The AI Curriculum Challenge
How colleges can balance AI governance with growing employer demand for AI skills, and why intentional teaching, integration, and program design are essential.
Three years after the arrival of ChatGPT, higher education is facing an uncomfortable reality. Colleges are still debating whether to allow AI in the classroom, while employers like Microsoft, Google, and Goldman Sachs now list “AI proficiency” as a required skill in entry-level roles. At the same time, AI-generated cheating has reached an all-time high, putting institutions under pressure to police misuse while also preparing students for an AI-enabled workforce.
This tension set the stage for Rize’s recent webinar, Teach, Integrate, Prohibit? The AI Curriculum Challenge, featuring leaders in higher education who are actively shaping how AI is taught in higher education:
- Greg Edwards, VP of Learning and AI at Rize
- Risto Miikkulainen, Professor of Computer Science at UT Austin and VP of AI Research at Cognizant Advanced AI Labs
- Francesca Violich Kennedy, Instructional Design Lead at Rize
- Rob Lucas, Instructional Design Lead at Rize
- Kevin Roy, Product Marketing Lead at Rize
Together, they explored the central question facing every institution today: How should colleges teach AI when both the risks and the expectations are rising at the same time?
You can watch the full recording below, or keep reading for the highlights:
The Growing Tension: Policing or Proficiency
The webinar opened with what Rize has dubbed the "AI Skills Paradox." Students and employers overwhelmingly expect AI proficiency, yet very few institutions are intentionally teaching students how to use AI. The result is a widening gap. Colleges feel pressure to prevent AI misuse, but they also know students need structured guidance to build real workplace skills.
Two forces are driving this gap:
The policing challenge
In many disciplines, traditional assignments can now be completed by AI in under a minute and can produce work that appears convincingly authentic. Faculty often feel unprepared for this shift and unsure how to adapt assessments without lowering academic standards.
The market demand
Employers expect graduates to use AI as naturally as working professionals do. Students themselves are asking faculty for help on how to use AI responsibly and effectively across majors.
These pressures leave institutions stuck between outdated assessment models and rising expectations for workplace readiness.
What AI Integration Actually Looks Like
To move past the theory, the speakers walked through real examples of how faculty can design assignments for an AI-enabled world.
1. Boundary Assignments
Greg explained boundary assignments, which show students where AI helps and where it fails. In a public health course, for example, students use AI to create a complete intervention plan, then analyze its accuracy, feasibility, and ethical issues. This exercise creates an early shared understanding of where human judgment is still required.
2. Using AI Like a Professional
Francesca described how marketing students learn to work with tools used in industry, such as image generation or Sora. Students produce a full week of branded content, then refine it using the brand guidelines they created earlier. This mirrors the workflow of real creative teams and helps students build portfolio-ready projects.
3. Applied AI for Technical Majors
Rob walked through an optimization assignment where students compare several AI-powered algorithms that improve warehouse efficiency, then build their own. This teaches students how to evaluate, adapt, and create AI tools, which is exactly what employers expect from technical graduates.
4. Systems Thinking for MBA Students
In the AI MBA specialization, students map the workflows of an organization and determine where AI tools can support decision-making. They assess risks, identify areas where human oversight is essential, and consider how AI impacts business operations. This mirrors the strategic decisions real leaders face today.
What Colleges Need Now
The panel explained that colleges often stall for four reasons:
- Traditional assignments no longer measure the skills instructors intend to assess
- AI proficiency is not defined or measured consistently across departments
- Faculty have no baseline understanding of what students already know about AI
- Curriculum change moves slowly while AI tools evolve very quickly
Rize addresses these issues through structured scaffolding across programs:
- AI Literacy gives all students a baseline understanding of prompt engineering, evaluation, and responsible use
- Applied AI prepares technical majors to design, evaluate, and deploy AI systems
- MBA Specialization in AI helps emerging leaders understand strategic decision-making, implementation, ethics, and buy or build frameworks
Risto emphasized that the assignments must be tool agnostic. Tools change quickly, but the conceptual understanding behind them is what lasts.
From Interest to Implementation
The speakers closed with practical next steps for colleges, including starting conversations across departments about shared AI practice, redesign legacy assignments using the AI Assignment Design Canvas and building scaffolding across programs so students in all majors gain both literacy and domain-specific AI skills.
Examples from partner institutions like Belhaven University and Erskine College showed that full program-level integration is possible without adding years of development or hiring large teams. Faculty at these colleges are successfully embedding AI assignments across business, general education, and technical programs with support from Rize.
The Path Forward
Colleges will not be able to police their way through the AI era. The only viable path is education. AI will shape the future of work for every student, not only those in technical fields. Graduates who lack AI fluency will lose opportunities to those who know how to use the tools effectively.
Rize’s programs and assignment frameworks give colleges a feasible way to build a future-ready AI curriculum that enhances academic integrity, satisfies employer demand, and meets student expectations.
If your institution is exploring how to teach, integrate, or govern AI, Rize can help. To learn how to bring AI Literacy, Applied AI, or the AI MBA specialization to your campus, connect with the Rize team and begin preparing students for the future of work.
The AI Curriculum Challenge
How colleges can balance AI governance with growing employer demand for AI skills, and why intentional teaching, integration, and program design are essential.
Three years after the arrival of ChatGPT, higher education is facing an uncomfortable reality. Colleges are still debating whether to allow AI in the classroom, while employers like Microsoft, Google, and Goldman Sachs now list “AI proficiency” as a required skill in entry-level roles. At the same time, AI-generated cheating has reached an all-time high, putting institutions under pressure to police misuse while also preparing students for an AI-enabled workforce.
This tension set the stage for Rize’s recent webinar, Teach, Integrate, Prohibit? The AI Curriculum Challenge, featuring leaders in higher education who are actively shaping how AI is taught in higher education:
- Greg Edwards, VP of Learning and AI at Rize
- Risto Miikkulainen, Professor of Computer Science at UT Austin and VP of AI Research at Cognizant Advanced AI Labs
- Francesca Violich Kennedy, Instructional Design Lead at Rize
- Rob Lucas, Instructional Design Lead at Rize
- Kevin Roy, Product Marketing Lead at Rize
Together, they explored the central question facing every institution today: How should colleges teach AI when both the risks and the expectations are rising at the same time?
You can watch the full recording below, or keep reading for the highlights:
The Growing Tension: Policing or Proficiency
The webinar opened with what Rize has dubbed the "AI Skills Paradox." Students and employers overwhelmingly expect AI proficiency, yet very few institutions are intentionally teaching students how to use AI. The result is a widening gap. Colleges feel pressure to prevent AI misuse, but they also know students need structured guidance to build real workplace skills.
Two forces are driving this gap:
The policing challenge
In many disciplines, traditional assignments can now be completed by AI in under a minute and can produce work that appears convincingly authentic. Faculty often feel unprepared for this shift and unsure how to adapt assessments without lowering academic standards.
The market demand
Employers expect graduates to use AI as naturally as working professionals do. Students themselves are asking faculty for help on how to use AI responsibly and effectively across majors.
These pressures leave institutions stuck between outdated assessment models and rising expectations for workplace readiness.
What AI Integration Actually Looks Like
To move past the theory, the speakers walked through real examples of how faculty can design assignments for an AI-enabled world.
1. Boundary Assignments
Greg explained boundary assignments, which show students where AI helps and where it fails. In a public health course, for example, students use AI to create a complete intervention plan, then analyze its accuracy, feasibility, and ethical issues. This exercise creates an early shared understanding of where human judgment is still required.
2. Using AI Like a Professional
Francesca described how marketing students learn to work with tools used in industry, such as image generation or Sora. Students produce a full week of branded content, then refine it using the brand guidelines they created earlier. This mirrors the workflow of real creative teams and helps students build portfolio-ready projects.
3. Applied AI for Technical Majors
Rob walked through an optimization assignment where students compare several AI-powered algorithms that improve warehouse efficiency, then build their own. This teaches students how to evaluate, adapt, and create AI tools, which is exactly what employers expect from technical graduates.
4. Systems Thinking for MBA Students
In the AI MBA specialization, students map the workflows of an organization and determine where AI tools can support decision-making. They assess risks, identify areas where human oversight is essential, and consider how AI impacts business operations. This mirrors the strategic decisions real leaders face today.
What Colleges Need Now
The panel explained that colleges often stall for four reasons:
- Traditional assignments no longer measure the skills instructors intend to assess
- AI proficiency is not defined or measured consistently across departments
- Faculty have no baseline understanding of what students already know about AI
- Curriculum change moves slowly while AI tools evolve very quickly
Rize addresses these issues through structured scaffolding across programs:
- AI Literacy gives all students a baseline understanding of prompt engineering, evaluation, and responsible use
- Applied AI prepares technical majors to design, evaluate, and deploy AI systems
- MBA Specialization in AI helps emerging leaders understand strategic decision-making, implementation, ethics, and buy or build frameworks
Risto emphasized that the assignments must be tool agnostic. Tools change quickly, but the conceptual understanding behind them is what lasts.
From Interest to Implementation
The speakers closed with practical next steps for colleges, including starting conversations across departments about shared AI practice, redesign legacy assignments using the AI Assignment Design Canvas and building scaffolding across programs so students in all majors gain both literacy and domain-specific AI skills.
Examples from partner institutions like Belhaven University and Erskine College showed that full program-level integration is possible without adding years of development or hiring large teams. Faculty at these colleges are successfully embedding AI assignments across business, general education, and technical programs with support from Rize.
The Path Forward
Colleges will not be able to police their way through the AI era. The only viable path is education. AI will shape the future of work for every student, not only those in technical fields. Graduates who lack AI fluency will lose opportunities to those who know how to use the tools effectively.
Rize’s programs and assignment frameworks give colleges a feasible way to build a future-ready AI curriculum that enhances academic integrity, satisfies employer demand, and meets student expectations.
If your institution is exploring how to teach, integrate, or govern AI, Rize can help. To learn how to bring AI Literacy, Applied AI, or the AI MBA specialization to your campus, connect with the Rize team and begin preparing students for the future of work.
