Executive Director, AI and Data

Executive Director, AI and Data

Arizona State University is seeking a visionary executive leader to help architect the next generation of the AI-enabled university.

At ASU, we believe the future of higher education will be shaped by institutions capable of combining advanced technologies, human-centered design, and public purpose  one of the nation's leading innovation universities, ASU is advancing a bold transition from traditional "EdTech" models toward a new Tech Ed paradigm: intelligent, interoperable, AI-augmented systems designed around learners, discovery, and lifelong impact.

To help lead this transformation, ASU is recruiting an Executive Director of AI and Data — a senior Enterprise Technology leader responsible for shaping the university's AI-ready data ecosystem, enterprise integration strategy, and intelligent platform architecture.

This is not a traditional higher education IT role.

The successful candidate will help move ASU from fragmented systems and isolated data environments toward connected "data rivers" capable of powering real-time intelligence, institutional agility, and AI at scale.

Salary Range: $ - $; depending on experience

Special Instructions to Apply:
Please include a cover letter in your application speaking to your experience advancing AI and data transformation at an Enterprise scale.

Essential Duties:

• AI-enhanced student success
• Personalized and adaptive digital experiences
• Intelligent institutional operations
• Research acceleration
• Responsible AI governance
• Human-centered automation
• Cross-functional interoperability at enterprise scale

This role will define and advance the enterprise architecture required to support:

• AI-enabled institutional operations
• Intelligent workflow orchestration
• Modern enterprise integrations
• Trusted and governed data ecosystems
• Semantic and analytics infrastructure
• Agentic AI systems and services
• Scalable digital experiences for students, faculty, researchers, and staff

This leader combines enterprise architecture, data engineering, AI platform strategy, systems integration, organizational transformation, and executive leadership to:

• Engage with executive leadership, faculty innovators, operational leaders, and cross-functional teams in conversations about institutional change, human-centered design, and the future of work in higher education.
• Advance architectures and practices that enable experimentation, interoperability, responsible AI adoption, and continuous organizational learning.

This leader will help ensure ASU remains at the forefront of AI innovation while aligning technology decisions with the university's charter commitments to access, inclusion, student success, and public value.

Desired

Qualifications:

Most importantly, we are looking for a leader who understands that the future of AI is not simply about replacing human work — it is about amplifying human capability, accelerating insight, and creating more adaptive and responsive institutions. An executive-level technology leader who combines deep technical credibility with institutional imagination.

The ideal candidate brings experience leading complex AI, data, or platform modernization initiatives within large-scale environments such as:

• Research universities
• Global enterprises
• Cloud and platform organizations
• Digital-native organizations
• Large healthcare, technology, or public-sector ecosystems

This individual should be equally capable of:

• Executing on strategic vision
• Designing modern AI-ready architectures
• Leading enterprise integration strategies
• Building trusted data ecosystems
• Scaling teams, platforms, and enterprise services
• Driving organizational transformation
• Influencing executive stakeholders
• Bridging technical and non-technical audiences
• Developing high-performing technical teams
• Leading with empathy, curiosity, and a growth mindset
• Translating emerging technology into measurable institutional value
• Operating amid ambiguity and rapid technological change

Successful candidates will demonstrate expertise in many of the following areas:

• Enterprise data architecture and governance
• AI/ML platforms and AI operations
• Cloud-native infrastructure and platform engineering
• Enterprise systems integration and APIs
• S…