Make AI adoption actually stick

AI rollouts trigger resistance patterns that conventional software rollouts do not. Three reasons: (1) AI changes how people make decisions, not just which tools they use, which threatens professional identity and status, especially for senior experts. (2) AI deployment surfaces unresolved questions about accountability, fairness, and ethics that previous rollouts never raised. (3) The shadow-AI usage already present in most organisations means you are not introducing AI, you are formalising a contested status quo. These three dynamics produce resistance that traditional rollout playbooks ignore, which is why 70%+ of AI initiatives fall short of their business case.

Generic OD consulting produces qualitative narratives and workshop outputs that cannot be defended to a sceptical sponsor or replicated across stakeholders. Our programme produces: (1) a defensible per-stakeholder diagnosis traceable to specific behavioural signals via MLRC, (2) intervention sequences drawn from peer-reviewed literature with published conversion benchmarks, (3) Kirkpatrick four-level instrumentation with measurable leading and lagging KPIs, and (4) integration with the technical implementation under a single engagement letter. Most OD consultancies cannot deliver any of these four.

Yes. Regulated-industry engagements include sector-specific layers: financial services adds MiFID II conduct and operational-risk overlays, healthcare adds clinical-safety and HIPAA workflow integration, manufacturing adds operator-safety and ISO 9001 quality-system alignment. All engagements include GDPR and Swiss nFADP compliance for the survey, interview, and behavioural telemetry data. EU AI Act high-risk-system implications are integrated where the AI system being rolled out qualifies.

This is the most common starting point we see. The first job of the discovery phase is diagnosing exactly why the previous attempt failed, usually a combination of: missing sponsor commitment, premature deployment without reinforcement systems, communication treated as broadcast rather than dialogue, or no per-stakeholder intervention design. Cynicism is a Logic-type resistance pattern, well-documented in the literature, and responds to data transparency and demonstrated competence rather than to messaging. We design the early phases specifically to convert cynics into early validators before the broader rollout.

Both. We deliver the diagnostic, the intervention design, the communication plan, and the training pathway. Training delivery is either run by us, run by an internal L&D partner against our designed pathway, or co-delivered with peer champions we identify and equip during the discovery phase. The training is one channel among several. Resistance does not dissolve through training alone, which is the most common reason large training investments fail to move adoption metrics.

Standard engagements run 8 to 12 weeks from kickoff to deploy, with a 6 to 12 month sustainment cadence afterwards. Deep engagements for board-level or multi-site transformations run 12 to 24 weeks active plus 24 month sustainment. All engagements are fixed-fee, scoped at the discovery call, with no hourly billing and no scope creep. Pricing reflects the size of the affected population and the regulatory complexity of the sector.