AI governance – getting started
Establish an initial AI governance operating model with an owner, a lightweight AI Council, a use and risk register, rules, controls and reviews. For French-speaking Africa, the approach prioritises a pragmatic scope, rapid decisions, controlled costs and immediately usable deliverables.
- AI Value & Adoption
Qualify applications, risks, responsibilities and priority decisions.
Govern AI applications
AI use is spreading without clear responsibilities, a shared register or a decision cycle to assess risks, compliance and conditions for continuation.
Pain points
AI use is spreading without clear responsibilities, a shared register or a decision cycle to assess risks, compliance and conditions for continuation.
Promise
Quickly establish a proportionate governance cycle that governs AI use without blocking innovation: applications, risks, decisions, controls and reviews.
Outcome
Lightweight, workable governance: named roles, inventoried applications, assessed risks, recorded decisions, priority controls and a review schedule.
Recommended entry service
A short assessment to objectively map the situation, identify the major gaps and prepare a prioritised action plan.
Essential services
These services form the offer's foundation and contribute to the expected deliverables within the agreed scope.
AI Governance Starter
AI governance package: principles, roles, usage rules, use case validation, security, compliance and control.
AI Council Design & Operating Model
AI Council design: sponsor, success owner, IT, HR, communications, champions, recurring activities, decisions and backlog.
Responsible AI & Compliance Readiness
AI risk assessment: GDPR, EU AI Act, data protection, labels, agent security and usage rules.
Services to go further
Activate complementary services according to priorities, constraints and capabilities already in place.
Value Tracking Office
Benefits tracking framework: baseline, adoption, productivity, satisfaction, use cases, ROI and improvement plans.
AI CoE Design
AI centre of excellence design: roles, skills, governance, backlog, standards, support and operating model.
AI Portfolio Governance & Scale Review
Governance review cycle for scaling AI use cases: prioritisation, risks, value, dependencies and trade-offs.
Talk to an RFC expert
Describe your priorities, constraints and projects to prepare a discussion with the relevant teams.
Technology stack
Tools to support AI applications, governance and adoption according to the selected needs.
Operational governance
Organise responsibilities, rules and decision reviews.
(Step 01)
Inventory usages and decisions
Identify existing practices, the risks to control and the decisions that are hard to make today.
Deliverable
Map of usages and governance needs.
Explore the domain's other capabilities
Find complementary offers and areas of expertise to extend your approach according to your organisation's needs.
- See details...AI Value & Adoption
AI maturity & priority use cases sprint
Assess AI maturity, select the most defensible use cases and build a 90-day roadmap connecting value, data, risks, security and adoption. For French-speaking Africa, the approach prioritises a pragmatic scope, rapid decisions, controlled costs and immediately usable deliverables.
Talk to an RFC expert
Share your context, priorities and constraints. Our experts help you structure an IT journey aligned with your transformation goals.
Tell us about your challenges
Share your priorities to prepare for a focused discussion.