Applied Intelligence: A Scalable Path to Production for Your AI Initiatives
Across the industry, nearly 90% of models fail to be leveraged for production decisioning and the “successful” 10% take too long and cost too much. With the statistics not in your favor, understanding the root causes of failed AI projects is critical to ensure that your initiatives don’t share a similar fate. Learn best practices and how to establish a repeatable, outcome-driven approach that aligns data science and IT teams and enables the AI lifecycle from idea to production to realized business value. With companies finally beginning to find success in building and validating quality models, the session will focus on the “last mile” problem of using those models in production to automate and optimize business decisions and customer interactions. Discover how capabilities like feature stores, model deployment, data and ML pipelines, feedback loops, human-in-the-loop and automated model retraining, drift and anomaly detection, and model and decision performance monitoring are all essential to fully leverage Applied Intelligence throughout your organization.
Key Takeaways: • Ensure success by selecting the right use cases and establishing early wins for your organization • Define a repeatable path to production decisioning for AI models • Learn how to increase analytic throughput and other KPIs used to measure productivity and ROI of your AI initiatives
Alex Fly is the Co-founder and CEO of Quickpath, an Applied Intelligence company focused on enabling businesses to make automated, intelligent decisions throughout their organizations using machine learning and artificial intelligence. He is an experienced speaker, thought-leader, and industry expert in leveraging applied intelligence to automate and optimize business processes and customer interactions. Alex is a trusted partner to Quickpath’s customers, helping them deliver real-time data and analytic products that provide massive business value across their organizations.