• Lead the design and implementation of AI-enabled automation strategies to enhance enterprise technology services and operational efficiency. • Identify opportunities to automate repetitive processes, service desk operations, and data workflows using AI and intelligent automation technologies. • Implement automation-first approaches across enterprise platforms, leveraging machine learning, predictive analytics, and intelligent agents to improve service delivery. • Establish best practices for responsible AI adoption, governance, and operational integration. • Implement AI-powered service management capabilities, including virtual agents, automated troubleshooting tools, and predictive issue detection. • Develop automation solutions that reduce service desk workload through self-service tools, chatbots, and intelligent routing of support requests. • Use AI-driven analytics to identify service trends, root causes of incidents, and opportunities for operational improvement. • Monitor performance metrics for automated service capabilities to improve response times, resolution rates, and user satisfaction. • Design and implement automated workflows and integrations between enterprise platforms using APIs, event-driven automation, and orchestration tools. • Develop automation pipelines that connect enterprise applications, cloud services, and collaboration platforms. • Implement automation-as-code practices using CI/CD pipelines, workflow orchestration tools, and automation frameworks. • Integrate AI capabilities into enterprise SaaS platforms to improve productivity, collaboration, and decision-making. • Lead development of AI-powered analytics capabilities to extract insights from operational and enterprise data. • Develop predictive models, statistical analysis tools, and machine learning workflows that support data-driven decision-making. • Design and implement data pipelines and analytics platforms that support real-time and batch processing of enterprise data. • Develop dashboards and visualization tools that allow leadership to monitor performance metrics, operational trends, and program outcomes. • Enable predictive insights that support mission-critical decisions and improve operational performance. • Establish frameworks for secure, scalable AI implementation across enterprise technology platforms. • Ensure automation solutions align with enterprise architecture, cybersecurity requirements, and data governance policies. • Implement monitoring tools to track AI system performance, model accuracy, and automation effectiveness. • Develop governance policies for the responsible use of AI and automated decision-support tools. • Work closely with engineering, cybersecurity, service operations, and data teams to integrate AI capabilities across the enterprise environment. • Communicate complex AI concepts and automation strategies to technical and non-technical stakeholders. • Provide training and guidance to teams on automation tools, AI platforms, and intelligent workflow solutions. • Support cross-functional teams in identifying automation opportunities and implementing scalable solutions.