What information can I put into a tool?
- Will I get in trouble if I experiment?
- Is AI useful for my actual role?
- Is this hype, or is this something real?
That is why Level 1 matters.
It is not just a knowledge gap. It is a trust, language, ownership, and direction gap.
AI is not just another workplace software category. It is changing how people search, write, decide, create, analyze, communicate, and think through work. That does not mean every job disappears or every process needs to be automated. But it does mean the conversation is bigger than “Which tool should we buy?”
At Level 1, the organization is not only asking:
What can AI do?
It is also quietly asking:
What does AI mean for us?
That is a very different question.
The Three Capacities Leaders Need to Build at Level 1
A healthy AI Awareness stage should begin building three early capacities:
- Information judgment
- Emotional trust
- Adaptive action
These do not need to become a complicated internal model. They are simply a practical way to understand what people need before AI adoption can become real.
For a practical worksheet, use the AI Awareness Trap Finder.
1. Information Judgment
People need a basic understanding of what AI can do, what it cannot do, and why human review still matters.
This is especially important because AI tools can produce outputs that sound confident even when they are incomplete, misleading, outdated, or wrong. Employees need to understand that AI-generated work is not automatically accurate just because it sounds polished or authoritative.
At Level 1, the goal is not mastery. The goal is basic judgment and one of the most important human-only skills of the future: critical thinking.
People should understand that AI can help brainstorm, summarize, draft, organize, rewrite, analyze, and explore ideas. They should also understand that AI can hallucinate, miss context, mishandle sensitive information, or produce work that still needs human review.
That is a leadership issue, not just a training issue.
2. Emotional Trust
AI adoption has an emotional layer that many organizations are tempted to ignore.
That is a mistake.
The team at AI CultureWorks reminds us that if leadership talks only about efficiency, employees may hear replacement. If leadership says nothing, employees will fill the silence themselves. If leaders act like every concern is just resistance, they will miss the real fear and uncertainty sitting inside the organization.
At Level 1, people need room to ask basic, honest questions without feeling embarrassed, threatened, or judged.
Some people are excited. Some are scared. Some are skeptical. Some are overconfident. Some are pretending they know more than they do. Some are quietly using tools because they do not want to fall behind.
All of that is part of the adoption reality.
A company cannot build a healthy AI strategy if fear is never named.
3. Adaptive Action
Awareness should not become endless conversation.
The point of Level 1 is not to sit around talking about AI forever. The point is to create enough shared understanding that the organization can take a safe, practical next step.
That next step may be a leadership briefing. It may be a maturity discussion. It may be a basic safe-use session. It may be early opportunity mapping. It may be a readiness diagnostic. It may be a governed adoption pilot.
The right next step depends on the organization.
But it should be grounded in reality, not panic.
For a companion article, read The Three AI Awareness Traps Most Organizations Need to Avoid.
What Leaders Should Do at Level 1
At Level 1, leaders do not need to solve everything.
They do need to create enough clarity that the organization can move from scattered awareness toward practical readiness.
A useful Level 1 leadership agenda might include:
- Name AI as a business issue, not just a technology issue. AI affects work, people, process, quality, risk, knowledge, customer experience, and decision-making. It should not be treated as an IT-only conversation.
- Create a shared vocabulary. People need plain-English definitions for terms like generative AI, copilots, prompts, hallucinations, sensitive data, automation, agents, and human review.
- Ask where AI is already being used. Before creating a plan, leadership should understand what is already happening inside the organization.
- Identify early concerns and fears. The organization needs to know what people are worried about, where they are confused, and where expectations may be unrealistic.
- Set temporary safe-use boundaries. Even before a full AI policy exists, leaders can define what types of information should not be entered into public AI tools.
- Avoid large tool purchases too early. Buying software before understanding readiness, workflows, data, and use cases often creates more noise.
- Pick a few low-risk learning areas. Start with safe examples like summarizing public information, drafting internal outlines, brainstorming, rewriting, or creating training questions.
- Decide who owns the next step. Level 1 should not end with “we should look into AI.” It should end with a clear owner or sponsor for the readiness conversation.
The practical question is not, “How do we automate everything?”
The practical question is:
Where should we start without overcommitting?
What Employees Should Do at Level 1
AI adoption cannot be only a leadership conversation.
Employees have a role at Level 1 as well.
The goal for employees is not mastery. It is honest curiosity with good judgment.
That means employees should:
- Learn the basics of what AI can and cannot do
- Avoid entering confidential, sensitive, client, customer, employee, or proprietary information into tools without guidance
- Treat AI output as a draft, not a final answer
- Save examples of useful and poor results
- Ask for guidance instead of guessing
- Identify one or two repetitive tasks that may be useful future AI examples
- Avoid pretending to be more fluent than they are
That last point matters.
There is a lot of pressure right now for people to act like they are already AI-capable. But pretending creates risk. People need permission to learn honestly.
At Level 1, a healthy organization does not need everyone to become an AI expert. It needs people to start building practical awareness and safe judgment.
What HR and Managers Should Pay Attention To
HR does not have to become the AI owner.
But HR should not sit out the conversation either.
At Level 1, HR and people managers can help make sure the human side of adoption is not ignored. That includes fear, communication, training needs, role impact, manager support, and internal trust.
Practical HR and manager actions may include:
- Helping leadership communicate clearly
- Surfacing employee fears and misconceptions
- Supporting manager talking points
- Beginning to map training needs
- Asking which roles are most exposed to informal AI use
- Clarifying that safe use is not the same as compliance assurance
- Preparing for AI literacy training
- Identifying potential AI champions
This is where many AI initiatives either gain trust or lose it.
If employees believe AI is only being introduced for cost-cutting, they may resist quietly. If managers do not know what to say, they may avoid the topic. If HR is left out until after tools are selected, the organization may miss the emotional and cultural signals that determine whether adoption actually works.
AI adoption is not just a technology problem.
It is a people, process, culture, timing, and leadership problem.
When Level 1 Is Ready to Become Level 2
The next rung on the ladder is AI Readiness.
Level 2 is where the organization begins looking more carefully at whether people, workflows, data, documents, business context, and guardrails are ready for practical AI use.
But the organization should not rush there just to feel more advanced.
A company is ready to move from AI Awareness to AI Readiness when:
- Leaders agree AI matters enough to discuss seriously
- Employees have a basic shared vocabulary
- Early fears and questions have been surfaced
- Current AI experimentation has been identified
- Obvious sensitive-data concerns have been named
- There is agreement that tool access is not the same as adoption
- Someone owns the next step
- The organization is ready to examine workflows, documents, data, context, and guardrails
That is when curiosity starts turning into readiness.
And that is the point.
Being at Level 1 is not the problem. Staying there while pretending AI adoption is already happening is the problem.
Awareness becomes useful only when it leads to the next practical step.
The Practical Level 1 Question
Every rung of the AI Adoption Maturity Ladder has a practical question.
For Level 1, the question is:
Where should we start without overcommitting?
That question matters because many organizations are being pulled in too many directions at once.
One vendor says buy a platform.
One employee says automate everything.
One leader says move faster.
One manager says slow down.
One team is experimenting.
Another team is scared.
IT wants guardrails.
HR wants clarity.
Operations wants practical use cases.
Finance wants to know what this is going to cost.
The answer is not to ignore AI.
The answer is also not to rush into automation.
The answer is to build enough shared awareness that the next step is practical, safe, and tied to real work.
That may not sound as exciting as “AI transformation,” but it is how real adoption starts.
How the AI Adoption Maturity Ladder Helps
The AI Adoption Maturity Ladder gives leadership a simple way to name where the organization is and what kind of support fits next.
At a high level:
- AI Awareness asks: Where should we start without overcommitting?
- AI Readiness asks: What needs to be clarified before training, broader use, or automation makes sense?
- AI Literacy asks: How do we help people use AI in useful, responsible, repeatable ways?
- AI Workflow Adoption asks: Which AI habits and use cases are worth repeating, refining, or scaling?
- AI Operational Integration asks: Which workflows are ready for AI-supported process change, and what still needs human review?
- AI Adoption Capacity asks: How do we keep useful AI adoption governed, measured, and sustained over time?
The ladder should help conversations, not complicate them.
Use it to identify the next practical support need. Use it to avoid jumping into automation before workflows are understood. Use it to create shared language between leaders, managers, employees, and AI champions.
Do not use it to label a team as behind. Do not use it to imply adoption is guaranteed. Do not use it as a replacement for legal, compliance, cybersecurity, privacy, or regulatory review. Do not use it to force every organization into the same path.
The real value of the ladder is that it helps leaders stop guessing.
Closing Thought
AI Awareness is not adoption.
But it is where adoption begins.
It is the stage where leaders stop treating AI as a vague pressure and start turning it into a practical business conversation.
That conversation does not need to be perfect. It does not need to answer every question. It does not need to produce a massive transformation plan.
It needs to be honest enough to name where the organization actually is.
It needs to be clear enough to reduce fear and confusion.
It needs to be practical enough to create a safe next step.
And it needs to be grounded enough to remember that AI adoption is not about chasing the highest rung on a maturity ladder. It is about helping real people, inside real organizations, use powerful tools in ways that are useful, responsible, and tied to the work that actually needs to get done.
If your organization knows AI matters but does not know where to begin, start with the first practical question:
Where are we really, and what is the next step that fits?
That is the beginning of AI Awareness.
And done well, that is the beginning of practical adoption.