Senior Specialist - Digital Products & Business Intelligence

The Senior Specialist, Digital Products (AI) is responsible for shaping and executing the AI workstream within the digital products portfolio. The role owns the AI roadmap, ensuring alignment with the wider product roadmap and organisational strategy, and drives the identification, assessment, and delivery of high-impact AI use cases from concept through to implementation, monitoring, and refinement. Operational Develop and maintain the AI roadmap for the Registration Authority, ensuring alignment with the digital products roadmap and the central AI programme. Own and continuously refine the AI use case assessment and prioritisation framework, ensuring it remains fit for purpose as the portfolio and technology landscape evolve. Identify, document, maintain and prioritise AI use cases across business functions, applying the prioritisation framework consistently. Prepare business cases and requirements documentation for approved use cases, including success criteria and measurable KPIs. Manage prioritised use cases with technology teams and vendors through to delivery, acting as product owner for AI initiatives. Ongoing analysis of market and technology landscape to identify tools, platforms, and emerging capabilities that can support delivery of the AI roadmap and make recommendations for evaluation or adoption. Produce regular reporting on delivered AI tools and solutions, covering adoption, performance against success criteria, efficiency gains, and lessons learned, for management and relevant governance forums. Assess the operational, regulatory, and data impact of AI implementations prior to deployment. Ensure all AI implementations and tooling comply with information security requirements, data protection obligations, and organisational technology governance, coordinating with relevant teams for assessment and approval. Establish ongoing monitoring of deployed solutions, tracking performance against defined success criteria and identifying opportunities for refinement. Manage AI-related risks, including model accuracy, data quality, security, and responsible AI considerations, in line with organisational governance and applicable regulatory requirements. Define UAT acceptance criteria in line with documented requirements, coordinating testing activities with product teams, business users and technology teams. Lead user acceptance testing (UAT) for developed products, following established procedures to validate functionality, accuracy, and usability prior to release. Ensure defects and gaps identified during testing are logged, tracked, and resolved before solutions are exposed to end users, with formal sign-off recorded. Support product teams in roadmap delivery, including defining success criteria, tracking metrics, and reporting on outcomes. Provide analytical and documentation support across the digital products portfolio as required. Design, build, and maintain internal AI agents and automations using existing enterprise technologies (e.g. Microsoft Copilot Studio, Power Automate) to drive operational efficiency within the Authority. Develop training materials, guidance, and outputs to support adoption of AI tools across teams. Act as an internal champion for responsible and effective AI usage. Information Security related Understand, adopt, adhere and practice responsibilities or controls as per ADGM Information Security policy and as per best practices explained in the induction and awareness sessions. Confidentiality, Integrity and availability of the ADGM Information shall be maintained at all times i.e. within as well as outside ADGM. Bachelor's degree in a relevant field (computer science, business, engineering, or similar) Education & Work Experience Bachelor's degree in a relevant field (computer science, business, engineering, or similar) 8 years+' experience in product ownership, business analysis, or digital transformation, with demonstrable exposure to AI/ML initiatives. Demonstrable experience leading AI programmes or initiatives end to end, including use case identification, prioritisation, delivery, and post-implementation monitoring. Hands-on experience with low-code AI/automation platforms (Copilot Studio, Power Automate, or equivalent). Experience writing requirements documentation, business cases, and prioritisation frameworks. Experience planning and leading UAT within structured delivery processes. Familiarity with AI governance, risk management, and responsible AI principles; regulatory environment experience an advantage .

Bachelor's degree in computer science, business, engineering, or a related field. 8+ years of experience in product ownership, business analysis, or digital transformation with demonstrable exposure to AI/ML initiatives. Demonstrable experience leading AI programmes end to end, including use case identification, prioritisation, delivery, and post-implementation monitoring. Hands-on experience with low-code AI/automation platforms (Copilot Studio, Power Automate, or equivalent). Experience writing requirements documentation, business cases, and prioritisation frameworks. Experience planning and leading UAT within structured delivery processes. Familiarity with AI governance, risk management, and responsible AI principles; regulatory environment experience is advantageous.

Shape and execute the AI workstream within the digital products portfolio, owning the AI roadmap and aligning it with the wider product roadmap and organisational strategy. Identify, document, maintain and prioritise AI use cases across business functions; prepare business cases and requirements documentation including success criteria and KPIs. Manage prioritised use cases with technology teams and vendors through to delivery, acting as product owner for AI initiatives. Monitor market and technology landscape to identify tools, platforms and capabilities; produce regular reporting on AI tool adoption and performance. Ensure AI implementations comply with information security, data protection and governance requirements; coordinate assessments and approvals. Establish ongoing monitoring of deployed solutions and manage AI-related risks in line with governance and regulatory requirements. Define UAT acceptance criteria and coordinate testing with product teams and stakeholders; lead UAT and ensure defects are logged, tracked and resolved before release. Support roadmap delivery by defining success criteria and tracking metrics. Design, build and maintain internal AI agents/automations to drive operational efficiency. Develop training materials to support adoption of AI tools; promote responsible and effective AI usage. Maintain information security responsibilities and confidentiality/integrity/availability of information.