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Navigating AI Adoption for Businesses

A Conversation with Heather Harris from Herkimer Consulting

Hello readers!

On this week’s podcast, Ryan and Neil speak with Heather Harris, Principal Data Scientist at Herkimer Consulting, about how businesses can better navigate the field of AI adoption and challenges such as data integrity, identifying true AI solutions, and obtaining the right data.

Why You Won’t Want to Miss This

  1. Discover the importance of AI literacy among leadership for discerning and navigating AI solutions in business.

  2. Learn about the pitfalls and challenges of adopting AI in various business settings, emphasizing the need for strategic and informed decision-making.

  3. Gain insights into the importance of aligning AI adoption with business goals and the necessity of understanding underlying technologies.

  4. Explore the role of data integrity and quality in successful AI implementation, including strategies for managing and utilizing data effectively.

  5. Understand the evolving landscape of AI in business, covering topics from data analytics to machine learning and the importance of staying informed.

Our Favorite Moment

“We need to also promote AI literacy, so we understand that all the information that we're being fed by AI isn't necessarily going to be accurate. We need to make sure we know ourselves well enough that the AI doesn't know us better, and we don't start trusting it more than we trust ourselves.”

— Heather Harris

Navigating AI Adoption

Meet Heather Harris

Heather Harris has a PhD in statistics related to cognitive processes, and she has worked as a consulting data scientist and statistician for 6 years. Her approach to consulting is to guide clients through setting up complex processes and AI solutions while keeping data governance, data integrity, and diversity/data representativeness front-of-mind.

As a consultant, she’s led a multitude of diverse projects including predicting audiences and micro-target marketing for the first movie with a theatrical release following the pandemic, predicting and segmenting viewers for several television shows and networks, developing scoring algorithms for EdTech companies, and working with clients from several substantive areas to architect data ecosystems for AI solutions and advanced analytics.