AI Con USA 2025 - IT Technology Leader

Understanding the readiness of your source data before you launch an expensive AI/ML project lets you take corrective data engineering measures that will streamline the project and give you the best probability of a successful outcome.  Artificial Intelligence (AI) and Machine Learning (ML) projects can provide significant returns on investment when they are applied to narrow but difficult business problems and are supported by adequate amounts of relevant, quality data. Many such projects start with high hopes but get derailed due to fundamental problems with source data, which were...

Executive leaders across the globe have been asking a relatively simple yet profound question: Can we leverage generative AI to transform our business, enterprise, or industry? For software-based companies, focus has either been on differentiating their product and service offerings using this new technology. But how about leveraging generative AI to improve team productivity and efficiency? This may be possible but how do you measure its success? What are some of the key use cases within business analysis, development, and testing that software teams can use? Are there any pitfalls...

Retrieval-Augmented Generation (RAG) applications are becoming essential for companies, combining AI with real-time data retrieval to enhance customer experiences. While Large Language Models (LLMs) handle general conversation well, they struggle with domain-specific, up-to-date information, often producing inaccurate or unhelpful responses. This workshop will empower participants with the necessary skills to optimize RAG applications using existing best practices. Justin will walk through integrating RAGAS, a framework designed to evaluate, monitor, and fine-tune the performance of RAG...

Large language models, like Generative Pre-trained Transformers (GPTs) to create textual content in ChatBots and other Generative AI applications, have garnered much attention recently. However, not all data is textual. Another important use of LLMs is for image processing to address real-world problems such as: real-time object recognition, classification of images, and generation of modern art. Jeffery Payne will explore how large language models for images (also known as visual language models - VLMs) can be used for image classification, object detection, image capture generation, and...

Generative AI tools hold promise to increase human productivity.  In the world of software development, GitHub Copilot was one of the first practical applications of the use of generative AI to support developer productivity.  However, measuring software productivity is non-trivial.  For example, developer productivity gains is more than just producing code faster. If these artifacts don’t meet quality standards or themselves bring cost efficiency challenges then there may not be much overall improvement. To truly understand the benefits and challenges of AI-powered copilots requires real-...

The session covers a testing approach that utilizes a new age Test Data Management (TDM) technique which learns from production data. Machine learning analyzes the data to create a model capable of generating synthetic data with identical source data attributes. Multiple learning iterations refine the model, enhancing its accuracy with each cycle. The data model incorporates security measures like differential privacy, enabling safe movement to lower environments. Later, generative AI leverages this model to produce desired volumes of test data for various testing types, including...

Step into the future of AI with an immersive dive into the cutting-edge world of AI-Augmented GenAI and how it intercepts with Quantum technologies. This session explores the intersection of multi-threaded AI workflows and the powerful anomaly detection capabilities made possible by Quantum-inspired computing. Discover the latest trends in ModelOps, where agile deployment strategies for domain-specific generative AI models are accelerating innovation in industries ranging from healthcare to defense. Jonathon will uncover how GraphRAG (Graph Retrieval-Augmented Generation) is...

The advent of disruptive technologies, particularly in artificial intelligence, has ushered in a new era of possibilities and challenges. This talk proposes a comprehensive framework for operationalizing disruptive technologies, specifically focusing on the transformative potential of Generative Artificial Intelligence (GenAI). As organizations grapple with integrating GenAI into their operations, there is a pressing need for a structured approach that addresses technical, ethical, and organizational considerations. Mary will delve into a strategic framework designed to guide businesses in...

Traditional leadership has relied on intuition, manual processes, and fragmented feedback loops. But what if AI could fundamentally reshape how we lead—creating inherent alignment, removing hierarchical bottlenecks, and enabling decentralized decision-making? Imagine an autonomous AI companion that analyzes patterns, prioritizes coaching needs, and adapts in real time to foster self-organization, continuous learning, and leadership at every level. In this session, we’ll explore how AI-driven leadership models can replace rigid hierarchies with dynamic, data-informed decision-making,...

This session explores the transformative impact of AI on biotechnology applications, including drug discovery, genetic sequencing, and digital pathology. It delves into the modernization of testing and verification practices, highlighting the intersection of AI and cybersecurity. Attendees will gain insights into addressing challenges associated with limited training datasets in regulated environments and strategies for developing robust applications. Practical lessons learned and actionable insights will be shared to empower participants in navigating the evolving AI landscape in...

The majority of businesses today can set up a fundamental RAG pipeline that effectively handles most use cases. However, this basic setup eventually reaches its limitations in terms of functionality and accuracy, hindering further advancements. Matt Payne aims to detail the necessary pipeline components for building advanced RAG pipelines. For each component, he will explain the what, when, why, and how and provide real-world examples. Key areas of focus include leveraging tools and function calling, which enables you to create a systematic approach to using knowledge from multiple sources...

As AI systems increasingly support the social and emotional well-being of humans, the integration of human-like interactions presents both opportunities and significant risks that necessitate the use of trauma-informed principles in design. This session examines the delicate balance between creating emotionally intelligent AI and maintaining essential ethical boundaries. Join Megs to explore critical decisions in AI development: when emotional support should be provided versus redirected to human professionals, how to establish clear limitations in AI capabilities, and methods for...

Leadership in AI/ML is as much about managing complexity as it is about fostering innovation. AI leaders must navigate a landscape where data science, engineering, and operational disciplines intersect. They frequently have to bridge the gap between research and production, balancing innovation with scalability, and fostering team collaboration. AI product and platform development is non-trivial and typically requires building prototypes, adapting and evolving them for production, while maintaining agility in an ever-changing field. Join Tariq King as he shares lessons learned from leading...

Join with your peers in an engaging and highly interactive session to discuss the issues that affect you most. Using answers to the question “As a Leader, What is Keeping You Up at Night?” posed at Thursday’s evening reception, participants will form small groups to work on finding solutions to pressing leadership & management issues. Discussions will review identified issues, barriers to change, and focus on innovative strategies and practical next steps. At the end of the think tank, all feedback will be collected and posted online to encourage further collaboration.