Business Education in the Age of Abundant Intelligence
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Artificial Intelligence
What Business Education Must Teach When Intelligence Becomes Abundant
Published: 27 October 2026
Written by: Christoph Herpfer
Assistant Professor of Business Administration
In the era of powerful AI, the constraint is no longer producing analysis. Instead, it is about defining tasks and deciding outputs: who to send, what to believe, and what to ignore. Leadership becomes the binding constraint.
Consider this scenario:
Mike is inventive but often suggests impractical ideas, while Jane is precise like a Swiss engineer, yet can lose sight of the bigger picture.
Good managers leverage their team members' strengths, directing them accordingly.
"Mike, find an unconventional solution to this problem."
"Jane, audit our assumptions and every line of code."
This situation feels familiar, but something new is at play. Neither Mike nor Jane are human; they are AI agents and sub-agents working together.
AI agents create a new management challenge: managing AI itself.
Directing AI agents is similar to managing a talented yet flawed team. Managers assign tasks based on skills and individual constraints, anticipate challenges, intervene when needed, and decide when a final product is ready.
However, a crucial difference arises: AI tools like Codex, Claude Code, and Grok Bot can tailor teams for each task. You can add more skeptics for extra assurance, replace generalists with specialists, or deploy more creative minds for high-risk attempts, while using more capable (and expensive) models for critical decisions. As AI usage costs rise, matching model capabilities to tasks becomes a key managerial skill.
When Intelligence Becomes Abundant
In the past, scarce analytical intelligence required expert time and apprentice analysts to generate analysis. Now, AI agents can produce first-pass analyses on complex tasks, summarize information, and draft reports at lightning speed. While AI can still generate "hallucinations" without proper management, it makes analytical reasoning abundant and affordable.
Leaders can now request multiple forecasts and involve diverse AI agents in evaluating recommendations. However, the human capacity to process and act upon this information has not kept pace, with even AI power users reporting difficulty managing more than five parallel AI workflows.
What does this shift mean for business schools?
Agentic AI demands the very skills an MBA aims to cultivate:
- Judgment under uncertainty
- Leveraging diverse perspectives
- Navigating complex systems
- Adapting to rapid change
- Ethical considerations in AI deployment