For global
organisations.

Three years deep,
not three quarters in.

Most enterprise AI advisory was built in 2024 or 2025, after the generative AI wave became impossible to ignore. Large consultancies retooled existing transformation practices and rebranded them. Enterprise is the long alternative. The Darla Method has been in active corporate use since January 2023 (Day 32 of ChatGPT's public existence) and was being taught publicly from October 2023 onward, over two years before the academic AI Fluency Framework was published. When that framework arrived, the alignment with what was already being taught was so complete that the first Anthropic Academy course was completed without working through the material at all.

Thirteen Anthropic Academy courses completed. Twelve certificates issued. 550+ professionals trained across nine countries. The framework taught is the academically co-badged Teaching the AI Fluency Framework, published jointly by Anthropic, University College Cork, Ringling College of Art and Design, the Higher Education Authority of Ireland, and the National Forum for the Enhancement of Teaching and Learning. Not borrowed. Recognised.

Enterprise also differs structurally: David delivers and leads personally rather than via the consultancy pyramid model. There is no junior consultant team behind the senior name on the proposal. The methodology, the framework, the implementation, and the executive accountability all come from one named senior practitioner who has been doing this work since the practice began.

David embedded on the org chart as the named senior AI lead, on a retainer basis. Responsibilities span AI strategy, governance framework, adoption tracking with monthly board reporting, model upgrade briefings, workflow refreshes, ExCo access for leadership meetings, and a quarterly-updated strategic AI roadmap. Senior AI accountability on the executive team without committing to a full-time Chief AI Officer hire.

Region-specific cohorts running in parallel on a shared global framework. Each region adapted to local context while sharing common architecture, common assistants, and common adoption metrics. The framework moves at the speed of the business rather than at the speed of one delivery team.

Per-function and per-role assistants built across the organisation. Sales, marketing, operations, finance, HR, legal, engineering. Each configured to the function's actual work, standards, and recurring tasks. Not vendor demos. A working ecosystem the organisation owns and refines.

Policy on AI use, data handling protocols, escalation paths for high-stakes decisions, transparency standards for AI involvement in published or credited work, board-facing reporting cadence. Diligence (accuracy, ethics, accountability) treated as a first-class principle from week one rather than retrofitted after rollout.

Multinational organisations deploying AI as a strategic capability across multiple regions and business units. Typically commissioned at board or C-suite level when AI moves from operational tool to competitive necessity. Designed for situations where governance, consistency, and capability maintenance across regions all matter as much as the training itself.

Multi-region delivery on a shared global framework. Region-specific cohorts running in parallel, each adapted to local context while sharing common architecture, common assistants, and common adoption metrics. David is embedded as fractional Chief AI Officer on a retainer basis, providing strategy, governance, and delivery oversight. Custom AI assistant ecosystem built across functions. Governance framework, data handling policy, and escalation paths integrated from week one.

David Ward embedded on the org chart as the named senior AI lead, on a retainer basis. Responsibilities include AI strategy, governance framework, adoption tracking with monthly metrics reported to the board, model upgrade briefings, workflow refreshes, board and ExCo access for leadership meetings, and a quarterly-updated strategic AI roadmap. The role is designed for organisations that need senior AI accountability on the executive team without committing to a full-time Chief AI Officer hire.

Three things. First, the methodology has been in active corporate use since January 2023, over two years before the academic AI Fluency Framework was published. Large consultancies were reselling vendor decks while the Darla Method was already in third-year refinement with regional clients. Second, the framework taught is the academically co-badged Teaching the AI Fluency Framework, published jointly by Anthropic, University College Cork, Ringling College of Art and Design, the Higher Education Authority of Ireland, and the National Forum. Third, David delivers and leads personally; there is no junior consultant pyramid behind the senior name on the proposal.

Governance scaffolding is built in from week one. Policy on AI use, data handling protocols, escalation paths for high-stakes decisions, transparency standards for AI involvement in published or credited work, and a board-facing reporting cadence. The framework treats Diligence (accuracy, ethics, accountability) as a first-class principle alongside the technique-focused disciplines, which most corporate AI training treats as a checkbox at the end.

Every Enterprise engagement begins with the AI Readiness Audit (four weeks) to scope the actual situation. The proposal includes a benchmark comparison against McKinsey, BCG, Accenture, and Deloitte for equivalent multi-region engagements. Commercial appendix covers MSA, IP ownership, data security, and SLA. Pricing is structured around scope, regions, and the duration of the Fractional Chief AI Officer engagement rather than headcount alone.