Workforce AI Impact Snapshot
What a Snapshot is
Your people each complete a short, private assessment of their own day-to-day work. We summarize those results into one anonymous, organization-level picture — this document. You see the aggregate. You never see any individual’s report, and neither does anyone else.
A Snapshot measures three things, and — this matters — it keeps them separate. They are never added together into a single score, because they answer three different questions.
The roles behind the numbers
A small local-government office runs the same core functions any organization does — reception, finance, records, IT, communications, HR — often more of them packed into one small team than a business this size. The roles you’ll recognize here show up almost everywhere. We’ve tagged which are common across most orgs and which are sector-specific. Not every role appears in every organization, and the actual tasks vary — but the pattern travels.
| Role | Type | Task exposure |
|---|---|---|
| Chief Administrative Officer | Common | 25–35% |
| Office Administrator | Common | 55–65% |
| Front-counter Receptionist | Common | 50–65% |
| Finance / Accounting Clerk | Common | 50–60% |
| Records & Accounts-Payable Clerk | Common | 60–70% |
| Communications Coordinator | Common | 45–60% |
| IT Support Technician | Common | 55–65% |
| HR / Payroll Coordinator | Common | 45–55% |
| Planner / Development Officer | Sector | 30–45% |
| Public Works Coordinator | Sector | 30–45% |
| Bylaw Enforcement Officer | Sector | 15–25% |
Eight of eleven roles here are the universal office backbone — the same functions a law firm, a clinic, or a manufacturer would staff. Only three are specific to local government.
Three dimensions, kept separate
1 · Task exposure
That spread is the whole point: two people under the same roof can sit at opposite ends depending on what they actually do each day. Exposure is a signal of where to look first — not a threat, and not a verdict on anyone.
Exposure concentrates in routine administrative, finance, and records tasks — predictable for an office this size, and exactly where attention pays off first.
2 · Human strengths
Nine to ten of eleven staff score strong or very strong across core human strength categories — stronger than you might expect. Critically, this does not track with task exposure. Several of the roles carrying the highest exposure scores also carry the strongest human strength profiles. These are genuinely independent dimensions, and conflating them leads to the wrong conclusions.
3 · Adaptability
Overall adaptability is genuinely strong across this team. The one meaningful variable within this dimension is tech comfort — which is scored and tracked separately because it moves independently of general adaptability.
A lower tech comfort score is never a ceiling — it is a starting point, and one that responds well to the right support. Knowing who is at that starting point is precisely what a Snapshot is for.
What this tells you
- Exposure is concentrated and predictable — routine administrative, finance, and records work. That’s the clearest place to look first. But it is not a verdict on the people doing that work.
- Human strengths are exceptionally strong across this team — nine to ten of eleven scoring strong or very strong. And they do not track with exposure. Some of the highest-exposure roles in this office also carry the strongest human strength profiles. That matters: it means the people are not the problem to solve. They are the advantage to build on.
- Adaptability is broadly strong, with one genuine variable worth attention: tech comfort. Roughly a third of the team is still building comfort with technology — not a problem, but exactly the kind of thing worth knowing before any tool or training decision is made.
Questions this Snapshot is meant to raise — not answer for you:
- Which repetitive administrative tasks consume the most time, and would the team welcome support with them?
- Where do our people’s strengths most deserve protecting as the work shifts?
- Who would benefit from a conversation about change before any tool or training is ever considered?
You’ll notice this report recommends no products, no training, and no tools. That’s deliberate. We collect and summarize. What happens next is entirely your decision.
Practical Considerations
What the data means — and the questions it raises. No recommendations. No products. Your decisions.
What this picture says, taken together
The overall picture here is one of a capable, experienced team carrying meaningful but concentrated AI exposure — and carrying it from a position of genuine strength. That combination matters, and it’s worth considering carefully before drawing any conclusions.
Task exposure is real and it sits where you’d expect it in an office like this: administrative processing, records management, finance workflows, and communications drafting are the functions where AI tools are most actively being applied. Seven of eleven roles show elevated exposure in those areas. That’s not alarming — it’s a description of where the work is routine enough that tools are being developed to support it. The question it raises isn’t “are we at risk” but “do we understand which specific tasks are shifting, and are we paying attention to the right things.”
The human strengths picture is the strongest part of this profile, and it should carry real weight in how leadership interprets the exposure numbers. Nine of eleven staff score strong or very strong across the capabilities that matter most: judgment, communication, coordination, relationship management, and the kind of institutional knowledge that doesn’t live in any system. Critically, those strengths are not concentrated in the low-exposure roles — they show up across the exposure spectrum, including in several of the roles most touched by AI. Your people are not the vulnerability here. They are the asset.
Adaptability is broadly strong, with one genuine variable worth specific attention: tech comfort. Four of eleven staff are still building familiarity with technology. In the context of a team where seven roles carry elevated exposure, it identifies a cluster who may benefit from a different kind of conversation — not about AI specifically, but about their relationship with technology more generally — before any tools or changes arrive.
Where the dimensions intersect
The three dimensions are reported separately because they answer different questions. But the combinations are where the most useful patterns appear. Two intersections in this profile are worth specific attention.
Exposure × Tech comfort
Exposure × Human strengths
Questions worth exploring
These questions come directly from this organization’s specific profile. They are not generic — a different organization with different numbers would face different questions. They are not answered here. That’s deliberate.
- ExposureIn the administrative, records, and finance functions that show the highest exposure — which specific tasks consume the most staff time, and are those the tasks where AI tools are actually being deployed? Task exposure in the abstract is less useful than knowing which hours of the week are genuinely shifting.
- ExposureThe communications coordinator role sits at 45–60% exposure — a wide band that reflects genuine uncertainty about how drafting, editing, and content work will evolve. Does your organization have a position on AI-assisted communications, and does that person know what it is?
- AdaptabilityThe three to four staff still building tech comfort — do they know that’s where they sit, and have they been given any opportunity to build that familiarity on their own terms? Tech comfort tends to respond well to low-stakes exposure; it tends to stall when people feel assessed or pressured.
- AdaptabilityThe four elevated-exposure roles with strong tech comfort are your most likely early adopters if tools arrive. Are they positioned to be early evaluators rather than just early users? The difference matters — evaluators shape how a tool lands; users absorb it.
- Human strengthsThe intersection analysis shows your highest-exposure roles are held by your strongest people. Does your leadership team know that? It changes the conversation from risk management to opportunity — but only if it’s named.
- Human strengthsThe sector-specific roles — bylaw enforcement, public works, planning — sit at lower exposure but also carry very strong human strength profiles. What’s the organization’s thinking about how those roles evolve as the administrative layer around them changes?
- ExposureThe records and accounts-payable clerk role shows 60–70% exposure — the highest in the organization. Is that role currently structured around tasks that AI tools are being designed to automate? If so, what’s the thinking about how that role might evolve rather than simply contract?
- AdaptabilityOverall adaptability is high across the team, but adaptability is not the same as readiness for a specific change. Has the organization had a general conversation with staff about the direction of AI in their sector — not as a threat briefing, but as a shared picture of where things are heading?
- Human strengthsWith nine of eleven staff scoring strong or very strong human strengths, this organization has significant capacity to evaluate AI tools on their merits rather than adopt them by default. Is there a mechanism for that kind of evaluation — a process by which staff can assess whether a tool actually fits their work?
Where organizations with this profile tend to focus
This is not a recommendation. It’s an observation about what organizations that have understood their baseline tend to prioritize. Some of these will be relevant. Some won’t. That judgment belongs to your leadership team.
Common focus areas after a Snapshot
Role-level conversation before org-level decision
Rather than making a broad organizational decision about AI, starting with individual conversations about specific roles and specific tasks — particularly in the elevated-exposure cluster. Understanding what the work looks like day to day, and where people see change already happening, tends to produce better decisions than top-down policy.
Tech comfort as a starting point, not a problem to fix
Organizations with mixed tech comfort scores rarely find that mandatory training moves the dial. What tends to work is giving the building-comfort group low-stakes opportunities to encounter technology on their own terms — alongside colleagues who are already comfortable, not in a classroom setting.
Positioning strengths before addressing exposure
In profiles where human strengths are strong across the board — as they are here — organizations that start by naming what the team does well tend to have more productive conversations about change than those that lead with the exposure numbers.
Watching specific functions rather than monitoring broadly
With exposure concentrated in administrative, records, and finance, organizations in this position tend to focus attention on those specific functions rather than treating AI as an organization-wide issue. The data tells you where to look first — not everywhere at once.
Why no one is identifiable
Privacy is structural, not a promise
Individual reports are always private. The employer receives aggregate data only — never a single person’s results. This is what makes the data honest: people answer truthfully precisely because no one is looking over their shoulder, the same way anonymous engagement surveys work.
In a live report, any role held by a single person is grouped into a broader category so no individual can ever be picked out of the numbers. The role-by-role table above exists in this document only because the organization is fictional. It does not represent what an employer sees.