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AI Transformation Simulation · Adoption Reset

Transformation isn't a communications problem. It's a sequence.

The same interventions, run in the wrong order, stall. Flag where your transformation is stalling, sequence the plays that move each segment, and watch the adoption curve evolve, including what happens when you deploy a play before the proof it needs exists.

A note on this tool

A deliberately simplified model, not a forecast of your organization. It makes one thing visible: how the order and timing of your interventions compound or stall across a whole population. Use it to build intuition for the shape of the work.

1

Flag where the transformation is stalling

Set each segment's share of your people on the left, then click the 2–3 cells where they're stuck
Precontemplation"no problem here"
Contemplation"maybe there is"
Preparation"I'll try"
Action / Maintenance"I'm doing it"

Population set: 100 / 100% of your people (raise one segment by freeing room in another)

0 cells flagged. These are the bottlenecks your sequence should target. Plays that hit a flagged cell land harder, and the bigger that segment's share of your people, the harder they pull.

2

Sequence your interventions

Click a play to add it · drag to reorder · independent plays overlap automatically, so the calendar compresses below the sum of their durations

Your 24-week plan

0 / 24 weeks
Click plays on the left to build a sequence. Order, and how long each play runs, both matter — independent plays overlap automatically, so calendar time is less than the sum of their durations.
    3

    Watch the curve evolve, and what each move demands

    100% 75% 50% 25% 0% Launch Week 6 Week 12 Week 18 Week 24 Sustain phase · institutionalize Self-sustaining transformation ↑
    Your sequenced plan Value realized (real output: speed, quality, results) Do nothing (adoption erodes without reinforcement)
    —
    Week-24 adoption, your plan
    —
    Week-24 value realized
    —
    Points of adoption your sequence adds

    The revolution, in phases

    A transformation isn't a project you finish. It's a set of thresholds an organization crosses. Each lights up when your sequence carries it there.

    What to get right, in order

    The groundwork each step needs, in order. A play run out of order, or without the foundation it leans on, gets flagged. Use the toggle to see the real outcome each move drives (speed, quality, results) alongside how far it widens reach.

    Illustrative model, not a forecast. What it isolates: the sequencing of a transformation, namely who moves first, how proof gates the next play, why sponsorship sets the ceiling on how far change spreads (won directly, or earned by a bottom-up win that demonstrates results), why adoption without capability is usage rather than value, and how a mistimed move breaks trust and breeds quiet resistance. It renders the logic of the Adoption Matrix and the Adaptability field note. What it can't see: a simulation moves averages; real change turns on specific people. One leader with the capital to fund it and go first, or to quietly starve it, can decide the outcome, and no curve names that person, or tells you whether a sponsor truly leads or a manager truly coaches. That human work, with your real people and data, is what the Adoption Reset builds. The tool is the map; the people who walk the terrain are the engagement.

    The lesson in the model

    The work is in the execution.

    The model earns one honest claim: sequence and timing shape the outcome. Put the laggard path or the skeptic reframe in week one and it barely moves the line, because there is no peer proof yet for it to stand on. Seed proof with your innovators first, equip managers early to amplify what follows, and the same plays compound. Push a move onto people who aren't ready and it does worse than fizzle. It spends trust, and the curve can bend back down as people stop responding.

    Every one of those effects assumes the work was carried out well, and that is what reality tests hardest. A simulation moves segments and averages. A transformation moves specific people: the sponsor who actually goes first, the manager who coaches the judgment behind the tool, the champion who is genuinely respected. None of it runs itself. Your team clears the time, has the conversations, and holds the line when the launch energy fades. The model shows you the shape of the work and where a sequence gains or loses ground. The work itself is on the ground, in the execution. That is the part we do together.

    Get your simulation summary

    Get the finished summary sent to you.

    You've built a working model. Request the finished summary and Tom sends it to you personally: a single sheet with your curve, your sequence, and the read on where the transformation holds or breaks, plus a short take on what it means for your actual rollout. The simulation you built is attached automatically.

    Included in the report

    Build a sequence above and your report will include a plain-English read on the common pitfalls hiding inside it: the traps most teams underestimate, written to read on its own and share with your team.

    No list, no drip sequence. One human reply.

    Messages route to sail@tdcatalyst.com. Prefer to talk? Book a Fit Call →

    The engagement behind the tool

    Adoption Reset · 60–90 days

    Diagnosis by role and workflow, a population mapped onto the matrix, and a sequenced set of interventions for the cells where adoption is actually stalled. Enablement delivered through two workshops for leaders and champions. You walk away with a plan built around behavioral change, not communications volume, and usage that survives the quarter after launch.

    See the engagement Book a Fit Call
    Sources

    The simulation is TDcatalyst's own synthesis of four decades of behavioural science, shaped by hands-on experience leading AI and digital transformations across Fortune 100 and public-sector organizations. What follows separates the frameworks TDcatalyst developed from the published research they stand on.

    Developed by TDcatalyst

    • The Adoption Matrix. The operational grid that crosses Rogers' diffusion segments with Prochaska's stages of change, so a leader can locate exactly where a population is stuck and match the play to the cell. Set out in the Adoption Matrix field note.
    • The sequencing logic. The dependency graph the model enforces: sponsorship as the ceiling on how far change spreads — won directly or earned by a demonstrated bottom-up win — proof before the plays that borrow its credibility, capability as what converts adoption into value, and institutionalization held for the sustain phase. Distilled from what holds and what decays in real rollouts.
    • The trust-and-relapse model. Treating a mistimed intervention as active harm: it breaks trust, dampens how people respond to everything after, and can bend the adoption curve back down into performative relapse. TDcatalyst's modeling of a pattern seen repeatedly in the field, read through self-determination theory and Turner's liminal collapse.
    • Transformation as a marked passage. The five phases and the escape-velocity threshold, framing a transformation as a set of thresholds an organization crosses and holds. TDcatalyst's application of rites-of-passage theory to the AI transition, set out in the Adaptability field note.

    The frameworks it stands on

    1. Everett M. Rogers, Diffusion of Innovations (5th ed., 2003). The population's split into innovators/early adopters, early majority, late majority, and laggards (the 16 / 34 / 34 / 16 segment sizes), the chasm between early adopters and the majority, and the “whole product” requirement all come from Rogers. In the model this is the matrix's row axis and the reason proof must precede the majority-belief plays.
    2. James O. Prochaska and Carlo C. DiClemente, “Transtheoretical Therapy: Toward a More Integrative Model of Change,” Psychotherapy (1982). The five stages of change — precontemplation, contemplation, preparation, action, maintenance — are the matrix's column axis, and the finding that a mismatched intervention (right message, wrong stage) is a leading cause of underperformance is the basis for the trust penalty.
    3. Susan Michie, Maartje van Stralen, and Robert West, “The behaviour change wheel: a new method for characterising and designing behaviour change interventions,” Implementation Science (2011). The COM-B model (capability, opportunity, motivation) groups the intervention library into the Opportunity, Capability, and Motivation families.
    4. John P. Kotter, Leading Change (1996). The eight-step model informs several plays: the guiding coalition and visible urgency behind Executive Sponsorship, the short-term wins of Proof Seeding, and anchoring the change in the culture through the sustainment plays.
    5. Kurt Lewin, the unfreeze–change–refreeze model (1947). The arc from loosening the old way to refreezing the new sits under the phase progression, and the refreeze is exactly the reinforcement the Policy, Performance Criteria, and Ritual plays provide.
    6. Edward L. Deci and Richard M. Ryan, Intrinsic Motivation and Self-Determination in Human Behavior (1985). Autonomy, competence, and relatedness are why mandates produce compliance or “quiet resistance” rather than commitment; this underwrites the trust-erosion mechanic and the laggard play's one-to-one, non-spotlight design.
    7. BJ Fogg, Tiny Habits (2019) and the Fogg Behavior Model (B = MAP). Behaviour needs motivation, ability, and a prompt to converge; the model's emphasis on ability (capability building, workflow redesign) over motivation alone is the Fogg inversion.
    8. Peter M. Gollwitzer, “Implementation Intentions: Strong Effects of Simple Plans,” American Psychologist (1999). The two-to-threefold uplift from “when situation X arises, I will do Y” plans is the When-Then Prompts play.
    9. Geoffrey A. Moore, Crossing the Chasm (1991). The pragmatist majority adopts only once the whole product and credible peer proof exist — the dependency the model encodes between Proof Seeding, Peer Proof Relay, and the Whole-Product Kit.
    10. Chip Heath and Dan Heath, Switch: How to Change Things When Change Is Hard (2010). The rider / elephant / path frame for equipping managers as the change channel is the Manager-as-Channel play and its amplifier effect.
    11. Jeff Hiatt / Prosci, ADKAR: A Model for Change (2006) and Prosci's benchmarking on active and visible sponsorship. Sponsorship as the single strongest predictor of success is modelled as a hard gate; ADKAR's Reinforcement stage is the sustainment plays (policy, criteria, ritual).
    12. The change curve, the “valley of despair” adapted from Elisabeth Kübler-Ross's stages, with William Bridges, Transitions (1980). The productivity dip before the payoff, drawn on the chart whenever a workflow is genuinely redesigned, is this curve.
    13. Arnold van Gennep, Les rites de passage (1909) and Victor Turner, The Ritual Process (1969). The separation / threshold / reincorporation architecture and Turner's “liminal collapse” (premature certainty that produces the symptoms ritual prevents) underpin the five transformation phases, the “liminal” below-threshold state, and the performative-relapse behaviour when trust is lost. See also Jonathan Shay, Achilles in Vietnam (1994).

    The simulation renders this logic. It is an illustrative teaching model, not a calibrated forecast.