Built for CAIOs, CIOs, and technology leaders designing the AI function as priorities, structure, and scope are still forming.
A board approves an AI plan, delegates execution to the CIO, CAIO, or CHRO, and opens requisitions against a generic role taxonomy, in that order, across mid-market and enterprise organizations almost every time. Time-to-fill stretches past forty-four days, candidate abandonment runs above sixty percent, and most hires that land do not stay eighteen months. Leaders treat the problem as a labor-market issue or a JD problem, but role design causes the failure: it is an output of work specification, not an input to it.
The AI function is structured around a small set of archetypes that serve four distinct organizational purposes. Each archetype carries its own compensation band, reporting line, skill signature, and sequencing logic, and together they constitute the twelve-role taxonomy published inside the toolkit. The preview below shows the shape of the taxonomy; in the reference guide, every role is named, positioned, and specified in full.
Three previews follow, each partially redacted for this public page. Inside the toolkit, all three appear in full and in context.
| Archetype | Strat | ML | MLOps | Data | Gov | Prod |
|---|---|---|---|---|---|---|
| Chief AI Officer | E | F | F | P | E | P |
| Head of AI Strategy | ||||||
| AI Product Manager | ||||||
| ML Engineer | ||||||
| + 8 more archetypes |
E = EXPERT . P = PROFICIENT . F = FOUNDATIONAL
Eleven more cards inside. Comp bands and skill signatures unredacted in the toolkit.
Because role design is downstream of work specification, six organizational dimensions must be scored before any archetype is ranked. The toolkit scores each dimension on a five-point scale, feeds the results into a priority scorecard, and produces a hiring sequence that reflects your actual organizational signals rather than the market's defaults.
Each input's definition, scoring rubric, and consequence chain lives in Chapter 2 of the reference guide.
The three composites below, drawn from recurring patterns across RBD. client engagements in insurance, financial services, manufacturing, and professional services, illustrate the same toolkit producing three distinct hiring plans. The six input specifications score differently in each organization, so the resulting sequence differs too, by design.
Composite organizations, not specific clients. Patterns consolidated from multiple RBD. engagements.
The toolkit is delivered as two instruments designed to be used together. The reference guide specifies the framework and publishes the full archetype taxonomy. The working Google Sheet turns your organization's inputs into a live priority scorecard and a quarter-by-quarter hiring sequence, both of which recompute as you adjust the signals.
A five-chapter publication in the RBD. format containing the full framework, every archetype, every input specification, every decision tool, and three applied cases at three organizational scales.
Copy the master Sheet into your Drive in a single click, fill the six dropdowns on the Input Specs tab, and watch the priority scorecard recompute live as the hiring sequence builds itself against your organizational signals.
The Toolkit delivers the working instrument. The Workforce 2030 research brief supplies the strategic context around it, open reading in the research library. Your key opens the Toolkit immediately after purchase.
For context. An executive search for a Chief AI Officer typically runs $50K to $150K in retainer fees and ninety-plus days of calendar time, and a misfire at day forty-four costs measurably more than both. The toolkit sits upstream of that process, specifying the work before requisitions open, for $195 once.
Four forces are reshaping enterprise talent strategy simultaneously, and each one compounds the others. The toolkit provides the operational response. The companion research brief, Workforce 2030: Four Forces Reshaping Enterprise Talent Strategy, provides the strategic narrative for the pressure the four forces together generate, and it is open reading in the research library.
Both. The reference guide specifies the framework, and the companion Google Sheet operationalizes it: you fill six dropdowns on the Input Specs tab, the Priority Scorecard ranks archetypes against your organizational signals, and the Hiring Sequence pulls the top four into a Q1 through Q4 plan automatically. A senior leader can produce a defensible hiring plan in a single sitting.
Generic taxonomies list archetypes; this toolkit sequences them. The ten-skill matrix surfaces which roles are too narrow or too broad for your context, and the six input specifications determine which archetype comes first for your organization rather than for the market as a whole. The decision tree also catches the single most common hiring error we see in post-mortems of failed AI programs: the Bridge cluster is routinely skipped, and the diagnosis almost always points back to that omission. No JD library contains that pattern, because the pattern is organizational rather than role-level.
Yes, and the framework sequences regulated organizations differently by design. Under the EU AI Act and comparable U.S. regimes, the AI Ethics and Governance Lead functions as a named regulatory contact rather than a ceremonial reviewer. Composite Two in the applied cases is modeled on a $12B-AUM financial services firm where the resulting sequence hires governance before delivery. The Workforce 2030 brief in the research library covers the broader compliance dimension.
Yes. Composite Three in the applied cases is modeled on an enterprise SaaS organization with a CAIO already seated, and the sequence that follows identifies Product Manager, MLOps, and Data Product Owner as the next three hires. The toolkit functions as the decision framework for the second, third, and fourth hire rather than the first. The ten-skill matrix also serves a secondary diagnostic purpose, because it surfaces whether the CAIO in seat is operating as a CAIO or as a relabeled CIO, which is a question worth running explicitly.
The complete toolkit: the five-chapter reference guide with all twelve archetypes, the six input specifications with scoring rubrics, the ten-skill matrix, the decision tree, the hiring sequence, the JD template, the three applied cases, and the ten-tab working Google Sheet that operationalizes all of it. Your access opens immediately after purchase. The Workforce 2030 research brief that supplies the strategic backdrop is open reading in the research library.
Built to be used inside a single leadership conversation. Bring it to the next board meeting, the next search firm briefing, or an executive team session where AI hiring is on the agenda.