Thinking about how organisations perform in an AI-enabled world
Connecting people, process, technology and culture — from global transformation to the emerging human–AI enterprise.
Designed and established Canon Corporate University and MyLearningZone, scaling blended learning across Europe.
A common learning capability and digital access across a multinational workforce. The figures describe rollout reach.
Led strategy, roadmap and governance across learning, skills, experience and an enterprise technology landscape.
Simplified architecture and aligned investment with business priorities. Directed a £10m learning technology workstream within a £200m HR transformation; the wider figure is programme context.
Implemented validated SuccessFactors Learning and centralised services, governance and operating processes.
Strengthened compliance, consistency and organisational agility across a regulated regional operation.
Designed an operating model connecting compliance, product, data and distribution, with AI-enabled content workflows.
Established the design and business case for scalable adviser enablement, education and communications. Outcomes remain framed as design contributions.
Scale and delivery evidence from Dominic’s CVs. Figures describe reach and programme scope; benefit statements describe the documented contribution.
Four interacting parts of organisational performance.
Talent · Learning · Leadership · Skills · Capability · Performance · Workforce · Employee experience
Operating models · Governance · Workflow · Compliance · Service design · Performance systems · Value realisation
Digital platforms · HR technology · Learning technology · Enterprise systems · Data · AI · Agents · Automation
Leadership · Communication · Engagement · Adoption · Behaviour · Trust · Change · Organisational readiness
What happens to talent strategy when organisations can acquire capability through people, agents or automation?
If AI can provide knowledge at the moment of need, what should corporate learning actually do?
Is declaring a skill useful, or should organisations capture evidence that someone can actually perform?
AI adoption changes work, roles, behaviour, incentives and trust alongside technology.
If an agent performs organisational work, does it eventually need objectives, competency evidence, permissions and performance management?
What is the difference between an organisation possessing information and actually being capable of acting on it?
A family of connected experiments around persistent capability intelligence, learning, careers, deliberation and the mixed human–AI workforce.
Persistent evidence of what people — and eventually agents — can do, rather than reducing capability to job titles or course completions.
ConceptNeed → experience → evidence → capability → next intervention. Learning as an evolving performance system rather than a catalogue.
In developmentExploring the distinction between model capability, deployed-agent competence, authorisation and currency.
Research propositionA concise guide for managers: what to do now, prepare next and watch over the longer term.
Practical Impact & archive →Vendor signals, capability comparisons and commercial implications—claims examined, dependencies exposed.
Tech Tack & archive →