Closing the AI Gap in Business Education

• Business schools can lead the AI revolution only by creating systems that allow the rapid incorporation of AI into their teaching, research, and strategic planning.
• A school’s necessary first step is to form an AI task force or dedicated center to assess readiness, develop an AI strategy, and measure progress toward key performance indicators.
• Sustained AI readiness depends on robust faculty development, strong external partnerships, and an academic culture that promotes responsible AI use.

 
As artificial intelligence rapidly transforms the workplace, employers increasingly expect graduates to arrive with practical experience using AI tools. According to a recent global report, 77 percent of employers expect new graduates to have experience with AI, yet 58 percent believe that higher education institutions are not doing enough to develop these skills.

Business schools now face the challenge of adapting their teaching methods, curricula, and learning experiences much more rapidly than before. However, structural constraints within universities often make this difficult. Academic programs typically require multiple layers of governance and approval before changes are implemented, slowing down the integration of emerging technologies into teaching.

How, then, can business schools keep pace with the rapid evolution of AI while meeting both student expectations and labor market needs? They must create robust systems for incorporating AI into their teaching, research, and institutional cultures.

Institutional Governance and Strategic Alignment

A first essential step is the development of clear institutional governance frameworks for AI. These frameworks should define how a school’s community uses AI tools across teaching, research, and administrative processes, while ensuring ethical practices.

At UPF Barcelona School of Management (UPF-BSM), we are addressing AI strategically across governance, teaching, and knowledge transfer. Our AI Task Force, established in 2024, aims to enhance academic quality and innovation by embedding AI into the curriculum, promoting impactful scientific output, and improving institutional efficiency through the optimization of administrative and operational processes.

The Task Force is composed of internal experts from UPF-BSM as well as external members who are primarily engineers and industry professionals. So far, its members have developed an AI readiness strategy, which includes a set of key performance indicators (KPIs) that the school’s leaders will use to assess the institution’s preparedness to scale AI adoption between 2025 and 2030. These KPIs include metrics such as the percentage of courses following AI guidelines, the proportion of faculty and staff with certified AI literacy, and the rate of cross-departmental AI integration.

AI in Teaching and Assessment

A critical dimension of this transformation lies in rethinking how schools incorporate AI into teaching and assessment. Rather than relying on isolated experimentation by individual faculty members, business schools should develop shared methodologies across their teaching portfolios that embed generative AI (GenAI) tools into learning activities while safeguarding academic rigor.

At UPF-BSM, we have developed a Faculty Integration Guide that offers concrete methodologies for incorporating GenAI into coursework, assessment design, and research, while protecting learning outcomes and fostering critical thinking. In parallel, we have created comprehensive GenAI usage guides for students, which align pedagogical innovation with academic integrity, regulatory developments, and global AI literacy standards. Both guides were developed by AI Task Force members and reviewed by external advisors.

Clear institutional governance frameworks should define how a school’s community uses AI tools across teaching, research, and administrative processes, while ensuring ethical practices.

As part of this approach, every student has access to a free introductory course that explains how GenAI works and defines the technology’s capabilities and limitations. At the same time, faculty benefit from dedicated training programs that support the redesign of courses and teaching methods.

This dual approach ensures that both learners and educators develop a balanced understanding of AI as a tool that enhances—rather than replaces—human judgment and creativity.

Supporting Responsible AI Literacy

AI competencies are not purely technical; they also require ethical awareness. Business schools must therefore promote responsible AI literacy across all programs and activities, ensuring that students understand both the opportunities and the risks associated with the technology.

To support this objective, UPF-BSM was part of the AI Leaders Project, funded by the European Union’s Erasmus+ initiative. The project’s goal was to develop resources for educators to use in their teaching, in order to prepare future business leaders to develop and apply AI solutions aligned with European ethical standards.

The project included six partners: the University of Lodz in Poland (the project coordinator), the University of Porto in Portugal, and UPF-BSM, as well as the Accreditation Council for Entrepreneurial and Engaged Universities, the European E-learning Institute, and Feltech Software Innovations Ltd.

Although the work is now complete, its resources remain accessible on the AI Leader Project’s website, in multiple languages, for interested educators, professionals, or institutions. These free resources include:

• An Introductory Toolkit and a set of Responsible AI Case Studies that provide conceptual foundations on AI, its business applications, and associated ethical dilemmas.
• AI Open Educational Resources (OERs) based on real-world cases, including practical activities, simulations, interactive tools, and faculty guides, organized across key areas such as marketing, human resources, finance, supply chain, and leadership.
• A hackathon model focused on AI in business management, accompanied by a guide to facilitate its implementation in other institutions.

Academic partners created the content, while nonacademic partners handled its formatting, translation, and publication. All partners participated in reviewing the final products to ensure quality and consistency.

For example, the OERs were tested by a focus group of 30 instructors in their classes across three academic institutions; the materials were then refined based on feedback collected from the instructors and around 90 students. The hackathon model also was piloted at three institutions, with each test involving approximately 30 students, ten professors, and five industry experts.

All these materials are open, flexible, reusable, and designed to support the teaching of AI. Their purpose is to support the education of ethical future business leaders.

AI competencies are not purely technical; they also require ethical awareness. Students must understand both the opportunities and the risks associated with the technology.

UPF-BSM faculty have already implemented these resources in programs such as the Master in Marketing and the MBA. For example, in the course Marketing Analytics and Big Data, these resources supported students as they developed functional chatbots using beginner-friendly tools, incorporating principles of ethical design.

In the course Technology Disruption in Organizations, students analyzed the impact of replacing human agents with AI chatbots. They went beyond a focus on operational KPIs such as efficiency and response time to also incorporate qualitative metrics such as satisfaction and trust. The course also emphasized the value of testing small-scale prototypes before scaling AI solutions.

Investing in Faculty and Staff Development

The successful integration of AI into education depends on the engagement and capability of a school’s faculty and staff. Business schools must therefore invest in development initiatives that build confidence and competence in the use of AI.

At UPF-BSM, we are embedding AI into our academic culture through development initiatives, including a comprehensive GenAI training program available to all faculty and staff. This initiative equips participants with practical skills in leading AI tools such as Perplexity, NotebookLM, Canva, Gamma, and Copilot.

We want to enable our faculty and staff to enhance teaching, research, and administrative practices, as well as foster the responsible and informed use of AI across the institution. Moreover, UPF-BSM has signed an agreement with Microsoft to take advantage of its MS Learn for Educators program, which provides free training opportunities for our faculty.

Staying Up to Date Through Collaboration

Business schools cannot address the AI challenge in isolation. It is also essential that they engage in close collaboration with companies, public institutions, and technology partners to ensure that their teaching remains aligned with real-world developments.

Beyond our own classrooms, UPF-BSM participates in international collaborations such as the Digital Education Council’s Teaching With AI Working Group. As part of this community, we exchange best practices with other business schools, co-develop training resources, and contribute to the definition of governance standards for the ethical use of AI in academic environments.

In addition, we participated in a council working group to produce “Ten Dimension AI Readiness Framework,” a report that highlights a shared structure that higher education institutions can use to assess their AI readiness. We also engage in the Higher Education Leader Series organized by Google for Education. This series brings together representatives from higher education institutions in Spain, Portugal, and other countries to explore new tools and their application in teaching.

Our Long-Term AI Vision

Now that UPF-BSM has established a solid infrastructure, its next phase is not simply about maintaining momentum, but about evolving to a fully embedded AI scenario. We want to move beyond isolated initiatives to ensure that AI becomes a core, coordinated driver of transformation across the school.

At a community level, a key priority will be placing people at the center of this evolution. Rather than focusing primarily on technology, the school will invest in building an inclusive, human-in-the-loop culture that promotes AI literacy, ethical awareness, and continuous professional development for faculty, staff, and students.

At the academic level, UPF-BSM aims to integrate AI across curricula, rethinking pedagogical approaches and strengthening research capabilities to shape responsible, future-ready leaders. To sustain and scale these efforts, the school will develop infrastructure designed to be resilient, adaptive, secure, and accessible, with the goal of reducing rather than reinforcing digital divides.

There is a pressing need for business schools to bring students, faculty, and employers closer together around a shared understanding of AI and its implications.

Finally, our ambition extends beyond our own institution. We aim not only to transform the way we teach, learn, and operate, but also to help other organizations embrace the opportunities of this digital revolution.

In line with this vision, we recently launched the AI Business Transformation Institute, an initiative designed to support companies and institutions in adopting artificial intelligence through executive education, training programs, and advisory services focused on its ethical and responsible implementation. The institute brings together faculty members and leading industry experts, combining academic rigor with practical expertise to address the challenges and opportunities of AI-driven business transformation.

In short, our next steps are focused on deepening our impact. For this, we will align our strategy, empower our people, embed AI at the core of our academic and organizational activities, and strengthen our role as a global leader in innovation.

Bridging the Gap

To set out clear systems for AI implementation, schools must make deliberate commitments in three areas:

• Establishing governance bodies, such as task forces or dedicated centers, to assess the school’s current level of AI readiness and define clear, achievable objectives.
• Setting well-defined goals, including KPIs and a realistic five-year roadmap.
• Focusing on progressively achieving AI readiness, rather than on attempting a full-scale, immediate implementation of technology across the institution. Schools must remain pragmatic rather than overly ambitious, as unrealistic expectations can lead to frustration.

As AI use in business continues to expand, such commitments have become imperative. There is a pressing need for business schools to bring students, faculty, and employers closer together around a shared understanding of AI and its implications. Institutions need to create more structured opportunities to engage with companies, better understand their evolving needs, and develop agile mechanisms to translate these insights rapidly into program design and delivery.

Only by adopting a sustained, coordinated strategy can business schools effectively bridge the gap between academia and the workplace in the age of artificial intelligence.