Purpose and Methodology

In October 2024, AACSB conducted two surveys—one for faculty and one for deans—to explore GenAI adoption and proficiency among business school educators and leaders. The surveys addressed key topics such as governance policies, training initiatives, and practical examples of GenAI in teaching and research. The objective was to gain deeper insights into how business schools were navigating the GenAI landscape, identifying priorities, and uncovering challenges that required further support.

Survey Participation

As shown below, participation across the two surveys reflects regional variability. Additionally, faculty and dean respondents represent separate groups of schools, and the findings should be interpreted as insights from two distinct populations.

This report draws on insights from 236 business school deans representing AACSB member institutions in 56 countries and 429 business school faculty from 321 member institutions in 61 countries.

Survey Highlights

• Perceptions Among Deans and Faculty
  Deans exhibit greater optimism about GenAI adoption and acceptance within their institutions, while faculty often express more caution or skepticism. Both groups generally agree on the importance of preparing for and integrating GenAI across curriculum, research, and teaching. However, the differing levels of enthusiasm, particularly among faculty, present challenges for achieving cohesive strategic progress at the institutional level.

• Proficiency and Usage Trends
  Both deans and faculty predominantly identify as novice or intermediate users of GenAI. Faculty tend to use GenAI more frequently in teaching than in research, with tasks like content creation and summarization among the most common applications. In contrast, technical uses, such as data analysis, are less prevalent, often due to concerns over security and reliability. Responses on usage frequency indicate that GenAI is still largely a supplementary tool rather than a core component of most faculty workflows. Notably, faculty with higher self-reported proficiency are more likely to integrate GenAI into their work more regularly, highlighting the importance of building confidence and skills in its use.

• Ethical Concerns and Governance Policies
  Concerns about plagiarism, data privacy, and academic integrity are significant barriers to increased GenAI adoption. While 47 percent of deans report that their schools have implemented AI/GenAI policies, many lack clear or actionable guidance. Schools will need to develop consistent and practical policies, alongside training on ethical concerns, to foster responsible GenAI use.

• Potential and Challenges in Education
  Faculty and deans view GenAI’s impact on creativity, critical thinking, and problem-solving as both a promising opportunity and a notable risk. These perspectives highlight the importance of balancing GenAI’s integration with traditional pedagogical methods. Schools may need to rethink the learning process to fully harness AI’s potential while also addressing the technology’s limitations.

• Resource Allocation Strategies
  Schools are prioritizing curriculum integration as a dominant strategy, embedding AI/GenAI into teaching as a key focus. Limited efforts in hiring, staffing, and departmental restructuring suggest that most institutions are leveraging existing resources rather than significantly expanding their infrastructure.

• Training and Development Opportunities
  Survey results highlight a preference for combining self-directed learning, like online tutorials and hands-on practice, with structured institutional support. While workshops and seminars are widely valued for foundational knowledge, low participation in formal programs, such as university courses or certifications, suggests untapped potential for more robust, credentialed learning pathways in GenAI.

Dean and Faculty Perceptions of GenAI Adoption

Both the faculty and dean surveys aimed to capture perceptions of how their business schools’ stakeholders—administrators, faculty, and students—have embraced GenAI. The surveys also explored the extent to which business schools encourage GenAI usage by faculty and students. While the samples of deans and faculty are not directly comparable, an overarching trend emerges in the results: deans are significantly more optimistic about the adoption and acceptance of GenAI by their faculty, staff, and students. Faculty responses reflect a more cautious or skeptical perspective.

Deans’ responses to statements about their business schools’ support for AI reveal stronger perceived institutional backing compared to faculty outlooks. However, for the specific statement regarding whether their school encourages students to use AI/GenAI for assignments or learning activities, deans are more divided, with only 49 percent in agreement. Faculty also are more likely to disagree with this statement. As highlighted in several open-ended responses, decisions about students’ use of GenAI are often left to individual faculty members, reflecting variability in institutional policies and practices.

The largest gap between deans and faculty is in their perception of the use of AI/GenAI in operational or administrative processes, with significantly more deans than faculty who believe their schools encourage this use. While the majority of faculty agree that their business school encourages the use of AI tools in teaching, learning delivery, curriculum design, and as a topic in the curriculum, the data suggest that deans’ enthusiasm for such practices has not yet been fully embraced by faculty to the same extent.

While both deans and faculty generally believe that senior administrators and students at their institutions, as well as they themselves, embrace GenAI, deans continue to be more optimistic.

A closer comparison of responses to the statement, “Most faculty at my business school fully embrace the idea of using GenAI in their work,” reveals notable variability in agreement levels, with faculty showing greater skepticism compared to deans.

The Risk and Promise of GenAI: Mixed Views

The open-ended responses from deans and faculty reveal a complex mix of emotions about GenAI. While the majority of educators and leaders acknowledge that GenAI is here to stay—viewing it as a critical skill for preparing students to be workforce-ready and as a tool capable of driving efficiencies and even transforming higher education—there is also a sense of cautious optimism, even among its proponents, and clear apprehension from others. One faculty member captures this sentiment succinctly: “It is highly flawed right now, and people seem to rarely discuss or present its weaknesses. There seem to be two extremes—AI is awful, I won’t use it, and AI is amazing, I’ll use it for everything. I want to take a balanced approach, but there is very little out there to support a balanced approach. I’m having to build it myself, which is extremely time-consuming.”

3 Key Takeaways

Deans and Faculty Share

Deans’ Goals for GenAI Integration

The deans surveyed are optimistic about GenAI’s transformative potential, identifying key goals that align with enhancing the quality and outcomes of business education. Their responses reflect a strong focus on using GenAI to improve educational impact and prepare students for the evolving workforce rather than prioritizing competitive positioning or revenue generation.

When asked to rank nine institutional goals related to GenAI, deans consistently selected preparing students for the future workforce, exploring innovative teaching methods, and enhancing the value of higher education as top priorities. Lower-ranked goals, such as pursuing alternative revenue streams, attracting new faculty, and differentiating their institutions from competitors, indicate that deans are currently focused on student-centered outcomes rather than institutional gains. This approach emphasizes the use of GenAI to enrich the learning experience and better equip students for future challenges.

Deans' Self-Assessment of Proficiency

Exactly half of the surveyed deans describe themselves as having intermediate proficiency in GenAI, while 13 percent (32 out of 235 respondents) describe themselves as having advanced or expert proficiency. Notably, the survey did not probe the specific characteristics or criteria deans used to self-assess their proficiency, which may be an interesting question for future research. Instead, it aimed to better understand respondents’ confidence in using the technology.

Analysis of the more GenAI-proficient dean responses shows some regional differences:

• In Europe, the Middle East, and Africa (EMEA), 26 percent of deans report higher proficiency levels in GenAI, with 22 percent indicating advanced proficiency and 4 percent (3 respondents) expert proficiency.
• In Asia Pacific, 10 percent of deans report advanced proficiency, with no respondents indicating expert levels.
• In the Americas, only 7 percent report advanced proficiency, and similarly to Asia Pacific, no deans report expert-level proficiency.

The majority of dean GenAI users (42 percent) report using GenAI occasionally or a few times a month, followed by 31 percent who use it frequently or a few times a week. Only 6 percent (14 out of 232 responding deans) report using GenAI very frequently (daily).

Usage patterns among occasional users are consistent across all regions. However, the greatest regional variation is observed among infrequent and frequent users: deans in EMEA and Asia Pacific are more likely to use GenAI frequently, while their counterparts in the Americas are more likely to report rare use of the technology.

Faculty Proficiency With GenAI in Teaching and Research

With faculty, we explored in more detail their GenAI proficiency and its use in teaching and research activities, with most respondents identifying themselves as novice or intermediate users in these areas. Specifically, 32 percent classify themselves as novices in teaching compared to 38 percent in research, while 38 percent identify as intermediate in teaching and 33 percent in research. These patterns are relatively consistent across regions, highlighting a global trend in faculty proficiency levels.

Notably, only 7 percent of respondents (21 faculty members) consider themselves experts in the use of GenAI for teaching. Of these experts, 71 percent have been in a faculty role for 15 years or less, suggesting that newer faculty members may be more inclined to exhibit greater proficiency with this technology.

In research, only 18 faculty members self-identify as experts, but this group displays a broader distribution across faculty experience levels. This finding suggests that expertise in applying GenAI to research may be tied less to years in academia and more to specific research needs or personal initiative to adopt the technology.

When it comes to frequency of GenAI use, 39 percent of faculty report that they use it occasionally (a few times a month) in their teaching, followed by 28 percent who use it rarely (a few times a year). This suggests that while GenAI is being explored, it has yet to become a daily tool for most teaching activities.

GenAI is used even less frequently in research. Thirty-seven percent of faculty say they rarely use it for research activities, while 29 percent use it occasionally. Only a small proportion of faculty use GenAI frequently or very frequently, with 25 percent leveraging it in teaching and 21 percent in research.

These figures suggest that GenAI has not yet achieved widespread adoption in business classrooms and research settings. However, usage patterns reveal a clear link between proficiency and frequency of use: faculty who self-report higher proficiency with GenAI are significantly more likely to use it more frequently. This correlation highlights the importance of building confidence and familiarity with the technology in order to integrate it more effectively into teaching and research practices.

How Faculty Are Using GenAI in Teaching

While faculty are beginning to adopt GenAI in their teaching activities, its usage is largely experimental or supplementary. They are more likely to use it for occasional tasks like curriculum integration and content generation, while daily use and application for student assessments or feedback remain limited. This indicates a potential for growth as faculty become more proficient and confident in leveraging GenAI.

How Faculty Are Using GenAI in Research

Compared to teaching, faculty are more reluctant to incorporate GenAI into their research activities, with patterns of adoption varying widely by activity. The data underscore GenAI’s emerging role as a support resource for faculty in areas such as writing and summarization. Technical applications like data collection, analysis, and research design remain less explored, stemming from a lack of expertise, concerns about accuracy, or a belief by some faculty that GenAI is not appropriate for these practices.

GenAI As a Research Topic

Only 35 percent of faculty respondents address AI/GenAI as a topic in their recent or upcoming research—a consistent proportion across regions. Among those exploring AI, research topics include ethical and privacy considerations; biases in AI-generated outputs; trust in AI systems; workplace integration; and applications in HR, supply chain management, and marketing.

Faculty are also investigating AI’s influence on productivity and decision-making in areas such as portfolio management and financial calculations. As AI continues to impact work, education, and play, faculty research is likely to increasingly advance knowledge on the impact of AI across diverse academic, practical, and disciplinary domains.

Most-Used AI Platforms for Teaching and Research

As anticipated, OpenAI’s ChatGPT stands out as the most widely used AI platform among faculty for both teaching and research, with an impressive 96 percent and 95 percent of respondents, respectively, using it to some degree. This high adoption rate is consistent across regions, emphasizing its universal appeal, accessibility, and versatility.

In contrast, the usage of the seven other mainstream AI platforms included in the survey falls significantly short of ChatGPT, particularly for research activities. This stark gap underscores ChatGPT’s dominance in the educational AI space.

Among ChatGPT users, the frequency of use is relatively balanced, with faculty reporting occasional, frequent, and very frequent usage in near-equal proportions. This even distribution suggests that ChatGPT has become a reliable tool for a variety of teaching and research practices, catering to both light and intensive users.

The high use of ChatGPT may stem from faculty gravitating toward the most accessible and familiar option, as several respondents shared that they are overwhelmed by the abundance of platforms becoming available. However, this heavy reliance on ChatGPT also presents a clear opportunity for other AI platforms—especially those tailored specifically for higher education—to carve out a niche.

Additional platforms are listed below, and with the highly publicized introduction of DeepSeek, even more are likely to enter the market. By addressing specialized teaching needs and academic research challenges, alternative platforms could play a complementary role and broaden the AI ecosystem within education.

By addressing specialized teaching needs and academic research challenges, alternative platforms could play a complementary role and broaden the AI ecosystem within education.

Other AI Platforms Used by Faculty

In-Class Policies for GenAI

Faculty approaches to encouraging or discouraging the use of GenAI in their classrooms vary widely, with many schools leaving these decisions to individual faculty members. While some faculty have implemented their own structured guidelines, others are adopting a wait-and-see approach as they navigate GenAI’s continuous evolution.

Globally, 29 percent of faculty have implemented their own formal written policies for student use of GenAI in their courses. Meanwhile, 22 percent rely on informal guidelines, with many of those faculty noting a preference for flexibility as they monitor and adapt to the technology’s evolution. Interestingly, nearly a quarter of faculty acknowledge the need for a policy and have plans to create one. However, 18 percent report having no policy and no intention of drafting one, suggesting that some faculty may feel either unconcerned or unprepared to address the issue at this stage.

Regionally, notable differences emerge, particularly in the adoption of formal written policies. Faculty in the Americas are more likely to have individual policies in place compared to their counterparts in Asia Pacific and EMEA, where most faculty appear to be in the planning stages. A possible explanation for this discrepancy lies in institutional policy structures.

As explored later, a greater proportion of deans in Asia Pacific and EMEA report that their institutions already have AI/GenAI policies in place, potentially reducing the perceived need for individual faculty policies. In contrast, faculty in the Americas, where institutional policies are less prevalent, may feel a stronger imperative to implement their own guidelines to address the use of GenAI in their courses. This dynamic highlights the interplay between institutional and individual governance in managing AI use in education.

Individual Policy Characteristics

Faculty with their own classroom policies for AI/GenAI highlight significant variability in how they permit or restrict its use, as well as in the formalization of their guidelines. Most policies prioritize academic integrity, addressing concerns about plagiarism and responsible AI use in coursework. While some explicitly forbid AI, others support or encourage its use when appropriately documented, such as requiring students to disclose prompts and outputs.

Policies often distinguish between using AI as a learning tool and its prohibited use in assessments. Additionally, some faculty provide specific use cases or expectations, framing AI as a supplementary resource for brainstorming and refining ideas rather than a replacement for critical thinking. These varied approaches illustrate an evolving effort to balance innovation with ethical and academic standards in classroom settings.

I tell students I would be doing them a disservice if I restricted their use of GenAI since I imagine it will be a powerful way for them to compete in the marketplace. Simultaneously, I encourage them to consider the ethical implications should they overuse the tools during their own education—both for themselves and for society in general.

Encouraging Students to Use GenAI

Faculty worldwide are increasingly encouraging students to use GenAI across various activities, with strong support for tasks that boost creativity and streamline processes.

However, the degree of encouragement varies by activity, with some areas showing significant opportunities for growth.

• Brainstorming Ideas: Globally, 78 percent of faculty encourage students to use GenAI for brainstorming, making it the most widely supported activity. This response reflects a universal recognition of AI’s ability to foster creativity and generate diverse ideas.
• Drafting and Editing Written Assignments: Encouragement for GenAI in writing tasks is relatively high, with 49 percent of faculty globally supporting its use. However, there is a notable gap between the Americas, where 58 percent of faculty encourage it, and EMEA, where 32 percent endorse it, signaling differing levels of adoption for AI-driven writing assistance.
• Conducting Research: Globally, 41 percent of faculty encourage the use of GenAI for research purposes, demonstrating its growing role in helping students gather and synthesize information.
• Creating Visualizations and Multimedia Content: Faculty in EMEA and Asia Pacific are notably more supportive of this activity compared to their peers in the Americas, reflecting a regional difference in integrating AI into creative tasks.
• Translating Spoken Languages: Language translation represents one of the most significant regional differences in GenAI use. Worldwide, 30 percent of faculty support it, but in EMEA, this figure jumps to 56 percent, compared to just 19 percent in the Americas. One reason for this disparity could be the greater linguistic diversity of classrooms in EMEA, where translation tools may be more necessary.
• Performing Technical Tasks: Technical activities, such as data analysis and coding, received lower encouragement levels across all regions. This result may reflect the specialized nature of these tasks, which are often taught in dedicated courses that prioritize students’ conceptual understanding and skill development over their ability to leverage AI to find efficiencies.

Faculty Perceptions of GenAI's Impact on Teaching and Research

Impacts on Teaching

Faculty views on how GenAI is impacting education reveal a mix of optimism and uncertainty. While the technology is seen as transformative in some areas, it is still met with caution in others.

Impacts on Research

Policy Governance

Among the 236 institutions represented by responding deans, 47 percent report that their school follows an AI/GenAI policy, while a nearly identical 45 percent indicate that their school does not. Notably, 8 percent of deans are unsure whether their school has a policy, suggesting potential gaps in communication, awareness, or prioritization of AI/GenAI governance.

Interestingly, although the faculty and dean surveys do not align in institutional representation, 29 percent of faculty also report uncertainty about whether their school follows an AI/GenAI policy. This discrepancy underscores the need for clearer communication and broader awareness of AI-related strategies among key stakeholders, especially faculty.

Differences in policy adoption emerge when considering schools’ regional locations and sizes.

Regional Variations

• Schools in EMEA are the most likely to follow an AI/GenAI policy, with 62 percent of deans reporting the presence of a policy.
• In contrast, only 36 percent of schools in the Americas follow a policy, reflecting a notable regional disparity.
• Slightly over half of deans in the Asia Pacific region report that their school follows an AI/GenAI policy. However, this region also accounts for the majority of deans who are unsure about their school’s policy, with 15 percent expressing uncertainty.

Insights by School Size

• Large Schools (75+ Full-Time Faculty): A majority (54 percent) of deans from large schools follow an AI/GenAI policy, indicating a stronger adoption rate among larger institutions.
• Small and Medium Schools: Among schools with fewer than 75 full-time faculty, approximately 40 percent follow an AI/GenAI policy, suggesting that smaller institutions may face unique challenges in policy implementation.

Among schools that do not currently follow an AI/GenAI policy, the majority (36 percent) are exploring the possibility of developing one, while 25 percent are actively working on policy development. Fourteen percent of deans have no plans to develop a policy or remain unsure about future steps.

AI/GenAI Policy Characteristics

What’s Included in the Policy?

The ethical use of AI tools remains a top priority for educators, as reflected in the AI/GenAI policies adopted by business schools. Nearly all schools (95 percent) with a policy include guidelines for the ethical use of AI by students, followed closely by ethical use by faculty and staff (82 percent). Data privacy and protection emerge as the third most common focus area included in these policies.

While training for faculty and students is included in 29 and 24 percent of all policies, respectively, the importance of ethics and responsible AI use highlights an opportunity for institutions to place greater emphasis on training requirements and expectations. This would ensure that both students and faculty are equipped to use the technology responsibly and effectively.

Regional Differences in Training Focus

• Asia Pacific schools with policies in place are leading in this area, with 42 percent including faculty training expectations in their policies and 32 percent including student training expectations.
• By contrast, only about a quarter of policies in the Americas and EMEA convey expectations for faculty training and 22 to 23 percent address training for students.

Faculty Perceptions of AI/GenAI Policies

While acknowledging the differences in school representation between the faculty and dean surveys, faculty perceptions of their schools’ AI/GenAI policies reveal important insights. Among the 143 faculty who indicate that their school follows an AI/GenAI policy, 42 percent rate their school’s policy as either very useful (40 percent) or extremely useful (2 percent), highlighting that these policies are generally regarded as valuable tools for supporting faculty work.

At the same time, nearly a quarter of these faculty rate their school’s policy as neither useful nor not useful, suggesting that for some faculty, these policies lack direct impact or relevance to their work. Additionally, 6 percent of faculty found their school’s policy not at all useful, with dissatisfaction highest in the Americas (10 percent), compared to just 3 percent in Asia Pacific and 2 percent in EMEA.

The significant portion of faculty rating policies as only slightly useful or neutral highlights an opportunity for schools to refine and better align these policies with faculty needs, ensuring they are both actionable and directly supportive of teaching and research activities.

Faculty Share: AI Policy Opinions

Strategic Planning and Resource Allocation

Business school deans are implementing or planning diverse strategies to support AI/GenAI-related needs, with notable trends emerging across regions. While business schools are making strides in integrating AI/GenAI, significant opportunities remain to scale efforts in staffing, program development, and cross-industry collaboration.

Training and Support

Training Requirements

Most business schools responding to the surveys do not mandate AI/GenAI training for students, faculty, or administrators. Only 13 percent of schools require training for students, 12 percent for faculty, and 9 percent for administrators. Among the three regions, participating schools in Asia Pacific are the most likely to enforce training, with just over 20 percent requiring it for all three groups. Schools in EMEA follow closely, with 18 percent mandating training for students and faculty, and 11 percent for administrators.

Training Trends and Preferences Among Deans and Faculty

Regardless of school requirements, faculty and deans are turning to a mix of training approaches to build their own understanding of GenAI, with clear preferences emerging for flexible, self-directed options as well as institutional support.

• Self-Taught Learning: Tutorials, hands-on practice, and videos are the go-to methods for the majority of faculty (69 percent) and deans (61 percent), reflecting a strong preference for independent, on-demand learning.
• Workshops and Seminars: Workshops at business schools or universities are highly valued, engaging 43 percent of faculty and 52 percent of deans. External workshops also play a role, with roughly 40 percent of both groups participating, emphasizing the importance of guided, collaborative learning experiences.
• Institutional Training: Training provided by universities or business schools supports nearly half of both groups (52 percent of deans, 42 percent of faculty), showing reliance on institutional resources to bolster GenAI proficiency.

• Online Courses and Peer Learning: Platforms like Coursera and LinkedIn Learning are used by 35 percent of faculty and 29 percent of deans. Peer learning within institutions is more common (25 percent of faculty, 30 percent of deans) than training from outside of schools, where participation drops to around 20 percent.

• University Courses and Certifications: Only 7 to 10 percent of faculty and deans have pursued formal university courses or certification programs, signaling untapped potential for more robust, credentialed learning pathways.
• No Training at All: Notably, 13 percent of faculty and 9 percent of deans report a lack of engagement in any GenAI training, pointing to gaps in outreach or accessibility that institutions could address.

These insights highlight a clear preference for flexible, self-directed learning, paired with institutional support through workshops and training programs. However, the low engagement in formalized courses and certifications suggests an opportunity for institutions to develop more structured, impactful learning opportunities for both faculty and deans.

Training and Development Initiatives

Deans provide insights into their schools’ training and development efforts for faculty and students, reflecting a mix of accessibility, practicality, and strategic alignment. A key theme that emerges is the wide variability in the maturity of these efforts. Some schools have established structured programs with dedicated staff, funding, and resources, or they’ve enforced mandatory AI-focused courses. Others remain in the early stages, either uncertain about the next steps or relying on faculty to pursue self-directed training or independently integrate AI into their curricular portfolios.

Desired Training and Development Among Faculty

Faculty provide insight into additional training and development opportunities they wish their business schools would offer, focusing on three key areas:

• Demand for Practicality: Faculty want training that balances theory with hands-on application to make GenAI useful in day-to-day tasks, such as classroom integration.
• Focus on Ethics: Ethical use and governance are recurring concerns, indicating the need for robust institutional policies and training.
• Customizable Opportunities: Requests range from beginner-level courses to advanced applications, reflecting the diverse expertise levels among faculty.

As with any rapidly evolving technology, AI presents both significant challenges and transformative opportunities for educators and higher education broadly. Addressing these challenges strategically—through clear institutional policies, targeted training programs, and resource allocation—can help bridge gaps and unlock AI’s full potential.

Faculty Challenges

Faculty were asked to rank a series of challenges related to using or attempting to use GenAI in their teaching and research activities. Non-users of GenAI were also asked to evaluate the same challenges, reflecting how much these issues discouraged their use of the technology. Both groups highlighted a mix of systemic and individual obstacles, with time constraints, ethical concerns, and a lack of leadership emerging as the top barriers. Competency gaps and limited resources further hinder adoption. Notably, some non-users indicated that their decision to avoid GenAI was due to personal preference or disagreement with its use, rather than any particular challenges they faced in using it.

Dean Challenges

Deans also reveal the biggest challenges they believe their business schools face in integrating GenAI, with time constraints emerging as the most significant barrier globally. Balancing the demands of GenAI adoption with existing priorities highlights the complexity of introducing new technologies.

Other key challenges include a lack of faculty competency and ethical concerns, reflecting the need for professional development and strategies to ensure the responsible use of GenAI at their schools. Systemic issues, such as limited access to support resources and tools and a lack of clear leadership guidance, further hinder adoption.

Addressing these challenges will require institutions to invest in training, provide clear strategic direction, and enhance access to resources. These actions will enable schools to effectively integrate GenAI into their operations and unlock its transformative potential.

Supporting Business Schools in Their Journeys

The business education landscape in this GenAI moment is complex and ever-evolving, marked by similarities across schools and unique challenges specific to each institution. Variations often arise from factors such as faculty expertise, leadership support, training availability, governance structures, and the institutional culture around supporting new technologies. Despite these differences, the resources educators need to remain competitive and ensure their schools prepare future leaders to thrive in an AI-enabled world are universally essential.

Key Opportunities for Supporting GenAI Adoption in Business Schools

Effectively integrating GenAI into business education requires strategic support for both institutions and educators. Deans and faculty identified the following areas as priority opportunities for guiding and enhancing this support:

• Access to Tools and Use Cases
  Access to mainstream AI platforms and tools is not universal across institutions. Further, greater guidance on evaluating and selecting the ever-increasing landscape of tools for specific use cases ensures that educators can identify solutions tailored to their needs.
• A Focus on Foundational AI Knowledge
  Training that prioritizes a basic understanding of AI and large language models before introducing advanced applications can better equip faculty to use the technology effectively while reducing the risk of AI burnout.

I can foresee many universities and organizations wasting a massive amount of time, effort, and money trying to keep up with each new software or update while ultimately delivering training content that goes immediately above 80–90 percent of people’s heads. Basics, basics, basics! That has to come first, and it will separate the great institutions from those frantically failing to keep up with an impossibly large tide of new tools and systems. (Faculty)

• Balanced Perspectives and Critical Evaluation
  Offering more balanced insights on the pros and cons of GenAI—beyond one-sided enthusiasm—fosters critical evaluation and smarter decision-making among faculty and administrators.
• Interdisciplinary Collaboration
  Promoting dialogue and collaboration across disciplines can uncover innovative ways to integrate GenAI into teaching, research, and operations while enhancing institutional understanding of its broader impact.

I believe that fostering a collaborative environment around AI/GenAI adoption at our business school is crucial. Encouraging interdisciplinary projects and discussions can enhance our understanding and application of AI across different domains. (Faculty)

• Collective Action and AACSB Guidance
  Institutions and the business education industry as a whole can benefit from collective efforts rather than isolated initiatives. AACSB can play a vital role in fostering this collaboration by connecting schools with AI trailblazers in industry and academia, subject matter experts, AI platforms and providers, and other resources.
• Resource Allocation and Support
  Given the costs associated with AI integration, it is essential that schools build their expertise in resource allocation strategies. These include securing dedicated grants, funding AI centers, ensuring access to platforms and subscriptions, and optimizing budget planning. Strengthening these capabilities will allow for sustainable and effective GenAI integration.
• Inclusion of Smaller-Resourced Schools and Diverse Contexts
  Ensuring that development opportunities cases, and examples are accessible to schools with fewer resources and those in less mature markets helps to democratize GenAI adoption and ensure its relevance across diverse educational contexts.

Though the Western world and top B Schools have started adopting GenAI for all facets of academic activity, the B Schools at our level have still not [caught] up with the trend. Educator programs at all levels would help level this gap. (Faculty)

• Policy Guidelines and Strategic Planning
  Establishing and sharing clear policy guidelines and strategies at both the institutional and industry levels can create consistency and clarity around GenAI use, helping faculty and administrators align with best practices.
• Time for Experimentation
  Allocating time for faculty to explore, experiment with, and integrate GenAI tools into their work is critical for building confidence and uncovering innovative applications. 

Conclusion

As many faculty and deans note in the survey, AI is evolving at an extraordinary pace, leaving industries—including education—grappling with how to strategically navigate this transformation. While opinions differ on whether AI will ultimately create more value or more harm in preparing future leaders, there is consensus that its impact will be profound. Maintaining a balanced perspective is crucial, with ethics emerging as a top priority to address.

In the spirit of innovation and continuous improvement, schools and faculty are encouraged to explore this technology, adopting an open-minded approach to how it can enhance their work, boost productivity, and, most importantly, prepare graduates to address the business challenges of tomorrow.

AACSB is on this exploratory journey alongside you, and the insights from this survey provide important directions for further consideration and action.

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