Louisville AI Week - Conference Tracks

Cross-Industry Tracks

Essential sessions for every attendee. These tracks explore AI applications and strategies that transcend industry boundaries—perfect for leaders seeking comprehensive AI knowledge.

AI Foundations & Strategy

START HERE

New to AI? This is your launchpad. Learn what AI actually is, how it creates value for organizations, and where to start your AI journey. Walk away ready to have informed conversations about AI implementation with your team.

WHO SHOULD ATTEND:

Business leaders, managers, and anyone new to AI seeking foundational knowledge

NON-TECHNICAL TRACK

AI Transformation & ROI

BUSINESS IMPACT

Learn how leading organizations are achieving measurable ROI from AI investments. Discover frameworks for successful AI transformation, change management strategies, and how to build AI-ready cultures that drive adoption.

WHO SHOULD ATTEND:

C-suite executives, transformation leaders, and strategic decision-makers

NON-TECHNICAL TRACK

AI Agents & Automation

AUTONOMOUS SYSTEMS

Explore AI agents—autonomous systems that can reason, make decisions, and complete complex tasks. Learn how organizations are deploying agents to transform workflows, enhance productivity, and unlock new revenue streams.

WHO SHOULD ATTEND:

Operations leaders, product managers, and business strategists interested in automation

NON-TECHNICAL TRACK

AI Ethics & Governance

RESPONSIBLE AI

Navigate the critical ethical challenges of AI deployment. Learn frameworks for bias detection, fairness evaluation, transparency, and accountability. Build AI systems that align with human values and organizational principles.

WHO SHOULD ATTEND:

Ethics officers, compliance leaders, risk managers, and governance professionals

NON-TECHNICAL TRACK

Industry-Specific Tracks

Deep-dive sessions tailored to your industry's unique challenges and opportunities. Learn from peers who understand your regulatory environment, customer expectations, and competitive landscape.

AI in Healthcare

PATIENT OUTCOMES

Discover how AI is revolutionizing patient care, diagnostics, drug discovery, and operational efficiency. Learn about HIPAA-compliant implementations, clinical decision support systems, and predictive analytics for better health outcomes.

WHO SHOULD ATTEND:

Healthcare executives, clinical leaders, health IT professionals, and medical innovators

AI in Financial Services

RISK & OPPORTUNITY

Explore AI applications in fraud detection, risk management, algorithmic trading, and customer service. Learn how banks and fintech companies are leveraging AI while maintaining regulatory compliance and security.

WHO SHOULD ATTEND:

Banking executives, fintech leaders, risk officers, and financial analysts

AI in Manufacturing

SMART OPERATIONS

Transform your operations with AI-powered predictive maintenance, quality control, supply chain optimization, and digital twins. Real-world case studies from manufacturers achieving measurable efficiency gains.

WHO SHOULD ATTEND:

Plant managers, operations leaders, supply chain executives, and industrial engineers

AI in Retail & E-Commerce

CUSTOMER EXPERIENCE

Learn how retailers are using AI for personalization, inventory optimization, demand forecasting, and dynamic pricing. Discover strategies to enhance customer experience and drive conversion rates.

WHO SHOULD ATTEND:

Retail executives, e-commerce leaders, merchandising managers, and CX professionals

Function-Specific Tracks

Tactical sessions designed for specific business functions. Learn how AI is transforming your role and gain practical strategies you can implement immediately.

AI for Marketing & Sales

REVENUE GROWTH

Supercharge your go-to-market strategy with AI-powered personalization, predictive lead scoring, content generation, and campaign optimization. Learn how top teams are using AI to drive pipeline and close deals faster.

WHO SHOULD ATTEND:

CMOs, sales leaders, marketing managers, and revenue operations professionals

AI for Product & Design

USER-CENTERED AI

Build better products faster with AI-assisted design, user research automation, and intelligent prototyping. Learn how product teams are embedding AI features while maintaining exceptional user experiences.

WHO SHOULD ATTEND:

Product managers, UX/UI designers, product designers, and innovation leaders

AI for HR & Talent

PEOPLE OPERATIONS

Revolutionize talent acquisition, employee engagement, and workforce planning with AI. Learn ethical approaches to resume screening, skills matching, performance prediction, and personalized learning paths.

WHO SHOULD ATTEND:

HR leaders, talent acquisition professionals, L&D managers, and people ops teams

AI for Customer Support

SERVICE EXCELLENCE

Transform customer support with AI-powered chatbots, sentiment analysis, and intelligent routing. Reduce response times, increase satisfaction scores, and empower your support team to focus on complex issues.

WHO SHOULD ATTEND:

Customer success leaders, support managers, CX directors, and service operations teams

Technical Tracks

Advanced sessions for technical practitioners. Deep dives into architecture, implementation, and optimization of AI systems. Bring your engineering background and leave with actionable technical knowledge.

LLMs & Generative AI

FOUNDATION MODELS

Master large language models, fine-tuning strategies, prompt engineering, and RAG systems. Learn to build production-grade generative AI applications with optimal performance, cost, and reliability.

WHO SHOULD ATTEND:

ML engineers, data scientists, AI researchers, and technical architects

TECHNICAL TRACK

MLOps & Production AI

SCALE & RELIABILITY

Learn best practices for deploying, monitoring, and maintaining AI systems at scale. Cover CI/CD for ML, model versioning, A/B testing, observability, and strategies for handling model drift.

WHO SHOULD ATTEND:

DevOps engineers, ML engineers, platform teams, and infrastructure architects

TECHNICAL TRACK

Computer Vision & NLP

DEEP LEARNING

Dive deep into computer vision and natural language processing techniques. From object detection and image segmentation to transformer architectures and semantic search—learn to build intelligent systems.

WHO SHOULD ATTEND:

ML engineers, computer vision specialists, NLP engineers, and research scientists

TECHNICAL TRACK

Data Engineering for AI

INFRASTRUCTURE

Build robust data pipelines and infrastructure to power AI systems. Learn about data quality, feature stores, vector databases, real-time processing, and architectures that scale from prototype to production.

WHO SHOULD ATTEND:

Data engineers, analytics engineers, data architects, and platform engineers

TECHNICAL TRACK