Innovation with Integrity: Why Business Schools Can’t Compete Alone on Trust

At AABS Connect 2026 a conversation on technology, ethics, and quality in business education uncovered a deeper inquiry into trust and the pre-competitive foundation on which business education globally depends.

The annual AABS Connect Conference convened in Addis Ababa was themed “African Values, Global Futures: The Role of Business Schools in Driving a Transforming Continent.” and hosted by Kibur College.

Ethiopia, with its rich archaeological record pointing to early human origins, also gave the session a deeper human horizon and the conference venue, Africa Hall the UNECA head quarter, has long been associated with pan-African policymaking and deliberation. 

In other words, a conversation about technology, integrity, and the future of business education unfolded in a country that has long helped humanity understand where we come from — a powerful reminder that innovation should be rooted not only in the future we imagine, but in the deep human story we inherit.

A session hosted by John North, Executive Director of the GRLI Foundation, in conversation with Hermann Ndofor of Florida State University, resulted in a working conversation with the entire room. Participants were invited to reflect together through four lenses: technology and academic integrity; governance and leadership; quality assurance and standards; and the tension between innovation speed, public trust, transparency, and compliance.

To open the discussion John put forward a simple proposition:

Business schools compete on many things: reputation, rankings, faculty, programmes, partnerships, employability, international reach. But beneath all of this sits something they cannot compete on alone: whether society trusts that a degree means something, whether assessment is credible, whether research is reliable, whether graduates have developed judgement, and whether business education is serving the futures it claims to serve.

This can be framed as the pre-competitive floor.

If that floor weakens, every school is affected – not only those who failed to adapt.

The session therefore resisted the temptation to reduce “innovation with integrity” to a technical debate about AI tools, cheating detection, or digital learning platforms. Those questions matter. But the deeper question is whether business schools can develop forms of learning, research, assessment, and leadership that are worthy of the world these technologies are creating.

This linked directly to recent work in the GRLI Deans & Directors Collective, hosted by SPJIMR, where participants explored wise innovation as a practical leadership capacity: context-sensitive judgement under uncertainty, exercised over time, and accountable to consequences.

Innovation, the conversation opening suggested, is not wise simply because it is new, fast, or efficient. Innovation becomes wise when it strengthens judgement, deepens responsibility, and protects the trust on which institutions depend.

Four lenses on integrity

The room worked through four practical lenses. Each lens opened a different part of the integrity challenge.

1. Technology, academic integrity, and misuse

The first lens asked:

How can business schools integrate emerging technologies such as AI and digital learning platforms while safeguarding academic integrity and preventing misuse?

The sharper question underneath was:

What should we stop pretending we can police, and what should we start designing for instead?

This shifted the conversation from detection to design.

Of course, rules and boundaries matter. But if the institutional response to AI becomes primarily a search for better policing, business schools risk designing education around suspicion. That is a weak basis for formation.

The more promising design question is: what forms of learning and assessment make integrity more natural, visible, and relational?

Shorthand examples that were mentioned included:

• Disclosure norms — helping students and faculty state clearly how AI or digital tools were used.
• Oral defence — asking students to stand in relationship to their work and explain their judgement.
• Process evidence — assessing drafts, decisions, reflections, and learning journeys, not only final products.
• Authentic assessment — connecting work to real organisations, communities, and consequences.
• Research transparency — clarifying data sources, consent, attribution, and methodological choices.
• Faculty capability — equipping educators to redesign learning rather than simply detect misuse.

Hermann Ndofor brought a particularly important research and publishing perspective. From the scholar/editor side, integrity is being contested not only in student work, but in scholarly writing, data collection, data scraping, consent, and the limits of proving whether AI has been used.

The implication was clear: detection alone is a losing battle. The work is to design environments where judgement, transparency, and accountability are visible.

2. Governance and leadership

The second lens asked:

What governance frameworks and leadership approaches are needed to ensure ethical adoption of technology in business education?

A key distinction emerged:

A policy is a document. Governance is the living system of responsibility, transparency, accountability, and learning around that document.

Many institutions are now writing AI policies. That is necessary, but insufficient. Policies do not govern by themselves. They need practices, rhythms, incentives, review mechanisms, and trusted spaces where people can learn what the policy means in real situations.

Shorthand examples included:

• AI disclosure practices embedded into coursework and research.
• Faculty learning circles where educators compare experiments and dilemmas.
• Student compacts that clarify shared expectations around technology use.
• Research ethics updates for AI-assisted writing, scraping, data reuse, and consent.
• Cross-school governance groups that include academic, administrative, student, and quality perspectives.
• Sandboxes for experimentation where new practices can be tested safely.
• Annual integrity reviews that ask whether policy is shaping actual behaviour.

The leadership posture proposed was disciplined experimentation.

Deans and directors are under pressure to innovate, protect reputation, reassure faculty, satisfy students, meet regulatory expectations, and remain competitive. In that environment, leaders may be tempted either to overreact with control or underreact with vague encouragement.

Disciplined experimentation offers a third path: name the non-negotiables, create protected spaces for learning, document what is being discovered, and adjust institutional norms based on evidence.

Wise innovation is not the absence of risk. It is the capacity to exercise judgement when the trade-offs are not clean.

3. Quality assurance, standards, and accreditation

The third lens asked:

In what ways can quality assurance systems evolve to keep pace with rapid digital innovation without compromising standards and accreditation requirements?

Here the session introduced another distinction:

Compliance asks: did we follow the rule?
Trust asks: can others rely on what we claim?

Quality assurance has traditionally helped institutions demonstrate that they meet standards. But in a rapidly changing technological environment, the question becomes more demanding. It is not only whether a school has an AI policy. It is whether the policy is shaping practice. It is not only whether assessments are secure. It is whether they are meaningful. It is not only whether ethics appears in the curriculum. It is whether graduates are developing judgement.

Shorthand examples of what quality systems may need to see more clearly included:

• Evidence of student judgement, not only evidence of task completion.
• Process evidence, not only final outputs.
• Faculty capability to teach, assess, and research in AI-rich environments.
• Responsible AI use as a developmental and ethical practice.
• Research integrity culture, especially where incentives push in the opposite direction.
• Assessment authenticity, including links to context, relationship, and consequence.
• Employer and community trust, not only internal institutional compliance.
• Alumni learning loops, recognising that formation may increasingly extend beyond the bounded degree.

This again connects to learning from the recent GRLI Deans & Directors Collective: incentives are often the hard terrain. Leaders may want different outcomes, but rankings, accreditation signals, promotion pathways, and inherited KPIs continue to shape behaviour. (Global Responsibility)

Quality assurance, then, cannot only assure yesterday’s standards. It must help institutions notice whether today’s standards still protect tomorrow’s trust.

4. Innovation speed, public trust, transparency, and compliance

The fourth lens asked:

How can institutions balance the pressure to innovate quickly with the responsibility to maintain public trust, transparency, and regulatory compliance?

The session suggested that institutions need to operate at different speeds at the same time:

1. Move quickly where experimentation is reversible and learning is the goal.
2. Move carefully where credentials, student rights, research integrity, public claims, and institutional legitimacy are at stake.
3. Move transparently all the time.

This led to a practical question:

What is one small experiment a school could try in the next 90 days — and what would need to be transparent for that experiment to build trust rather than erode it?

Shorthand examples included:

• A 90-day AI disclosure protocol in selected courses.
• A redesigned assessment that combines AI-assisted work with oral defence.
• A faculty peer-learning circle on assessment redesign.
• A research integrity review of AI-assisted writing and data collection practices.
• A student-facing guide to acceptable, unacceptable, and discloseable uses of AI.
• A quality assurance pilot that tracks process evidence and reflective judgement.
• A cross-institutional exchange where schools compare what they are learning.

The key was not experimentation for its own sake. The key was transparent learning.

If every school learns privately, slowly, and defensively, the whole field will lag behind the technology. But if schools can share what worked, what failed, what created risk, and what improved learning, the field can move faster without becoming reckless.

This is where the pre-competitive dimension becomes practical. Business schools can compete on reputation, programmes, and partnerships. But they cannot outcompete each other on shared trust.

Integrity is multi-level

One of the central insights of the session was that integrity is not one thing.

It is context-dependent, and it operates at multiple levels.

1. There is the individual level: the graduate’s character, the researcher’s ethics, the faculty member’s judgement.
2. There is the institutional level: policies, assessment, research culture, quality assurance, governance, and credibility.
3. And there is the ecosystem level: accreditation, rankings, journals, associations, employers, public trust, and the rules of the global system itself.

All three levels are now being contested.

This matters especially in African business education, where formal and informal systems often coexist, and where trust, relationship, community, scarcity, ingenuity, entrepreneurship, and legitimacy are lived realities rather than abstract concepts. The session therefore invited a shift in posture: African business schools should not be positioned as late adopters of someone else’s answers. They can be originators of grounded answers that matter to the wider world.

Innovation beyond the shiny new thing

The conversation also cautioned against treating AI as the whole story. AI is important. It is powerful. It is already changing how students learn, how faculty teach, how researchers write, and how institutions operate. But focusing exclusively on AI risks turning it into another shiny new thing.

The more fundamental question is not how to make old systems ten percent more efficient. The more fundamental question is what these technologies invite business schools to reimagine.

What is a business school for? 

• If technology can generate polished answers, then business schools must become better at forming people who can ask better questions.
• If machines can optimise tasks, then business schools must form graduates who can ask whether the task is worth doing.
• If AI can accelerate production, then business schools must protect the time, relationship, and reflection through which judgement is formed.

The real work is not simply preventing or perfecting technology use. It is developing humanity — in researchers, teachers, deans, administrators, and students — as the distinctive edge in a world of increasingly capable machines.

From a GRLI perspective, this connects to global responsibility as an integrative responsibility to the self, the other, and the whole: I, We, All of Us. GRLI’s work has long centred on linking inner capacity and relational practice with the structural redesign of the systems that educate leaders.

Toward a pre-competitive floor of trust

The invitation from Africa Hall was not only for each school to protect itself. It was for business schools, associations, accreditors, researchers, students, employers, and partners to co-steward the trust on which all depend.

For African business schools, this is not a call to wait for global answers. It is an opportunity to contribute grounded insight from contexts where complexity, informality, community, entrepreneurship, scarcity, ingenuity, and relational trust are part of daily institutional life.

The future of business education will not be secured by competing harder to be the best in the world.

It will require collaborating more wisely to be the best for the world.

Because business schools can compete on many things. But they cannot compete alone on integrity.