Principal Specialist, Finance AI & Automation Enablement

Your role at a glance

The Principal Specialist, Finance AI and Automation Enablement (m/f/d), is a hands-on Finance transformation role focused on helping NTT GDC Finance identify, shape, test, and adopt practical AI-enabled productivity, process improvement, reporting, and decision-support use cases. Positioned within Finance, the role translates real Finance pain points into clear business requirements, controlled proof-of-concepts, reusable templates, prompt libraries, adoption materials, value measures, and executive-ready recommendations.

As NTT GDC expands into new geographies and grows its data centre development pipeline, this role helps surface Finance process, reporting, data-definition, approval, and control implications early so they are clearly framed for Finance leaders, process owners, and technology partners. This role is Finance-led and business-outcome focused; it does not own enterprise technology strategy, architecture, production deployment, or platform governance.

• Identify and prioritize AI and automation opportunities by grounding use cases in real workflow friction, manual effort, recurring reporting needs, and data-quality pain points.
• Scope Finance use cases, create low-risk prototypes, mockups, examples, or proof-of-value materials using approved enterprise tools, and coordinate with technology owners before any broader deployment or production use.
• Develop business-owned templates, analytical models, trackers, prompt libraries, reporting concepts, and workflow improvement ideas that improve Finance speed, consistency, and transparency.
• Apply practical product-style ways of working to Finance use cases, including user stories, backlog prioritization, iterative testing, user feedback, adoption planning, and value measurement.
• Document business purpose, Finance requirements, data sources, assumptions, limitations, control considerations, adoption needs, and handoff requirements for sustainment or scaling.

• Represent Finance business needs by translating process pain points, reporting gaps, control considerations, and user requirements into clear Finance-side inputs for technology, data, reporting, and automation partners.
• Assess current-state Finance pain points, process dependencies, data flows, reporting gaps, and manual workarounds to inform Finance Transformation priorities and technology-enabled improvement opportunities.
• Support Finance stakeholders in articulating requirements for ERP, reporting, automation, AI, and data-definition initiatives, ensuring Finance process, reporting, and control needs are represented.
• Promote stronger Finance data discipline by helping teams define trusted sources, standard definitions, reporting logic, quality checks, and ownership expectations across Finance processes.
• Partner with technology, data, ISO, and change teams where appropriate to ensure Finance use cases are reviewed, governed, tested, adopted, and sustained through the right channels.

• Support strategic Finance initiatives that connect organization, process, systems, data, and business-growth priorities into executable plans.
• Translate ambiguous business needs into problem statements, solution options, value cases, and decision-ready recommendations.
• Develop executive-ready narratives for Finance Transformation–what changed, why it matters, what value is being created, and what decisions are required.
• Create high-quality materials for CFO, Finance leadership, and Steer Co audiences, including transformation updates, business cases, roadmaps, and value-realization reporting.
• Maintain a prioritized backlog of AI, automation, and strategic-initiative opportunities, and run disciplined governance routines (cadence, RAID and decision logs, dependency and benefit tracking, escalation).

• Build practical AI and automation capability across Finance through peer learning, office hours, use-case showcases, templates, and hands-on experimentation sessions.
• Coach Finance users on responsible AI and automation use–data sensitivity, review discipline, tool limitations, control requirements, and appropriate human judgment.
• Partner with Change Management and Communications so new tools and process changes are clearly explained, adopted, and sustained.
• Define and track success metrics–adoption, cycle time, manual-effort reduction, decision speed, data quality, and business value.
• Identify risks to value capture (low adoption, unclear ownership, weak data quality, limited IT support) and drive mitigation with initiative owners.

• Bachelor’s degree in Finance, Accounting, Business, Information Systems, Analytics, Engineering, Economics, or related discipline (or equivalent experience).
• Multiple years of progressive experience across finance transformation, finance systems, strategic…