Capability 07 · Direction
Deciding what to build, and what not to
AI strategy & readiness
A roadmap that names the projects to decline.
In one paragraph
Siyada Tech runs AI strategy and readiness assessments for Saudi enterprises and government entities. We review data, systems, governance and skills against the use cases under consideration, then return a prioritised roadmap: the cases worth funding, what each one needs first, and the ones to decline.
- Readiness assessment
- Sequenced roadmap
- Decline recommendations
01What it is
A structured assessment that produces a use-case portfolio, a readiness view across data, platform, governance and people, and a sequenced roadmap with costs, prerequisites and decision criteria. Written to be acted on, and owned by the client.
02Who it is for
- Executives deciding where to invest in AI
- Transformation offices and PMOs
- Government entities aligning AI plans with national guidance
- Procurement teams evaluating AI vendors
03The problem
Organisations fund pilots on enthusiasm rather than readiness, then discover that the data is not accessible, the process is not defined, or nobody owns the system after handover.
04How it works
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01
Interview process owners and review the systems and data each candidate use case depends on.
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02
Score readiness across data, integration, governance and operating capability.
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03
Size each use case on value, feasibility and risk.
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04
Sequence a roadmap with prerequisites and explicit decline recommendations.
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05
Define how success will be measured before anything is built.
05Where it runs
- A fixed-scope engagement with workshops and a written report
- Optional follow-on delivery of the first prioritised use case
- Reports written for executive and board review
06Security and data
- Assessment material handled under NDA, and kept in the client's environment where required
- PDPL and NDMO considerations assessed for each use case
- Governance recommendations written against SDAIA AI-ethics principles
07Evidence
What we measure here. Results are published once each one has a stated method, sample size and evaluation date. How we publish evidence
- Share of assessed use cases taken to production
- Time from roadmap to first production release
- Share of cases recommended for decline
08What it is not
- The assessment reflects the information made available during the engagement.
- Value estimates are ranges built on stated assumptions, not guarantees.
- A readiness score is a decision aid, not an audit or a certification.
?Asked often
Questions
What is an AI readiness assessment?
A structured review of data, systems, governance and skills against the use cases you are considering, producing a prioritised roadmap with explicit prerequisites.
Will you recommend against building?
Yes, when readiness or value does not support it. Declining a case is a valid outcome, and often the most valuable one.
How long does it take?
It depends on scope and on stakeholder availability. Our typical range is not yet published to our evidence standard: [EVIDENCE REQUIRED].
Does it align with SDAIA guidance?
Governance recommendations are written against SDAIA's AI-ethics principles and PDPL obligations.
Is there a quick self-check first?
Yes. The readiness self-check takes a few minutes and shows where to look first. It is a starting point, not an assessment.
How do we start?
A scoping call to agree the units, use cases and people in scope.
Start with an assessment
We review readiness against your candidate use cases and tell you which ones deserve funding, and which do not.
Last reviewed · Siyada Tech engineering