Regenerative Org Transformation
Accompaniment & Network
Limicelia
Regenerative Organizational Transformation
Accompaniment & Network
Limicelia · Regenerative Tech & AI

AI that replenishes
rather than depletes.

Most AI adoption creates workload creep — tasks get easier, so more gets done, until the cognitive load exceeds what the productivity gains justified. We help organizations build the North Star, organizational imagination, and boundary practices that make AI regenerative rather than extractive.

The Problem
01

AI is making
burnout worse.

UC Berkeley researchers named it workload creep: AI makes tasks easier, so workers do more. Expectations rise to match new capacity. Workers feel they should accomplish more because AI makes it feel possible. Result: more work done, but higher cognitive load and burnout. 83% of workers are experiencing burnout (DHR Global, 2024). 77% say AI decreased productivity and increased workload (Upwork, 2024).

Without intention, AI makes it easier to do more — but harder to stop. Most AI adoption frameworks focus on tools, adoption rates, and productivity metrics. None of them ask: Why are we using this? What becomes possible with the capacity it creates? What prevents workload creep?

What's missing from traditional AI adoption: no conversation about why (beyond "productivity"), no organizational imagination about what becomes possible, no North Star guiding when to use and when to stop, no worker voice in how AI changes work, no regenerative vs. extractive framing.

Our Approach
02

The six-phase arc
applied to AI.

We don't do AI implementation. We do accompaniment through AI transformation — frontline-first, co-discovery, stay-through-the-messy-middle.

Phase 01
Discovery
Map where AI drains vs. creates capacity. Not validating leadership's AI strategy. Listening for where technology is adding cognitive load, not reducing it.
Phase 02
Deep Listening
Frontline workers first — they know which AI tools help vs. hurt. The people whose work is being automated understand the texture of that work better than anyone.
Phase 03
Honest Diagnosis
Structure (how AI is deployed) produces behavior (burnout) — not worker failure. Naming the actual cause before designing responses to it.
Phase 04
Co-Design
The organization discovers its own AI North Star — frontline and leadership together. Values, usage boundaries, regenerative metrics. Not prescribed. Discovered.
Phase 05
Accompaniment
Staying as work patterns change. Holding accountability to agreements. Watching for workload creep as it emerges, not after it's become a crisis.
Phase 06
Harvest
Regenerative AI practice playbook — not a report. Replicable processes the organization owns. Capacity to navigate future AI transitions without us.
Key Concepts
03

Three ideas that
change how this lands.

AI North Star

A values-based framework that answers: Why are we using AI — beyond productivity? What outcomes do we want? What becomes possible with the capacity it creates? What won't we do? How do we measure regenerative vs. extractive impact? The North Star guides tool selection and use. It comes before choosing which AI products to buy — not after.

Organizational Imagination

The practice of envisioning what becomes possible when AI frees capacity. Instead of "do more faster," asking: What deep work has never had time? What quality was sacrificed for speed? What meaningful work has been pushed aside? Without this practice, AI simply intensifies existing patterns — more of what was already burning people out.

Regenerative vs. Extractive Adoption

Extractive metrics: productivity gains, adoption rates, time saved per task, ROI. Regenerative metrics: energy levels, workload creep monitoring, decision quality, meaningful work percentage, worker agency, boundary maintenance, innovation capacity. These are measurements of fundamentally different goals.

Services
04

Four entry
points.

AI North Star Design
Values · Boundaries · Regenerative Metrics
Build the values framework, usage guidelines, and regenerative metrics that guide AI adoption before tool selection begins. Includes organizational imagination facilitation.
2–3 months
Regenerative AI Implementation
Embedded Practitioner · Full Arc · Sustained Accompaniment
Full accompaniment through AI transformation. Phase 1: organizational imagination. Phase 2: role redesign with frontline input. Phase 3: practice design and North Star integration. Phase 4: sustainment and workload creep monitoring.
9–12 months
Organizational Imagination Facilitation
Capacity · Vision · Meaning
For organizations that have already deployed AI and want to ask the harder question: what should we do with the capacity we've created? Facilitated process for teams to envision work that actually matters, rather than defaulting to more of what already existed.
4–6 months
Regenerative Adoption Coaching
Purpose · Agency · Boundary Practice
For individuals and small leadership teams navigating AI adoption within larger organizational systems. Motivates healthy adoption through purpose and vision, not fear and pressure.
3–4 months

Ready to build your
AI North Star?

The starting point is a diagnostic conversation about where AI is already affecting your organization — and where the workload creep is beginning.

Start a conversation Back to home