AI isn’t just hype or headlines—it’s a tool. And like any tool, it’s only as useful as the person using it. In this episode, Michelle sits down with Emily Heavner, product manager at Aspect (and PhD in mathematics), to demystify artificial intelligence and its place in the modern workplace. Emily shares how AI works, clears up common misconceptions, and explains why data—not magic—is the true engine behind intelligent systems. If you’ve ever wondered how AI can support your work, or how to spot red flags in tools you're adopting, this one’s for you.

You’ll Learn
• Why AI depends entirely on good data
• How AI compares to other automation tools
• What AI can (and can’t) replace at work
• How to evaluate AI tools with privacy and values in mind
• Where AI shines in boosting productivity and decision-making

Perfect For
Workplace leaders, team builders, data geeks, skeptics of AI hype, and anyone curious about how to use AI as a helpful, human-supporting tool.

Keywords
AI, artificial intelligence, workforce, data, machine learning, algorithms, productivity, misconceptions, applications, technology

Takeaways

• AI helps parse large data sets into usable, decision-ready insights
• Automation doesn't always require AI; not all AI is automation
• Quality data is the foundation—bad data, bad results
• AI should be evaluated through privacy, compliance, and value alignment
• Not everyone needs a full AI “tool shed”—just the right tools for the job
• AI isn’t new—it’s been decades in the making and is here to stay
• A well-built AI system improves with feedback and updated data
• Trust in AI increases when people understand how it actually works

Sound Bites

• “AI can and will support actual work.”
• “It’s all about data.”
• “You don’t need a tool shed. Sometimes you just need a hammer.”
• “If it doesn’t align with your core values, don’t use it.”
• “AI is not a new concept.”

Chapters
00:00 Introduction to Emily & AI
05:13 How Emily Got into Algorithm Development
11:30 Understanding What an Algorithm Actually Is
18:53 The Mechanics of Machine Learning
25:05 Common Misconceptions About AI and Automation
31:16 Data: The True Engine Behind AI
37:36 Evaluating AI Tools in the Workplace
44:25 Aligning Tools with Your Team's Values
50:12 Productivity, Trust, and Use Cases for AI
56:44 AI's Role at Aspect and the Future of Work

Related links for this episode:
· Emily Heavner – https://www.eheavner.com
· Aspect – https://www.aspect.company

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Learn more about Aspect at -

https://www.aspect.com/

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