IT Business Partner

Key Accountabilities

1. Demand Management

• Collect, analyze, and prioritize service, project, and AI-driven initiatives from business and stakeholders.
• Identify opportunities for process optimization through AI, automation, and advanced analytics.
• Ensure alignment between demand, budget, IT application architecture, and AI strategy.
• Evaluate technical and economic feasibility of proposed solutions (including AI use cases), managing conflicts and critical issues.

2. Impact Evaluation

• Assess the impact of changes on applications, data, infrastructure, AI models, and end users.
• Evaluate ethical, legal, and compliance implications of AI solutions (e.g. data privacy, bias, explainability).
• Ensure compliance with GDPR regulations in collaboration with the Data Protection Officer (DPO).

3. Collaboration

• Work with IT Cloud Infrastructure and IT Architecture teams to ensure application and AI service availability, scalability, and performance.
• Collaborate with Data & AI teams to design machine learning models, copilots, and intelligent automation solutions.
• Coordinate with IT Security to ensure new applications and AI systems meet Security by Design and Responsible AI principles.
• Engage with Procurement for tender operations, including selection of AI vendors and platforms.

4. Project Management

• Manage the design, development, and implementation of IT and AI-based solutions (custom and embedded).
• Lead end-to-end AI project lifecycle (use case identification, data readiness, model development, deployment, monitoring).
• Define work plans, resources, timelines, and costs, ensuring alignment with Agile, Waterfall, or hybrid methodologies.
• Apply project governance frameworks and ensure proper risk, issue, and stakeholder management.
• Collaborate with development and project teams to define technical specifications, including integration of AI capabilities into existing platforms (e.g. ERP, CRM, Salesforce, Microsoft ecosystem).

5. Communication & Documentation

• Manage communication and collaboration among internal and external stakeholders, including AI initiatives and innovation roadmaps.
• Translate business needs into AI and data-driven solutions, ensuring clarity for both technical and non-technical audiences.
• Draft technical documentation, AI model documentation, and progress reports.
• Promote AI adoption and change management, including user training and awareness.

6. Maintenance & Support

• Conduct preventive and corrective maintenance of IT applications and AI solutions (model monitoring, retraining, performance tuning).
• Provide second and third-level support for application and AI-related issues.
• Ensure continuity of IT and AI services by managing expectations, risks, and critical issues.
• Update documentation and operating procedures related to applications and AI systems.