Artificial Intelligence, DAI (Online in Chinese)

The Doctor of Artificial Intelligence (DAI) is an applied, STEM-designated doctorate designed for forward-thinking leaders who drive enterprise-level transformation. Tailored specifically for working professionals, this program bridges the gap be-tween frontier AI research and high-stakes business strategy across global industries.

Through a rigorous, multi-disciplinary curriculum, executives cultivate advanced expertise in strategic AI decision-making, governance, ethical implementation, and operational scaling. Whether optimizing enterprise performance or fostering disruptive entrepreneurship, graduates emerge equipped to leverage AI for sustainable competitive advantage.

The DAI is designed for mid-to-senior executives – including CEOs, CTOs, CDOs, CIOs, and Chief AI Officers (CAIOs) – as well as ambitious business and IT leaders tasked with spearheading complex AI-driven growth.

A landmark doctoral program of Golden Gate University – an AI-native institution in which AI is foundational to teaching, learning, research, and assessment – the DAI prepares graduates with a doctoral-level professional portfolio and enduring competencies in problem framing, solution design, evaluation, and governance, positioning them to meet the growing global demand for AI expertise in business, government, nonprofits, and entrepreneurship.

Upon successful completion of the Doctor of Artificial Intelligence program, graduates will be able to:

1. Solve problems: Evaluate and synthesize advanced artificial intelligence frameworks, algorithms, and emerging technologies to solve complex, domain-specific challenges across global industries.
2. Implement strategy: Formulate and execute enterprise-wide AI strategies that align technical capabilities with core business operations to drive measurable value, operational efficiency, and market leadership.
3. Institutionalize governance: Design and implement robust governance, security, and ethical frameworks to ensure responsible AI deployment within dynamic regulatory and international environments.
4. Think outside the box: Capitalize on disruptive AI technologies to foster innovation, scale new business models, optimize customer experiences, and build sustainable competitive advantage.
5. Lead complex change and advance AI research: Lead cross-functional teams and orchestrate organizational change while conducting rigorous, interdisciplinary research that bridges AI research, strategic decision-making, and high-impact enterprise execution, generating original knowledge and evidence-based insights to advance AI practice.