Embed AI into your reality.
The problem
Most AI transformations don't fail at the model.
Not because the model didn't work. Because analysis and adoption were run as separate problems, with separate vendors, separate budgets and separate teams.
of companies report no tangible value from their AI investment.
Source: BCG, October 2024The three failure modes we see in the field
Tech-led only
Platform deployed. No role redesign. Adoption stalls inside three months.
Consultant-led only
Strategy deck delivered. No technical scaffolding. Nothing operationalises.
Change-led only
Comms and training. No mapping of what AI actually displaces, augments, or makes emergent.
The method
Four stages. One connected system.
Architect the work. integrate the systems. Design the human in the loop. Adopt the change. Each stage hands cleanly into the next. Select a stage to see what it delivers.
The stage
Map the work, task by task: what AI displaces, augments or creates, and who does each task (human, AI or both).
Method
- Data ingestion & inputs
- Task classification
- Performed-by allocation
- Emergent task discovery
- Reverse rollup & QA
Outcome
A future-state operating model, with every role's AI/human split named.
The stage
Stand up the tech, data and governance that lets the new way of working run, without unmanaged AI risk.
Method
- Data flow mapping
- 5-layer architecture
- Governance forum design
- Decision rights delta
- Guardrail register
Outcome
AI running inside a risk envelope any board would sign off: audit-ready and built for Australian requirements.
The stage
Redesign the roles around the new AI/human mix, with the capability and motivation each one now needs. Evidence, not opinion.
Method
- Future-state role cards
- 4×3 capability grid
- Cluster Reiss profile
- Multi-level interventions
- Leadership design brief
Outcome
Roles built around the new work, and the people, capability and motivation to fill them.
The stage
Make the change land and stay landed. Behaviour change and delivery run together, both halves required. Powered by Momentum.
Method
- Momentum profile per cluster
- Six OD workstreams
- Statutory sequencing
- Risk register
- Measurement framework
Outcome
A change that lands and stays landed: measured, sequenced, statute-compliant and behaviourally honest.
Engagement tiers
One product, three depths.
Function
AiDA Function
3 weeks
Who
SMEs (under 100 FTE) or a single function inside a larger business.
What
1 cluster. 5–10 roles. Indicative Reiss Motivation Profile®. ~80% AiDA-orchestrated.
Team
1 practitioner, AiDA-accelerated. Director to review.
Cluster
AiDA Cluster
6 weeks
Who
Mid-large organisations (250–2,500 FTE) with a lighthouse business unit or function.
What
3–6 clusters. 15–40 roles. Full cluster Reiss Motivation Profile®. Per-cluster adoption plan. All 5 architecture layers.
Team
Lead + 1–2 practitioners + Reiss specialist. AiDA-accelerated.
Enterprise
AiDA Enterprise
12–24 weeks
Who
Large organisations (2,500+ FTE), board-mandated, cross-functional dependencies.
What
6+ clusters. 40+ roles. Top-two-tier Reiss Motivation Profile®. Portfolio-level sustainment. Full behavioural design playbook.
Team
Principal + 2–3 practitioners, Reiss specialist, tech architect, change lead.
When AiDA can help
Technology and people, brought together.
AiDA develops and delivers an org structure that embeds AI in a way that drives long-term impact.
AiDA
Make AI part of how you actually work.
Analysis and adoption, one team, one budget, one system. The next step is a conversation.