Direction and organisational readiness
AI Strategy, Readiness & Roadmap
A prioritised 90-day AI roadmap with named owners, resource needs and a business case.
Assess organisational readiness and capability for a proposed AI use in your business context. Align leaders, prioritise opportunities and plan people, responsibilities, resources and business value. Compare data readiness, supplier selection and investment options; define intended agent actions and technical dependencies.
Three key deliverables
- Organisational capability and readiness profile with leadership alignment
- Prioritised opportunities with business-value and feasibility assumptions
- 90-day roadmap with people, responsibilities, resources and review points
Best fit
You see potential in AI but need leadership agreement on where to start and what the organisation can support.
What we need to begin
- A sponsor who can align leaders around a proposed AI use and its business purpose.
- Access to workflow owners, affected employees, HR and relevant specialists, plus a high-level view of tools and data restrictions.
What you receive
Organisational capability and readiness profile with leadership alignment
Prioritised opportunities with business-value and feasibility assumptions
90-day roadmap with people, responsibilities, resources and review points
Business case with data, supplier and implementation dependencies
Opportunity map
- Customer-support drafting
- Propose a drafting pilot with a named authorising owner. Test blocked sends and record changes; any later expansion requires separate approval and technical validation.
- Order intake
- Map exceptions and validate data quality and integration before requesting a pilot.
- Inventory forecasting
- Assess historical data and compare with a simple forecasting baseline before any investment decision.
Organisational capability, in context
We assess readiness for a specific proposed AI use in its organisational context. Interviews, working sessions and available records show what is in place, where evidence is missing and what needs attention across eight dimensions.
- Purpose and direction
- Agree the business purpose, expected value and scope of the proposed use, including what leadership will prioritise or defer.
- Responsibilities and coordination
- Identify accountable owners, decision rights and coordination between business, HR, IT and risk.
- Work and roles
- Examine tasks, handoffs, role impacts, human review capacity and workload with the people doing the work.
- Leadership and management
- Clarify sponsorship, management decisions, available time and the support managers need to guide the change.
- Skills and learning
- Assess leadership and role-specific skills, practical AI literacy, learning needs and access to support.
- Participation and communication
- Plan employee participation, clear communication, feedback and responses to concerns.
- Tools, data and safeguards
- Check approved tools, data quality, access, integrations, permissions, human oversight and specialist validation needs.
- Results and adaptation
- Agree baseline evidence, quality, total effort and adoption measures, then assign reviews and adjustments.
The profile records evidence, gaps and priorities for the proposed use, with owners and review points. There is no combined maturity score: strengths in one dimension do not cancel a gap in another. These eight diagnostic dimensions sit alongside the five perspectives used to navigate our services.
Illustrative examples
Which opportunity is ready for a test?
Compare expected business value with practical feasibility. Select a scenario to inspect the assumptions, data needs and next step.
Higher feasibility means simpler integration, usable data and available skills and capacity. Risk, privacy, security and permission are separate approval considerations.
Fictional scenarios to explain the method. Positions are assumptions, not measured results or approval to use AI.
How the work unfolds
Define the proposed use and context with leaders and employees. Review eight organisational dimensions, current AI use, work and roles, skills, resources, data quality and restrictions; record evidence and gaps.
Align leadership on priorities. Compare expected business value, total costs, readiness and supplier options. Keep risk and permission as separate approval checks.
Agree a 90-day roadmap with people, responsibilities, resources and review points. Specify intended agent actions and authority limits; name specialists for permissions, integrations and implementation validation.
Your team’s contribution
Leaders, workflow owners and affected employees contribute evidence about current work, capacity and priorities. HR helps assess role and learning needs. Your IT and security specialists validate data, access and feasibility assumptions.
Timing and review points
The sprint is scheduled around access to the right people and an agreed review point. The 90-day roadmap is a planning output, not the duration of the engagement.
How the fee is scoped
The proposal reflects the number of teams, opportunities, interviews and review rounds. Share those inputs in your brief so the schedule and fee can be scoped.
Where responsibilities sit
Ada Studio provides decision and adoption advice. Client leadership retains employment decisions and investment approvals; relevant specialists retain technical feasibility, procurement, implementation and security validation.