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About the role
As an experienced AI professional, your role will involve guiding the organization in identifying, designing, and implementing practical Artificial Intelligence applications across research, institutional systems, knowledge management, and business processes. You will need to combine technology leadership, process redesign capability, innovation thinking, and strategic institutional advisory skills to determine the adoption, application, and measurable impact of AI. Key Responsibilities: - Assess current systems, workflows, and functional areas to identify AI integration opportunities. - Develop an institutional AI adoption roadmap aligned with research, policy, sustainability, and operational priorities. - Recommend short-term, medium-term, and long-term AI interventions across divisions. - Redesign internal workflows using AI-enabled automation for efficiency, speed, and decision-making. - Identify processes suitable for AI deployment across HR, finance, project management, procurement, administration, and reporting. - Build frameworks for AI-assisted decision support in institutional functions. - Advise researchers on AI applications in research design, data analysis, predictive modeling, literature synthesis, and report generation. - Explore AI applications in climate data, remote sensing, sustainability analytics, environmental modeling, and policy intelligence. - Support development of AI-enabled knowledge repositories and smart information retrieval systems. - Recommend AI integration with existing enterprise systems such as ERP, document management systems, learning systems, project monitoring platforms, and data repositories. - Guide development or adoption of AI-powered dashboards, institutional copilots, and intelligent workflow systems. - Conduct internal workshops and leadership sessions on practical AI use cases for teams. - Build institutional understanding of responsible AI use, limitations, governance, and ethical adoption. - Track emerging AI tools, platforms, and sectoral innovations relevant to sustainability, energy, environment, and development sectors. - Advise leadership on strategic technology partnerships and AI opportunities. Desired Profile: - Strong experience in technology leadership, digital transformation, or AI-driven institutional change. - Proven ability to align technology solutions with organizational goals. - Experience in process redesign and enterprise technology deployment. - Understanding of AI tools including generative AI, workflow automation, analytics platforms, and decision-support systems. - Ability to translate AI concepts into practical institutional solutions. - Strong stakeholder engagement and leadership communication skills. Preferred Qualification: - Masters degree in Technology, Computer Science, AI, Data Science, Management, or Digital Transformation. - Additional exposure to enterprise systems, automation frameworks, or innovation consulting preferred. Preferred Experience: - 15+ years of leadership experience in technology transformation, digital systems, AI advisory, or enterprise innovation. - Experience working across institutional systems such as ERP, DMS, LMS, workflow automation, or large-scale digital transformation projects. - Exposure to research, education, consulting, sustainability, or knowledge institutions preferred. As an experienced AI professional, your role will involve guiding the organization in identifying, designing, and implementing practical Artificial Intelligence applications across research, institutional systems, knowledge management, and business processes. You will need to combine technology leadership, process redesign capability, innovation thinking, and strategic institutional advisory skills to determine the adoption, application, and measurable impact of AI. Key Responsibilities: - Assess current systems, workflows, and functional areas to identify AI integration opportunities. - Develop an institutional AI adoption roadmap aligned with research, policy, sustainability, and operational priorities. - Recommend short-term, medium-term, and long-term AI interventions across divisions. - Redesign internal workflows using AI-enabled automation for efficiency, speed, and decision-making. - Identify processes suitable for AI deployment across HR, finance, project management, procurement, administration, and reporting. - Build frameworks for AI-assisted decision support in institutional functions. - Advise researchers on AI applications in research design, data analysis, predictive modeling, literature synthesis, and report generation. - Explore AI applications in climate data, remote sensing, sustainability analytics, environmental modeling, and policy intelligence. - Support development of AI-enabled knowledge repositories and smart information retrieval systems. - Recommend AI integration with existing enterprise systems such as ERP, document management systems, learning systems, project monitoring platforms,
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