AI Value & MI Analyst- Edinburgh

FDM is a global business and technology consultancy seeking a AI Value & MI Analyst to work for our client within the Financial Services sector. This is initially a 6-12 month contract with the potential to extend and will be a hybrid role that will be based in Edinburgh.

Our client is establishing an AI Acceleration Centre to accelerate the adoption of AI-enabled software delivery practices across multiple technology organisations.

The AI Value & MI Analyst will play a critical role in measuring, monitoring and reporting the adoption, performance and value generated through AI-assisted Software Development Lifecycle (AI SDLC) initiatives.

Working closely with CIO teams, programme leaders, product owners and delivery stakeholders, the successful candidate will develop reporting frameworks, dashboards and actionable insights that enable data-driven decision making and demonstrate the tangible benefits of AI adoption across the organisation

Responsibilities:

AI Adoption & Benefits Tracking

• Define and maintain frameworks for measuring AI adoption and value realisation.
• Establish baseline metrics and track progress across AI-enabled delivery initiatives.
• Measure the impact of AI adoption on productivity, quality, delivery performance and cost efficiency.
• Support benefit realisation activities and ensure measurable outcomes are captured and reported.
• Identify trends, opportunities and risks relating to AI adoption.

Management Information & Reporting

• Own the design and continuous improvement of the AI SDLC Management Information framework.
• Develop executive dashboards, scorecards and reporting packs.
• Define reporting standards, KPI definitions and measurement methodologies.
• Ensure reporting is consistent, accurate and trusted across the organisation.
• Deliver meaningful insights rather than simply producing reports.

Data Analysis & Insight Generation

• Analyse data from multiple sources including:
  • Azure DevOps
  • Microsoft 365
  • Teams
  • GitHub
  • Excel
  • Power BI
  • Other approved data sources
• Identify productivity trends, adoption gaps and performance opportunities.
• Translate complex data into clear recommendations for senior stakeholders.
• Support prioritisation and decision-making through insight-led reporting.

Stakeholder Engagement

• Work closely with CIO organisations, programme teams and transformation leaders.
• Facilitate discussions around KPI performance and programme outcomes.
• Present findings and recommendations to senior stakeholders.
• Promote data-driven decision making across the AI Acceleration Centre.

Continuous Improvement

• Improve reporting quality, governance and data standards.
• Challenge data quality issues and identify reporting gaps.
• Continuously enhance metrics, reporting frameworks and dashboards.
• Ensure measures remain aligned with programme objectives and business outcomes.