Chief AI Development Officer

Division

Infrastructure Management & Planning (IMP)

Reports to

Senior Vice President for IMP / Chief of Staff

Strategic access

President; Cabinet and Board briefings as requested

Scope

University-wide AI strategy, policy, training, governance, development, adoption, and agent enablement

Key partners

Academic Affairs, IT, Institutional Effectiveness, Student Affairs, Enrollment, Finance, Advancement, HR, VUU Global, and other University units

• Develop, publish, and maintain a multi-year University AI Strategy and implementation roadmap aligned with VUU strategic and institutional-effectiveness priorities.
• Establish and maintain University-wide AI policies, standards, acceptable-use requirements, procurement criteria, data protections, model-risk controls, and responsible-AI practices.
• Chair or lead the University AI Governance Council and establish review, approval, escalation, and exception processes for institutional AI use.
• Advise the President, Cabinet, and Board on AI opportunities, investments, emerging risks, regulatory developments, and institutional readiness.
• Create standards for security, privacy, accessibility, bias/fairness, transparency, human oversight, records management, and lifecycle governance for AI systems and agents.

• Establish tiered AI training protocols for executives, faculty, staff, students, technical teams, and other role-based audiences, including required foundational training where appropriate.
• Develop an institutional AI literacy program covering responsible use, prompt and workflow design, data handling, verification, academic integrity, agent use, and human accountability.
• Create training standards, playbooks, templates, office hours, workshops, and communities of practice that enable divisions to adopt AI consistently and safely.
• Partner with Academic Affairs to support faculty development, curricular AI literacy, credentials, and student preparation for an AI-enabled workforce.
• Measure training completion, adoption, proficiency, risk awareness, and demonstrated business or academic impact.

• Lead and enable the design, development, testing, deployment, and continuous improvement of AI assistants, agents, automations, retrieval-augmented systems, predictive tools, and other AI solutions.
• Help business units identify high-value processes and build agents that reduce cycle time, improve service, strengthen decision-making, increase accuracy, and automate appropriate repetitive work.
• Establish a reusable enterprise agent-development framework, including approved architectures, templates, identity/access controls, data connectors, testing protocols, human-in-the-loop controls, monitoring, documentation, and retirement standards.
• Create an intake and prioritization process for AI use cases based on strategic value, feasibility, risk, cost, measurable benefit, and readiness.
• Partner with IT to integrate AI securely with approved enterprise platforms, data sources, ERP, LMS, CRM, collaboration tools, and other University systems.
• Use Lean Six Sigma / process-improvement methods to redesign workflows before or alongside automation, ensuring AI improves the underlying business process rather than simply digitizing inefficiency.

• Partner with IT and Institutional Effectiveness to strengthen AI-ready data architecture, data quality, metadata, access controls, integration, analytics, and governance.
• Establish technical standards for model selection, evaluation, testing, observability, performance, security, versioning, auditability, and lifecycle management.
• Evaluate AI vendors, platforms, enterprise licenses, and emerging technologies in coordination with Procurement, Finance, IT, Legal/Compliance, and other stakeholders.
• Maintain an institutional inventory of approved AI systems, agents, use cases, owners, data dependencies, risk classifications, and performance outcomes.

• Deliver AI-enabled solutions across administrative and academic operations, including student success, enrollment, finance, advancement, HR, facilities, communications, VUU Global, and other priority areas.
• Define and report enterprise AI performance measures, including adoption, productivity, service improvement, cost avoidance, revenue impact, student outcomes, risk, and return on investment.
• Cultivate partnerships with technology companies, HBCU consortia, government agencies, foundations, and research organizations; pursue grants and sponsored funding in coordination with appropriate University offices.
• Recruit, develop, and lead AI developers, data/automation professionals, student interns, contractors, and cross-functional project teams as the function grows.
• Represent VUU externally as a leader in responsible AI adoption, HBCU innovation, workforce readiness, and applied institutional transformation.

• Master's degree in computer science, data science, artificial intelligence, information systems, engineering, business/technology management, or a related field.
• Progressive leadership experience in AI, software, data, automation, digital transformation, or enterprise technology, including experience leading complex cross-functional initiatives.
• Demonstrated ability to take AI solutions from concept through production and to translate emerging technology into practical institutional or business outcomes.
• Working knowledge of large language models, agentic systems, retrieval-augmented generation, workflow automation, cloud AI platforms, APIs/integrations, data governance, and AI operations.
• Experience developing or implementing technology governance, policy, security/privacy controls, training, change management, and responsible-AI practices.
• Executive-level communication skills and the ability to explain technical opportunities, risks, and decisions to trustees, executives, faculty, staff, students, and external partners.