On October 31st, MBA students participated in a workshop led by Matt Seitz, Director of the AI Hub at the Wisconsin School of Business. The session brought together students from Corporate Finance & Investment Banking (CFIB), Technology Strategy & Product Management (TSPM), and Marketing to tackle the challenge of launching two new products for Nova, a fictional athletic gear company.
We used AI throughout the entire process, from market research to financial modeling to presentation, and it reshaped our perspective on AI in business.
The Challenge: Only Two Hours to Launch
We had a straightforward mission: analyze Nova’s market position, identify an unmet need, design a physical and digital product concept, build a business case, and present it to an “AI CEO”.
Our group divided the work by program track. Marketing analyzed trends and identified opportunities. TSPM developed the product concept and features. CFIB built revenue projections and ROI scenarios. Each phase required both AI assistance and human judgment.
Where AI Accelerated Our Work
AI made us quicker and expanded what we could accomplish in a tight timeframe. Market research that would normally take weeks was done in seconds. AI estimated market size, identified key competitors, and summarized consumer trends.
When generating product concepts, AI offered a multitude of product ideas. It suggested features and identified pain points across customer segments.
Financial modeling was also much faster. Building multiple launch scenarios with different pricing strategies and volume assumptions, usually an arduous Excel task, took a fraction of the time.
The Limits of AI
Speed came with trade-offs.
Market data lacked credibility and changed when we pushed for reasoning. We realized we were accepting claims that would never pass in a real business setting, highlighting that AI’s seemingly unlimited output requires thorough human validation.
We faced the same issue with our financial model. AI produced revenue and growth projections that looked impressive and well put together but were unrealistic. It gave us overly optimistic margins, instant market adoption and volume figures for which the logic was difficult to follow.
Most importantly, our differentiating product concept didn’t come from AI at all. A teammate brought the idea to the session, which was formulated from their work experience in dermatology, and to us, it outperformed every AI-generated idea. That encompassed the core lesson, AI can accelerate the pace of your output, but it cannot replace human experience or intuition
Don’t Let AI Take the Wheel
AI is great for the blank-page problem, brainstorming and ideation are quicker, but it primes the user to think in a specific way and leads you down predictable paths.
When we let AI lead, we got average solutions. The differentiated concepts came when we started with our own hypotheses and used AI to stress-test and expand on. We didn’t want the first obvious answer; we wanted to dig deep for the best solution to our specific problem and AI helped us do that.
AI Toolkit
Another insight from the workshop, not all AI models are created equal. We used multiple LLMs and found specific strengths.
Claude was helpful with analysis and relaying detailed explanations; ChatGPT was strongest for creative brainstorming, and Gemini was useful for data synthesis. To take advantage of the power of these models, you need to utilize each differently to match it to the task at hand.
What This Means for Our Careers
The skills we practiced, prompting effectively, validating outputs and integrating AI into workflows, are what employers expect from the next generation of finance leaders.
Companies aren’t looking for people who can work without AI. They’re looking for people who can work better with AI. The competitive advantage in the workforce will go to those who can wield these tools effectively while thinking critically and using sound judgement.
Final Thoughts
Two hours utilizing AI in this manner taught me more about its capabilities and downsides than any video or article I’ve come across. The tech is no doubt transformational, akin to the internet, but it isn’t a substitute for human expertise and intuition.
The future of business isn’t man versus machine, it’s a partnership where we provide vision, context, and judgment and AI provides speed and scale.
Thanks to Matt Seitz and the AI Hub at WSB for designing an experience that prepared us for this future.
Interested in learning more about AI applications in business? Connect with the Wisconsin School of Business AI Hub or reach out to discuss how these tools are reshaping your business.