A Framework for Artificial Intelligence in Business Education: Exemplars and Critical Themes for Successful Integration

Inspire Higher Ed has partnered with AACSB, the Graduate Business Curriculum Roundtable (the Roundtable), and the Graduate Management Admission Council (GMAC) to systematically document and share how business schools are integrating artificial intelligence across teaching, learning, research, and operations. This collaboration highlights institutional exemplars and effective practices while providing academic leaders and educators with a practical framework to guide their own AI journeys.

AI has rapidly evolved from a promising innovation to a defining force in business education. Since the first edition of this framework in July 2025, the pace of change has intensified. What were once exploratory efforts are now strategic initiatives, with schools making deliberate decisions about curriculum design, faculty roles, infrastructure investment, and ethical responsibility.

This January 2026 update captures a pivotal transition, from experimentation to implementation, and offers timely insight for leaders navigating transformation amid ongoing uncertainty.

The report draws on evidence from 48 business schools across the AACSB network, representing a growing global community of practice committed to peer learning and shared progress. Participating institutions span regions, missions, scales, and funding models, but a common thread emerges: AI integration is not confined to highly resourced or technically focused institutions; rather, it is relevant and achievable across the full diversity of AACSB-accredited and aspiring schools.

Key Developments

Several developments define the current phase of AI integration in business education:

• From planning to execution: Schools have moved from strategy development to broad deployment of AI across teaching, learning, and operations.
• From elective to foundational: AI literacy is increasingly viewed as a core competency for all business graduates rather than a niche specialization.
• From isolated pilots to coordinated ecosystems: Institutions are investing in governance structures, platforms, and support models that enable scale and sustainability.
• From individual initiative to leadership-driven change: Deans and senior leaders are playing visible roles in setting priorities, allocating resources, and managing institutional risk.

Together, these shifts signal that AI is no longer an optional enhancement but a strategic factor shaping educational quality, relevance, and competitiveness.

8 Themes Defining Effective AI Integration

Analysis across participating institutions reveals eight convergent themes that characterize successful and responsible AI integration:

1. Comprehensive AI ecosystems and infrastructure that support coordination, scale, and long-term viability.
2. Democratization of AI education, ensuring AI literacy across all learning pathways, not only specialized tracks.
3. Domain-specific AI applications embedded within business disciplines to enhance career relevance.
4. Faculty development as the critical success factor, requiring sustained investment, incentives, and support.
5. Responsible AI and ethics integration woven throughout curricula and institutional practice.
6. Strategic partnerships with industry, technology providers, and peer institutions to accelerate capability.
7. AI-enhanced pedagogical innovation that transforms how learning occurs, not just what is taught.
8. Leadership in times of transformation, balancing urgency with institutional mission, values, and quality standards.

Collectively, these themes form a practical, non-prescriptive framework that institutions can adapt to their unique contexts while maintaining alignment with shared expectations of quality and impact.

Relevance for AACSB and Its Members

For AACSB audiences, several implications stand out:

• Quality assurance and innovation are increasingly intertwined. AI integration is reshaping expectations related to curriculum relevance, faculty engagement, learner outcomes, and ethical responsibility.
• Peer learning accelerates progress. Institutions benefit from shared frameworks and real-world examples rather than isolated experimentation.
• People and governance matter more than technology alone. Investments in faculty capability, policies, and institutional culture outperform technology-first approaches.
• Ethical and responsible AI use is becoming a baseline expectation. AACSB’s long-standing emphasis on societal impact, ethics, and responsible leadership is encouraged in these efforts.

Rather than promoting a single model for AI adoption, this report documents emerging patterns of effective practice and provides leaders with a structured lens for reflection, decision-making, and action.

Ongoing Exploration

The impact of AI on business education will be shaped by the decisions that academic leaders make now regarding investment priorities, faculty support, curriculum design, and governance. As this report demonstrates, waiting for perfect clarity is no longer a viable strategy. Institutions that act intentionally, learn from peers, and anchor innovation in mission and values are best positioned to sustain quality and relevance in a rapidly changing environment.

As an ongoing exploration, this framework reinforces AACSB’s role in convening dialogue, sharing insight, and advancing innovation across the global business education community.

For questions or any issues accessing the report, please email Tawnya Means at [email protected].