Join us for DataConnect Conference Oct 2-3 in Columbus, OH!
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This talk explores how organizations can avoid these pitfalls and move toward scalable, trusted AI adoption.
Many AI solutions get stuck in “POC hell”. These models (and the teams behind them) often face the same barriers: unclear business priorities, incomplete data pipelines, endless iterations without deployment, and stakeholders losing patience before results appear.This talk explores how organizations can avoid these pitfalls and move toward scalable, trusted AI adoption. Drawing on real-world stories from both high-risk industries and customer-facing applications, we’ll highlight common traps and show practical ways to reframe the journey from the start. We’ll outline predictable hurdles and proactive strategies to overcome them, helping you shift experimentation from “AI for AI’s sake” toward solutions that create lasting value.
While each organization’s path is unique, we've seen consistent patterns that work. We’ll show how tools and processes including strategy workshops, collaborative design, and disciplined development practices have helped teams align stakeholders, build confidence, and deliver AI solutions that get adopted.
If you’re ready to shift your organization from experimentation to building AI that earns trust, delivers value, and scales, this talk is for you.
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Kristy Hollingshead is a Senior Data Science Lead at Further, where she leads solution design and development for several different clients in the healthcare space. Her expertise lies in natural language processing (NLP) and machine learning, especially in parsing, semantics, anomaly detection, and linguistics-based profile analysis. In a previous role as a Research Scientist at the Florida Institute for Human & Machine Cognition (IHMC), Kristy led small technical teams implementing prototype systems for data wrangling and visualization of social media data for non-technical users to increase situational awareness. Her earliest work in the field was seminal in demonstrating that our everyday language - spoken or written - carries quantifiable indicators of neurological and mental health. Kristy is passionate about applications of AI that enable people to do what we are good at, and are not competitors to nor replacements for people, but instead serve as useful tools for us.
With a PhD in computer science from Oregon Health & Science University, Kristy’s work has long focused on providing actionable insights to non-data science practitioners, including clinicians, therapists, social workers, astronauts, and operations support. She has been a member of and reviewer for the Association for Computational Linguistics (ACL) since 2006, and served as a co-founder and co-organizer of the Computational Linguistics and Clinical Psychology (CLPsych) annual workshop from 2015 to 2020. In her spare time, Kristy is chasing her goal of running a half marathon in all 50 states (current count: 28).
