Summary: AI hype makes it difficult to separate genuine opportunity from vendor marketing. Mid-market leaders face pressure to 'do something with AI' but lack enterprise research budgets to evaluate options. This session provides the strategic filter CFOs need.

Outcome: Clear-eyed view of AI opportunities vs. hype for mid-market    

Takeaway: Decision framework for evaluating any AI investment

Key Discussion Points:

• Evidence-based assessment of AI categories with real ROI data
• What actually works: customer service AI, document processing, Excel productivity
• What to avoid: custom LLMs, fully autonomous decisions, massive data projects without clear use cases
• Warning signs of overhype: fully autonomous promises, vague ROI claims, 'transformational' language
• The 70/20/10 rule: 70% people/process, 20% technology/data, 10% algorithms
• Vendor evaluation: separating marketing from capability
• Build vs. buy considerations for mid-market
• Pilot design that actually tests value
• Realistic timelines and investment requirements
• When to wait vs. when to move