مدير التحول في مجال الذكاء الاصطناعي

Role Purpose:

Defineand accelerate the organization’s AI transformation agenda by leveraging artificial intelligence, generative AI, intelligent automation, and advanced analytics to improve business performance, operational efficiency, customer experience, and decision-making. Establish a scalable, responsible, and sustainable AI operating model aligned with corporate strategy, business priorities, governance requirements, and long-term value creation.

Key Accountabilities:

AI Strategy and Transformation Roadmap

• Define and maintain the organization's AI transformation strategy, aligned with corporate objectives and business priorities.
• Assess organizational AI maturity, identify transformation opportunities, and evaluate readiness across business functions.
• Develop a prioritized AI roadmap covering short-, medium-, and long-term initiatives.
• Identify opportunities for generative AI, intelligent automation, predictive analytics, and AI-enabled process redesign.
• Develop business cases, investment proposals, and value realization plans for priority AI initiatives.
• Advise executive leadership on AI opportunities, risks, emerging technologies, and strategic implications.

Business Transformation and Value Realization

• Partner with business leaders to identify high-impact use cases across operations, finance, customer service, commercial functions, HR, and other relevant areas.
• Translate business challenges into clearly defined AI-enabled transformation initiatives.
• Challenge existing processes and operating models to identify opportunities for redesign, simplification, and automation.
• Establish measurable outcomes for AI initiatives, including productivity improvements, cost optimization, revenue growth, service quality, and customer experience.
• Monitor benefits realization and ensure initiatives deliver sustainable business value beyond proof-of-concept activities.
• Promote the integration of AI into core business processes rather than treating AI as a standalone technology initiative.

AI Portfolio and Program Leadership

• Establish and manage a portfolio of AI transformation initiatives, including prioritization, dependencies, milestones, budgets, and delivery risks.
• Lead initiatives from opportunity identification and business case development through experimentation, deployment, adoption, and benefits measurement.
• Coordinate business stakeholders, IT, data teams, cybersecurity, legal, compliance, procurement, and external partners.
• Establish clear ownership, accountability, governance, and decision-making mechanisms for each initiative.
• Track portfolio performance and communicate progress, challenges, and decisions required to executive leadership.
• Ensure successful pilot initiatives have a credible path to production deployment, adoption, and scale.

AI Governance, Risk, and Responsible Adoption

• Collaborate with relevant functions to establish appropriate AI governance, policies, standards, and approval processes.
• Ensure AI initiatives address data privacy, information security, regulatory compliance, intellectual property, model risk, and ethical considerations.
• Define appropriate controls for human oversight, transparency, accountability, and the use of AI-generated outputs.
• Work with data and technology teams to assess data readiness, technical feasibility, architecture, and integration requirements.
• Promote responsible AI adoption consistent with applicable regulations and organizational risk appetite.

Organizational Adoption and Capability Development

• Build awareness and understanding of AI opportunities and limitations among executives, managers, and employees.
• Develop change management and adoption approaches for AI-enabled processes and new ways of working.
• Identify capability gaps and recommend targeted AI training, upskilling, and knowledge-sharing initiatives.
• Establish mechanisms for capturing lessons learned, sharing reusable solutions, and scaling successful practices.
• Foster a business-led, outcome-oriented culture of AI experimentation and continuous improvement.

Operating Model and Future Capability Development

• Define the proposed AI transformation operating model, including business ownership, technology delivery, governance, and decision rights.
• Establish a network of business stakeholders and initiative owners to support delivery without requiring an immediate dedicated team.
• Identify the capabilities, roles, resources, and partnerships required to scale the AI transformation agenda.
• Develop a phased plan for establishing a dedicated AI transformation function when justified by portfolio size, delivery demand, and business value.
• Recommend the appropriate balance between internal capabilities, technology vendors, consulting partners, and managed services.