The previous post laid out a diagnostic for figuring out where an organization actually sits on the AI maturity ladder. The lenses help, but lenses on their own are abstract. People recognize themselves more readily in a portrait than in a checklist. This post is the first in a series that walks through what a single theoretical organization looks like at each stage of the progression, so a reader can pattern-match against a coherent picture rather than running their own organization through five separate diagnostic passes.
A few things about how this case study is going to work. The organization is a fictional mid-market professional services firm with around 450 staff across three offices. Mixed practice: tax, audit, advisory. Partner-owned. The firm has been growing steadily for the last decade, mostly through hiring rather than acquisition. It's fictional and isn't drawn from any specific firm I've worked with. The dynamics it portrays are general patterns I've observed across organizations, recast into a setting that lets the patterns be seen clearly. Some readers will recognize echoes of their own firm in it. That recognition is the whole reason for writing it this way.
The stakeholders in the case are composites. A handful of them recur across the series because their roles put them in the middle of the AI conversation regardless of stage. The rest enter and exit as the stage requires.
The named characters worth knowing across the series:
Dana Reyes, Chief Financial Officer. Numbers-driven, pragmatic, slightly skeptical of technology pitches but willing to fund the right ones. Has been at the firm for about a decade, joined as controller and worked up.
Marcus Pham, Chief Information Officer. The IT leader. Has been doing this work for around fifteen years across two firms before this one. Was hired three years before the case begins, after the previous IT director retired and the firm decided to upgrade the role. Has earned credibility with the executive team but is still building it with the practice leaders.
Linda Brennan, Chief Human Resources Officer. New to the role, coming from a midsize firm in an adjacent industry. Has been at the firm for about a year. Brings outside perspective the rest of leadership has mixed feelings about.
The Managing Partner. Unnamed across the series because the role is structurally important but the person occupying it shouldn't be the load-bearing character. Strategic, externally focused, attentive to client relationships and firm reputation, less attentive to internal operations.
The practice leaders. Heads of tax, audit, and advisory. Three people, named individually when needed. They control the work and the people who do it. Their priorities shape the firm in ways the executive team often discovers after the fact.
Other roles appear as needed: senior associates, IT staff, the controller's team, business development. They come in when the stage requires it.
Phase I: awareness.
The firm is at the first stage of the maturity progression. Most organizations are past this stage by 2026, but the artifacts of it remain visible in how leadership conversations get framed, and a reader who hasn't done the diagnostic work in the previous post may still recognize their own organization here even if they thought they were further along.
What awareness actually looks like at this firm:
The Managing Partner read a Wall Street Journal piece on AI in professional services about eighteen months ago. The piece described a competitor firm that had partnered with a vendor for an AI-assisted document review workflow. The Managing Partner mentioned it in an executive team meeting and asked whether the firm should be doing something similar. Dana asked what the competitor had actually implemented and what it had cost. The Managing Partner didn't have those details. The conversation moved on.
Three months later, the same question came up in a different executive meeting, in a slightly different form. A client had asked the Managing Partner at a recent meeting what the firm's AI strategy was, and whether the firm's AI-enabled efficiencies would be reflected in pricing. The Managing Partner had answered in general terms about evaluating opportunities. The client followed up with an email asking for specifics, partly out of curiosity and partly because the client's own board was asking about AI procurement standards. The Managing Partner forwarded the email to Marcus and asked him to draft a response.
Marcus drafted a response. The response said that the firm was actively evaluating AI applications across its practice areas, that several pilots were under consideration, and that a more comprehensive strategy would be developed in the coming fiscal year. Marcus chose those words carefully. None of them were strictly false. None of them described any work that was actually underway.
This is what awareness looks like from the inside. The conversations are happening at the top of the firm. The vocabulary is in use. Clients are asking. The Managing Partner is being asked. Marcus is producing language that satisfies the immediate need without committing the firm to anything specific. No one in the firm is doing anything operationally with AI beyond what individuals are doing on their own time on their personal accounts.
The deeper artifact of awareness is what's missing from the conversation, not what's present.
In an executive team meeting two months after the client email, the Managing Partner raises AI again. The framing is strategic: where should we be on this. The conversation that follows is striking mostly for what doesn't happen in it. Dana asks what specific problems the firm would be trying to solve. The head of advisory responds that the firm should be at the forefront of AI-enabled client services, but doesn't name any specific service. Linda mentions that she's been reading about workforce implications and would like to bring some materials to a future meeting. Marcus, when asked directly, says he's been tracking the vendor landscape and has some preliminary thoughts. Each of these statements is reasonable on its own. None of them connects to any other. The executive team ends the meeting having had a conversation about AI without anyone having committed to anything.
The Managing Partner, walking back to his office, feels that the firm had a good strategic discussion. Marcus, walking back to his, knows the firm has done nothing.
This disconnect is the defining feature of awareness. The leadership team believes the firm is engaging seriously with AI because the topic is being discussed at the highest level. The functions closest to operational reality know that discussion alone isn't engagement. The gap between those two perspectives is invisible to the leadership team because they don't have a frame for distinguishing "we talked about AI" from "we're doing something about AI."
Other vantages on the same stage:
A Tuesday afternoon at the firm. A senior associate in the tax practice is reconciling a client's prior-year filings against current-year source documents. The work is methodical, line-by-line, and takes about eight hours of her week across multiple clients. She has used a general-purpose AI tool on her personal laptop to summarize portions of the relevant tax code when she's stuck on an interpretation question. She has not raised this in any meeting, partly because she assumes the firm's IT policy would prohibit it and partly because she doesn't have time to navigate the procurement process for a tool she isn't certain would work at scale. The work continues to be manual. She does not flag the inefficiency to her practice leader because she has internalized it as part of the job.
A vendor pitch arriving in Marcus's inbox. A professional services-focused SaaS company is pitching an AI-powered document review and workpaper platform. The pitch describes the platform as an integrated solution that uses machine learning to extract data from source documents, identify anomalies, route exceptions to humans, and standardize workpaper formats across the firm. The pricing is structured per-user per-year with a volume tier for the audit practice. Marcus reads the pitch carefully. The functional description sounds promising and the pricing is defensible. He has no way to evaluate whether the platform actually works at his firm's scale and with his firm's clients without spending more institutional energy than he has available, so he files it for a future evaluation that he isn't yet sure when he'll have time to do.
Linda's first attempt to raise AI workforce implications. In a one-on-one with the Managing Partner, Linda mentions that several of her peer CHROs at other firms have started talking about AI's implications for staff roles, particularly at the associate and senior associate levels, and that she'd like to start a small working group to explore the question. The Managing Partner says this is a good idea and asks her to put a proposal together for the next executive meeting. Linda puts the proposal together. The executive meeting agenda fills up with more urgent items, including a Q3 forecast revision and a partner compensation discussion. The proposal gets deferred to the following month. The following month, the same thing happens. Eventually Linda stops bringing it up, not because she's lost interest, but because she's recalibrated her sense of what the executive team will actually prioritize.
The practice leaders' perspective. The three practice leaders are generally aware that AI is a topic the firm should be addressing and assume, with varying degrees of charity, that the Managing Partner or Marcus or someone else has it in hand. They have not pressed for specifics, partly because their daily work is dominated by billable utilization and client demands, and partly because pressing for specifics would invite ownership of the work, which none of them wants. Their awareness is real but not penetrating, which is the comfortable equilibrium most senior partners end up in on most strategic topics that aren't actively in crisis.
A few things about this portrait.
The firm looks busy. The Managing Partner is asking questions. Marcus is reading vendor pitches. Linda is bringing up workforce implications. Clients are engaging. The practice leaders have opinions about applications in their practice areas. By any external measure, the firm is engaging with the AI moment.
It is also doing nothing, in the specific sense that no operational outcome is being pursued, no resource is being deployed, no decision is being made that would commit the firm to any specific direction. The activity is real. The motion is illusory.
This is the failure mode that awareness produces when it isn't carefully managed. Awareness creates the texture of engagement without the substance. The texture is comforting because it lets the firm tell itself, and its clients, and its peers, that it's taking AI seriously. The substance would require harder choices: what problem are we trying to solve, who owns the work of solving it, what resources are we willing to commit, what would we stop doing in order to make room.
A second thing to notice. The functions closest to the actual texture of the work, IT and HR, are seeing the gap clearly. Marcus knows the firm isn't doing anything. Linda has tried to start the conversation and has been deflected. But neither of them has the authority to force the firm past awareness on their own. The progression to the next stage requires either leadership engagement that goes beyond strategic vocabulary, or a coalition strong enough to push the conversation forward despite the absence of executive ownership.
A third thing. The Tuesday afternoon vantage matters. The senior associate in tax who isn't surfacing her manual workflow is one of many such people across the firm. The aggregate of all those unsurfaced inefficiencies is the substrate against which any future AI work would be evaluated. At awareness, none of that substrate is visible to leadership, because no one has done the work of mapping it. The conversation is being held at the strategic level while the operational reality remains opaque.
The firm will move from awareness to the next stage when one of two things happens. Either leadership develops a more specific sense of what they actually want to pursue, or a function inside the firm gets impatient enough with the activity-without-substance pattern to start doing operational work on its own. In this case study, both will eventually happen, in different parts of the firm and at different speeds. The next post in this series picks up the firm at the second stage, where tinkering and exploration have begun in earnest and where the firm's self-image starts to diverge meaningfully from its actual capability.
The firm at this stage is still recognizable to most readers. The leadership conversation about AI in your organization probably sounds something like the one in the executive meeting above. The vendor pitch sitting in your inbox is probably similar in shape. The Tuesday afternoon manual workflow exists in your organization, almost certainly, in dozens of places. If those vignettes feel familiar, you may be further along on awareness than you think you are, and earlier on tinkering than you've been telling yourself.
— Chris