Agenda

Plan your conference experience with ease. Explore the sessions and tracks at Ai4 2025. Stay tuned for the detailed agenda, which includes speaker session times, and valuable insights.

Monday, August 11

12:00 PMRegistration Opens

1:30 PMOpening Keynote

2:30 PMTrack Sessions

4:00 PMIndustry Meetups

5:00 PMKickoff Reception Begins

Tuesday, August 12

7:00 AMDoors Open & Breakfast

8:30 AMKeynote Sessions Begin

10:00 AMTrack Sessions Begin

12:30 PMLunch & Exhibit Hall Opens

5:00 PMExhibit Hall Reception

Wednesday, August 13

7:15 AMDoors Open & Breakfast

8:30 AMKeynote Sessions Begin

10:00 AMTrack Sessions Begin

12:30 PMLunch & Exhibit Hall Opens

4:00 PMNetworking & Reception

9:00 PMAi4 Official Afterparty Begins

Official Kickoff Reception

We’re hosting a special kickoff reception at 5pm on Monday, August 11 to kick things off!

Main Stage Keynotes

We’re proud to welcome real estate innovators from the industry’s top companies. Don’t miss these keynote sessions on the mornings of August 12th and 13th!

Exhibit Hall

Explore over 250 cutting-edge artificial intelligence solutions at your fingertips.

Tracks

Discover the latest trends, advancements, and best practices shaping the future of AI as industry experts, government organizations, disruptive startups, investors, research labs take the stage.

AI Transformation

Discover how executives at top organizations think about building and scaling AI across their organizations for business success. Click to expand and read more…

In this track, we will dive into AI agents—systems that can autonomously perform complex tasks and exhibit reasoning capabilities. Learn how these agentic systems are being leveraged by leading organizations to drive efficiency, enhance decision-making, and unlock new business opportunities. We will explore the key components of AI agents, their potential to reshape industries, and how they can be integrated into your business strategies. You’ll also gain insights into the challenges and limitations of these systems, as well as their future trajectory. This track will equip you with the knowledge to evaluate and implement AI agents within your organization.

Who should attend: This track is a NON-TECHNICAL: Business leaders interested in AI Agents should attend. This track does NOT require engineering backgrounds. 

Topics Include:

  • Introduction to AI Agents: What Are They?
  • Key Components of AI Agents: Reasoning, Autonomy, and Task Execution
  • Case Studies: AI Agents in Action
  • AI Agents for Process Automation and Efficiency
  • Ethical Considerations and Risks in AI Agents
  • The Future of AI Agents in Business

In this track, we will cover the critical components required to build and scale AI infrastructure, including both the hardware and software tools necessary for success. Learn how to architect systems that support AI initiatives at scale, ensuring they are flexible, efficient, and capable of handling growing data volumes and computational demands. We will dive into cloud computing, AI platforms, and the digital ecosystems that enable organizations to effectively leverage compute power and deploy AI solutions. This track will give you the knowledge to develop scalable AI infrastructure and utilize cutting-edge software tools to support long-term innovation.

Who should attend: This track is a NON-TECHNICAL: Business leaders interested in AI infrastructure should attend.  This track does NOT require engineering backgrounds. 

Topics Include:

  • Architecting Scalable AI Systems
  • Cloud Computing vs. On-Premise AI Infrastructure
  • AI Software Tools and Platforms for Scalability
  • Managing Computational Resources for AI
  • Handling Big Data for AI Applications
  • Building Digital Ecosystems to Support AI
  • Future-Proofing AI Infrastructure
  • Best Practices for AI Infrastructure and Digital Management

This track focuses on how to measure the return on investment (ROI) from AI initiatives and ensure continuous improvement in AI-driven projects. Learn how to set clear objectives, track key performance indicators (KPIs), and quantify the financial and operational benefits of AI implementations. We will also explore strategies for maintaining and optimizing AI systems over time, including methods for ongoing training, performance tuning, and adapting AI solutions to changing business needs. This track will equip you with the tools to evaluate AI success and foster a culture of continuous improvement.

Who should attend: This track is a NON-TECHNICAL: Business leaders, project managers, and decision-makers involved in AI projects who want to understand and maximize ROI should attend.

Topics Include:

  • Measuring AI ROI: Key Metrics and KPIs
  • Setting AI Objectives Aligned with Business Goals
  • Quantifying Operational and Financial Benefits of AI
  • Strategies for AI System Optimization and Tuning
  • Continuous Improvement in AI Implementations
  • Adapting AI Solutions to Evolving Business Needs
  • Best Practices for Ongoing AI Performance Monitoring

This track will focus on developing a strong data strategy that empowers organizations to unlock the full potential of AI. Learn how to align data collection, governance, and usage with your business goals to maximize the value of your data assets. We will cover key frameworks for building a data-driven culture, strategies for managing data at scale, and how to ensure data quality and compliance. This track will leave you with actionable insights on how to turn data into a strategic asset that fuels innovation and growth.

Who should attend: This track is a NON-TECHNICAL: Aspiring and current business leaders interested in how to effectively find business value in their data should attend.  This track does NOT require engineering backgrounds. 

Topics Include:

  • Building a Data-Driven Organization
  • Aligning Data Strategy with Business Goals
  • Data Governance and Compliance
  • Managing Data at Scale
  • Ensuring Data Quality for AI Initiatives
  • Turning Data into a Strategic Asset
  • Use Cases – Simple and Complex – For Your Data
  • Databases & Techniques for Making Use of Data

This track will delve into how AI is revolutionizing back-office operations, from finance to HR. Learn how organizations are using AI tools to automate repetitive tasks, improve decision-making, and enhance operational efficiency in back-office functions. We will cover real-world examples of AI-driven solutions, strategies for selecting the right tools, and the impact these tools can have on reducing costs and increasing productivity. This track will equip you with the knowledge to streamline back-office functions and create more efficient workflows.

Who should attend: This track is a NON-TECHNICAL: Business leaders interested in enhancing and automating back office operations should attend.  This track does NOT require engineering backgrounds. 

Topics Include:

  • Automating Finance and Accounting with AI
  • AI-Driven HR Tools: Recruitment, Onboarding, and Employee Management
  • Case Studies: AI Solutions for Back Office Operations
  • Cost Reduction and Efficiency Gains from AI
  • Best Practices for Implementing Back Office AI Tools

This track will lay the groundwork for understanding and developing a successful Generative AI strategy. Learn how to identify opportunities for generative AI within your organization, set the right objectives, and build a foundation for long-term success. We’ll discuss critical considerations, such as aligning AI initiatives with business goals, evaluating the technology landscape, AI risk management, and building the internal capacity needed to deploy AI solutions. The track will also address instrumental generative AI technologies such as LLMs, voice and image generation, and critical software tools and platforms. This session will ensure you are equipped with the knowledge to start your Generative AI journey with confidence.

Who should attend: This track is a NON-TECHNICAL: Business leaders, strategists, and decision-makers looking to establish a foundational Generative AI strategy should attend.

Topics Include:

  • Understanding Generative AI: Opportunities and Challenges
  • Setting AI Objectives Aligned with Business Strategy
  • Evaluating the Generative AI Technology Landscape
  • Building Organizational Capacity for Generative AI
  • Risk Management and Ethical Considerations
  • Best Practices for Laying a Strong AI Foundation
  • LLMs
  • Image and Video Generative AI
  • Multimodal AI
  • Generative AI Platforms and Tools
  • Prompt Engineering

This track will guide you through the process of developing a Proof of Concept (POC) for Generative AI and tailoring it to meet your organization’s needs. Learn how to design and build a successful POC, test its functionality, and ensure it aligns with your business goals. We will also cover the customization of AI models such as LLMs to suit your industry or organization’s unique requirements. By the end of this track, you’ll be prepared to develop, test, and refine generative AI solutions that deliver tangible results.

Who should attend: This track is a NON-TECHNICAL: Business leaders interested in Generative AI strategy and use cases should attend.

Topics Include:

  • Designing a Generative AI Proof of Concept (POC)
  • Customizing AI Models for Your Industry or Organization
  • Testing and Validating AI POC Performance
  • Iterative Development: Refining AI Solutions
  • Addressing Common POC Challenges
  • Best Practices for Generative AI POC Success
  • LLMs
  • Image and Video Generative AI
  • Multimodal AI
  • Generative AI Platforms and Tools
  • Fine-Tuning and Customization
  • Prompt Engineering

This track focuses on transitioning from a successful Proof of Concept (POC) to full-scale deployment of Generative AI solutions. Learn how to manage the complexities of scaling AI initiatives, including integrating them into existing systems, managing data flows, and ensuring performance consistency across multiple environments. We will also discuss how to maintain agility and adaptability as your AI solutions grow in scale. This track will prepare you to navigate the critical stages of deployment and scaling with confidence.

Who should attend: This track is a NON-TECHNICAL: Business leaders interested in Generative AI strategy and use cases should attend.

Topics Include:

  • Transitioning from POC to Full-Scale AI Deployment
  • Integrating Generative AI into Existing Infrastructure
  • Managing Data and Compute Requirements at Scale
  • Ensuring Performance Consistency Across Environments
  • Overcoming Scalability Challenges
  • Best Practices for AI System Monitoring and Maintenance
  • LLMs
  • Image and Video Generative AI
  • Multimodal AI
  • Generative AI Platforms and Tools
  • Prompt Engineering

In this track, we will examine real-world applications of Generative AI and explore use cases where the technology is being implemented successfully across various industries. Learn from detailed case studies on how leading companies are using Generative AI such as LLMs and multimodal tools to drive innovation, enhance efficiency, and create new business opportunities. This track will provide a clear understanding of how to apply generative AI in your organization and offer practical insights into what success looks like.

Who should attend: This track is NON-TECHNICAL: Business leaders, strategists, and AI enthusiasts who want to understand real-world applications of Generative AI should attend.

Topics Include:

  • Case Studies: Generative AI in Action
  • Industry-Specific Applications of Generative AI
  • Key Success Factors for Generative AI Deployments
  • Generative AI for Process Automation and Efficiency
  • Leveraging Generative AI for ROI
  • Measuring the Impact of Generative AI on Business Outcomes
  • LLMs
  • Image and Video Generative AI
  • Multimodal AI
  • Generative AI Platforms and Tools
  • Fine-Tuning and Customization
  • Prompt Engineering

In this track, we will explore AI-driven productivity tools that are transforming the workplace. Learn how to leverage automation, AI agents, and collaborative platforms to streamline workflows, reduce manual tasks, and increase efficiency across your organization. We will discuss real-world applications of these tools, how to choose the right ones for your business, and best practices for integrating them seamlessly into your existing systems. This track will provide you with actionable strategies to optimize your team’s productivity and enhance overall business performance.

Who should attend: This track is a NON-TECHNICAL: Business leaders interested in AI enhanced productivity should attend.  This track does NOT require engineering backgrounds. 

Topics Include:

  • Coding Assistants 
  • LLMs 
  • Copywriting
  • Research and Information Retrieval 
  • Intelligent Analytics Tools
  • AI-Powered Automation for Workplace Efficiency
  • Collaborative AI Tools for Teams
  • Choosing the Right Productivity Tools for Your Business
  • Case Studies: AI Productivity Tools in Action
  • Streamlining Workflows with AI Agents
  • Best Practices for Tool Integration and Adoption

In this track, we will explore Retrieval-Augmented Generation (RAG), a powerful technique that combines large language models (LLMs) with proprietary data to produce highly relevant, context-specific insights. Learn how to leverage your organization’s unique data to enhance AI outputs and create more tailored solutions. We will cover how RAG works, its potential applications across industries, and best practices for incorporating proprietary data into AI systems. This track will provide you with the knowledge needed to unlock value from your internal data and improve decision-making processes.

Who should attend: This track is NON-TECHNICAL: Business leaders and data strategists interested in utilizing proprietary data through AI should attend. No engineering background is required.

Topics Include:

  • What Is Retrieval-Augmented Generation (RAG)?
  • Leveraging Proprietary Data in AI Models
  • Enhancing LLM Outputs with Internal Data
  • Use Cases: RAG in Action Across Industries
  • Data Privacy and Security Considerations
  • Best Practices for Implementing RAG in Your Organization
  • Alternative Approaches to Leverage Proprietary Data 
  • RAG vs Fine Tuning vs Prompt Engineering
  • Database Strategies & Techniques for Aggregating Your Unique Data
  • Vector Databases

Industry Tracks

Our industry tracks include topics & use cases specific to your industry. No technical expertise required. These tracks were designed for our executive-level attendees holding non-technical roles. Click to expand and read more…

This track will focus on how AI is revolutionizing education, from personalized learning experiences to enhancing operational efficiency for educational institutions. Learn how AI is being used to improve student outcomes, streamline administrative tasks, and foster innovation. This track will give education executives the tools to incorporate AI into their institutions and enhance learning experiences.

Who should attend: This track is NON-TECHNICAL: Education executives, administrators, professors and teachers should attend.

Topics Include:

  • AI for Personalized Learning and Student Success
  • Streamlining Administrative Processes with AI
  • AI in Curriculum Development and Assessment
  • Enhancing Engagement with AI-Powered Tools
  • AI for Predicting and Improving Student Retention
  • Preventing Cheating
  • Future Trends in AI for Education

This track explores how AI is transforming the entertainment industry, from content creation and distribution to personalized experiences and audience engagement. Learn how top media companies are leveraging AI to streamline production, enhance creativity, and improve audience targeting. This track will help entertainment executives understand the impact of AI on their industry and how to capitalize on the latest trends and technologies.

Who should attend: This track is NON-TECHNICAL: Entertainment executives, media professionals, and decision-makers in the entertainment industry should attend.

Topics Include:

  • AI-Driven Content Creation and Personalization
  • Optimizing Audience Engagement with AI
  • AI for Video, Film, and Music Production
  • AI in Content Distribution and Rights Management
  • Predictive Analytics for Media Success
  • Future Trends in AI for Entertainment

This track will focus on how AI is reshaping banking services, from customer experience to risk management and regulatory compliance. Learn how leading banks are using AI to drive innovation, enhance security, and optimize operations. We will cover key AI applications in banking, from fraud detection to personalized financial services, to help executives stay ahead in the digital age.

Who should attend: This track is NON-TECHNICAL: Banking executives, strategists, and decision-makers interested in AI for financial services should attend.

Topics Include:

  • AI for Fraud Detection and Risk Management
  • Personalizing Customer Experience with AI
  • AI in Regulatory Compliance and Reporting
  • Optimizing Banking Operations with AI
  • AI in Loan Underwriting and Credit Scoring
  • Future Trends in AI for Banking

This track will dive into how AI is transforming asset management by enhancing data analysis, portfolio optimization, and risk management. Learn how AI is used to gain deeper insights into market trends, improve investment strategies, and automate decision-making. This track will prepare asset management executives to harness AI to stay competitive and drive value.

Who should attend: This track is NON-TECHNICAL: Asset management executives and financial strategists should attend.

Topics Include:

  • AI for Market Trend Analysis and Forecasting
  • Portfolio Optimization with AI
  • Automating Investment Strategies with AI
  • AI-Driven Risk Management in Asset Management
  • Enhancing Customer Engagement with AI
  • Future Trends in AI for Asset Management

This track will cover the evolving role of AI in the insurance industry, focusing on how AI is transforming underwriting, claims processing, and customer service. Learn how insurers are leveraging AI to improve efficiency, reduce costs, and provide more personalized coverage. This track will give insurance executives the knowledge to implement AI solutions that drive better outcomes for their businesses and customers.

Who should attend: This track is NON-TECHNICAL: Insurance executives and decision-makers interested in AI for the insurance industry should attend.

Topics Include:

  • AI for Underwriting and Risk Assessment
  • Streamlining Claims Processing with AI
  • AI-Driven Customer Service and Personalization
  • Fraud Detection and Prevention Using AI
  • AI in Insurance Product Development
  • Future Trends in AI for Insurance

This track will explore how AI is being adopted by governments to improve public services, streamline operations, and enhance decision-making. Learn how AI can help government agencies drive efficiencies, better engage citizens, and improve security. This track will provide government leaders with insights on how to leverage AI for smarter governance and improved public outcomes.

Who should attend: This track is NON-TECHNICAL: Government executives and decision-makers involved in AI policy, operations, or public services should attend.

Topics Include:

  • AI for Public Service Optimization
  • Enhancing Security and Data Privacy with AI
  • AI for Citizen Engagement and Communication
  • AI-Driven Decision-Making and Policy Planning
  • AI for Infrastructure and Urban Development
  • Future Trends in AI for Government
  • Law Enforcement and AI

This track will examine how AI is revolutionizing healthcare delivery for care providers, from improving patient outcomes to optimizing operations. Learn how AI is being used to assist in diagnosis, personalize treatments, and streamline workflows. This track will provide healthcare executives with insights into the opportunities and challenges of AI in care delivery.

Who should attend: This track is NON-TECHNICAL: Healthcare executives and decision-makers in care should attend.

Topics Include:

  • AI for Clinical Decision Support
  • AI Enhanced Patient Experience
  • Personalized Medicine with AI
  • Optimizing Care Delivery with AI Tools
  • AI in Medical Imaging and Diagnostics
  • AI in Patient Monitoring and Telehealth
  • Medical Devices
  • Wearable Devices
  • AI driven Surgery
  • Hospital and Care Provider Automation
  • Future Trends in AI for Healthcare Providers

This track will explore how AI is advancing the life sciences and pharmaceutical industry by accelerating drug discovery, improving clinical trials, and optimizing R&D processes. Learn how AI is helping life sciences companies bring innovations to market faster while reducing costs. This track will equip life sciences and pharmaceutical industry executives with the knowledge to drive AI adoption and enhance their competitive edge.

Who should attend: This track is NON-TECHNICAL: Life sciences and pharmaceutical industry executives as well as professionals focused on R&D, clinical trials, and drug development should attend.

Topics Include:

  • AI in Drug Discovery and Development
  • Accelerating Clinical Trials with AI
  • AI in Genomics and Personalized Medicine
  • Optimizing R&D Processes with AI
  • AI for Regulatory Compliance and Risk Management
  • Future Trends in AI for Life Sciences

This track focuses on how AI is helping healthcare payers improve operational efficiency, enhance member experiences, and optimize cost management. Learn how leading insurers and payers are leveraging AI to automate claims, predict member behavior, and drive personalized care plans. This track will provide healthcare payer executives with the strategies to effectively integrate AI into their operations.

Who should attend: This track is NON-TECHNICAL: Healthcare payer executives and decision-makers should attend.

 

Topics Include:

  • AI for Claims Automation and Fraud Detection
  • Predictive Analytics for Member Behavior and Risk
  • Personalizing Member Care Plans with AI
  • AI for Cost Optimization and Efficiency
  • Improving Customer Service with AI Tools
  • Population Health
  • Future Trends in AI for Healthcare Payers

This track will cover how AI is revolutionizing manufacturing and supply chain operations by improving efficiency, reducing costs, and enabling predictive maintenance. Learn how companies are using AI to enhance production processes, optimize logistics, and improve quality control. This track will provide manufacturing and supply chain executives with the knowledge to integrate AI into their operations for long-term success.

Who should attend: This track is NON-TECHNICAL: Manufacturing and supply chain executives and decision-makers should attend.

Topics Include:

  • AI for Predictive Maintenance and Quality Control
  • Optimizing Supply Chain Operations with AI
  • AI-Driven Automation in Manufacturing
  • Enhancing Logistics with AI
  • AI for Inventory and Demand Forecasting
  • Future Trends in AI for Manufacturing and Supply Chain
  • Improved Safety with AI
  • Improving Throughput with AI

This track will explore how AI is transforming retail, consumer packaged goods (CPG), and eCommerce. Learn how companies are using AI to create personalized shopping experiences, predict consumer demand, and improve logistics. This track will help retail and eCommerce executives understand how to harness AI for business growth and competitive advantage.

Who should attend: This track is NON-TECHNICAL: Retail, CPG, and eCommerce executives and decision-makers should attend.

Topics Include:

  • AI for Personalized Customer Experiences
  • Predicting Consumer Demand with AI
  • Optimizing Inventory with AI
  • Shopping Experience and AI
  • AI Driven Pricing
  • Checkoutless Technology
  • AI-Driven Marketing and Customer Engagement
  • AI for Product Recommendations 
  • Future Trends in AI for Retail and eCommerce

This track will explore how AI is being utilized by SaaS companies to enhance product offerings, improve customer retention, and drive business growth. Learn how AI can help SaaS providers create more personalized user experiences, optimize pricing strategies, and streamline product development. This track will equip SaaS executives with the strategies needed to leverage AI for increased competitiveness and innovation.

Who should attend: This track is NON-TECHNICAL: SaaS executives, product leaders, and decision-makers should attend.

Topics Include:

  • AI for Personalizing SaaS User Experiences
  • Optimizing Product Development with AI
  • AI-Driven Pricing Strategies for SaaS
  • Enhancing Customer Retention with AI
  • AI in SaaS Product Innovation
  • Future Trends in AI for SaaS
  • SaaS company Automation via AI
  • Software Pricing in the Age of AI

Job Function Tracks

Job function tracks focus on how AI relates to certain roles in enterprise settings. The focus of these tracks are cross industry.

This track will address the critical issues of AI governance, regulation, and compliance. Learn how to navigate the evolving regulatory landscape, ensure responsible AI use, and mitigate risks associated with AI deployment. We will explore frameworks for ethical AI, data privacy concerns, and how to implement compliance strategies that align with global regulations. This track is essential for leaders who need to understand the broader legal and ethical implications of AI.

Who should attend: This track is NON-TECHNICAL: Governance, compliance officers, legal professionals, and business leaders responsible for AI regulation and policy should attend.

Topics Include:

  • Navigating AI Regulations and Compliance Requirements
  • Ethical AI Frameworks and Responsible Use
  • Data Privacy and Security in AI Deployments
  • Implementing AI Governance Structures
  • Mitigating AI Risks and Biases
  • Legality of Various Types of AI Projects
  • Future Trends in AI Regulation and Governance

This track will provide insights into how AI is transforming the roles of CAIOs, CIOs, and IT leaders. Learn how to lead successful AI initiatives, manage infrastructure for AI deployments, and drive innovation across your organization. We will cover the strategic role of IT leaders in integrating AI solutions into enterprise systems, ensuring scalability, and fostering a culture of innovation. This track will help IT executives understand the key elements of leading AI-driven transformation.

Who should attend: This track is NON-TECHNICAL: CAIOs, CIOs, and IT leaders responsible for AI strategy and digital transformation should attend.

Topics Include:

  • Leading AI Initiatives and Digital Transformation
  • Building Scalable AI Infrastructure
  • Integrating AI Solutions Across the Enterprise
  • Managing Data and IT Resources for AI
  • Fostering Innovation Through AI in IT
  • Future Trends in AI for IT Leadership

This track will explore how AI is transforming the creative process with tools that help content creators generate, enhance, and distribute their work more efficiently. Learn how AI-powered tools are being used to create visual, audio, and written content, automate editing, and optimize creative workflows. This track will help creators and executives understand how AI can accelerate and enhance the creative process across various mediums.

Who should attend: This track is NON-TECHNICAL: Content creators, creative professionals, and media executives should attend.

Topics Include:

  • AI for Content Generation: Visuals, Audio, and Text
  • Automating Content Editing and Enhancement
  • AI Generated Music 
  • AI Generated Video
  • AI-Driven Tools for Creative Optimization
  • AI in Content Distribution and Audience Targeting
  • Enhancing Creativity with AI Collaboration Tools
  • Future Trends in AI for Creator Tools

This track will explore how AI is enhancing cybersecurity by improving threat detection, automating responses, and mitigating risks. Learn how AI-powered tools are helping organizations stay ahead of cyber threats by detecting anomalies, strengthening network defenses, and reducing incident response times. This track will provide cybersecurity professionals with insights into the latest AI-driven solutions to safeguard organizational assets.

Who should attend: This track is NON-TECHNICAL: Cybersecurity professionals, IT security leaders, and executives focused on AI-enhanced security should attend.

Topics Include:

  • AI for Threat Detection and Response
  • Automating Cybersecurity with AI Tools
  • Using AI to Identify Anomalies and Insider Threats
  • AI-Driven Security for Networks and Data
  • Enhancing Incident Response with AI
  • Future Trends in AI for Cybersecurity

This track will explore how AI is transforming customer service and the overall customer experience (CX). Learn how AI can be used to automate customer interactions, enhance personalization, improve service efficiency, and retain customers. We will discuss real-world use cases and tools that can help your organization optimize CX and build lasting customer loyalty. This track will equip customer service leaders with strategies to implement AI for a more responsive and engaging customer experience.

Who should attend: This track is NON-TECHNICAL: Customer service leaders, CX professionals, and executives responsible for customer engagement should attend.

Topics Include:

  • AI-Powered Customer Service Automation
  • Enhancing Personalization in CX with AI
  • Predictive Analytics for Customer Needs
  • AI-Driven Chatbots and Virtual Assistants
  • Measuring and Improving CX with AI
  • Conversational Agents
  • Future Trends in AI for CX & Customer Service
  • Customer Retention with AI

This track will explore how AI is enhancing data analytics and business intelligence (BI) by providing deeper insights and predictive capabilities. Learn how AI tools are transforming the way organizations gather, analyze, and act on data. We will cover best practices for implementing AI in BI workflows, automating data processes, and using AI to drive more informed decision-making. This track will empower BI and analytics leaders to maximize the potential of AI in their roles.

Who should attend: This track is NON-TECHNICAL: Data analysts, BI professionals, and business leaders responsible for analytics should attend.

Topics Include:

  • AI-Enhanced Data Analytics: From Descriptive to Predictive
  • Automating Data Processes with AI
  • Leveraging AI for Real-Time Business Insights
  • AI in Data Visualization and Reporting
  • Using AI to Improve Decision-Making
  • Future Trends in AI for Data Analytics & BI

This track will focus on how AI is reshaping marketing strategies by enhancing personalization, targeting, and campaign optimization. Learn how to use AI to better understand customer behavior, optimize ad spend, and create more impactful marketing campaigns. We will cover real-world applications of AI in digital marketing, including predictive analytics, customer segmentation, and content creation. This track will provide marketing leaders with the tools they need to acquire new customers with AI.

Who should attend: This track is NON-TECHNICAL: Marketing executives, CMOs, and marketing professionals looking to leverage AI for campaign success should attend.

Topics Include:

  • AI-Driven Personalization and Customer Segmentation
  • Optimizing Ad Spend with AI Analytics
  • Using Predictive Analytics for Marketing Campaigns
  • AI for Content Creation and Creative Strategy
  • AI-Enhanced Social Media Marketing
  • Future Trends in AI for Marketing
  • Customer acquisition with AI

This track will cover how AI is influencing product management by enhancing product development, customer research, and go-to-market strategies. Learn how AI tools can help you prioritize features, personalize product experiences, and better understand customer needs. We will explore how to integrate AI into product roadmaps and measure its impact on product success. We will also examine how to build world class AI products. This track will provide product managers with the insights needed to succeed in an AI driven future.

Who should attend: This track is NON-TECHNICAL: Product managers and product leaders responsible for product strategy and development should attend.

Topics Include:

  • AI in Product Development: Prioritizing Features
  • Personalizing Product Experiences with AI
  • Using AI for Customer Research and Insights
  • AI-Enhanced Product Roadmaps
  • Building AI Products
  • Measuring AI’s Impact on Product Success
  • Future Trends in AI for Product Management

This track will focus on how AI is revolutionizing software engineering, from automating code generation to enhancing development workflows. Learn how AI tools and platforms are helping engineers improve code quality, accelerate development cycles, and optimize performance. We will cover advanced AI-driven solutions for testing, debugging, and scaling software systems, giving engineers the insights they need to stay ahead in the evolving landscape of AI-driven software development. This track will also cover the role of software engineers in complex AI and ML projects across different organizations.

Who should attend: This track is TECHNICAL: Software engineers, developers, and technical leaders involved in AI-driven software development should attend.

Topics Include:

  • AI for Automated Code Generation and Testing
  • Optimizing Software Development with AI Tools
  • AI in Debugging and Performance Optimization
  • Machine Learning in Software Engineering
  • AI-Driven DevOps and Continuous Integration
  • DevOps for AI driven software projects
  • Future Trends in AI for Software Engineering

This track will focus on how AI is transforming sales by automating lead generation, enhancing customer interactions, and improving sales forecasting. Learn how to leverage AI to identify the best prospects, personalize outreach, and close deals faster. We will explore AI-powered CRM tools, predictive sales analytics, and how AI is reshaping the future of sales strategies. This track will provide sales executives with insights into using AI to drive more revenue and improve customer relationships.

Who should attend: This track is NON-TECHNICAL: Sales executives, sales leaders, and decision-makers looking to improve sales processes with AI should attend.

Topics Include:

  • AI for Lead Generation and Qualification
  • Personalizing Sales Outreach with AI Tools
  • AI-Enhanced CRM Systems for Sales Optimization
  • Predictive Sales Analytics for Forecasting
  • Automating Sales Workflows with AI
  • Future Trends in AI for Sales

Society Tracks

These tracks explore the profound impact of artificial intelligence on societal structures, human interactions, and global challenges. The focus of these tracks are cross industry.

This track will explore the ethical challenges of AI and the need to ensure AI systems align with human values. As AI grows more powerful, questions of fairness, transparency, and accountability become more pressing. Learn how to design AI systems that are ethically sound and aligned with societal goals, from eliminating bias in algorithms to ensuring AI remains under human control. This track is crucial for leaders who are responsible for the ethical governance of AI within their organizations.

Who should attend: This track is NON-TECHNICAL: Ethics officers, policymakers, and business leaders responsible for AI governance and alignment should attend.

Topics Include:

  • Ensuring Fairness and Transparency in AI
  • Ethical AI Design: Eliminating Bias
  • AI Alignment with Human Values and Goals
  • Accountability and Responsibility in AI Systems
  • Regulatory Frameworks for AI Ethics
  • Future Trends in AI Ethics and Alignment

This track will examine the emerging parallel technologies that are evolving alongside AI, such as blockchain and quantum computing. Learn how these technologies intersect with AI to create new possibilities in fields like data security, computation, and innovation. We will discuss how blockchain can enhance AI transparency and how quantum computing could revolutionize AI’s capabilities. This track will provide insights into the cutting-edge technologies that are shaping the future alongside AI.

Who should attend: This track is NON-TECHNICAL: Business leaders, strategists, and executives interested in the intersection of AI and emerging technologies should attend.

Topics Include:

  • AI and Blockchain: Enhancing Security and Transparency
  • Quantum Computing’s Potential to Revolutionize AI
  • Emerging Technologies and Their Impact on AI
  • The Convergence of AI with Blockchain and Quantum
  • Opportunities and Challenges in Parallel Technologies
  • Future Trends in AI, Blockchain, and Quantum Computing

This track will explore the environmental impact of AI, focusing on how we can make AI more energy-efficient and sustainable. As AI systems continue to grow in power and scale, their energy consumption rises, posing risks to the environment. Learn about cutting-edge research and best practices for reducing the carbon footprint of AI, from optimizing models to using renewable energy in data centers. This track will help executives and thought leaders understand how AI can be aligned with sustainability goals to create a greener future.

Who should attend: This track is NON-TECHNICAL: Sustainability officers, AI strategists, and business leaders interested in making AI more environmentally friendly should attend.

Topics Include:

  • Reducing the Carbon Footprint of AI
  • Energy-Efficient AI Models and Algorithms
  • Leveraging Renewable Energy for AI Infrastructure
  • Sustainable Data Centers and AI Systems
  • Balancing AI Innovation with Environmental Responsibility
  • Future Trends in Green AI and Sustainability

This track will address the broad social impacts of AI, covering topics such as job displacement, inequality, and the opportunities AI creates for social good. AI has the potential to reshape entire industries, influence economies, and impact the global workforce. Learn how to harness AI for positive social change while addressing its potential risks. This track is a must for leaders looking to understand the wider societal implications of AI and how to foster an inclusive AI future.

Who should attend: This track is NON-TECHNICAL: Business leaders, policymakers, and social impact professionals who are focused on the societal implications of AI should attend.

Topics Include:

  • The Impact of AI on Jobs and the Workforce
  • Addressing Inequality in the Age of AI
  • AI for Social Good: Healthcare, Education, and Beyond
  • Mitigating the Negative Effects of AI on Society
  • AI’s Role in Shaping Global Economies
  • Future Trends in the Social Impact of AI

Summits

The Summits at Ai4 unite special interest groups through both content sessions and dedicated networking opportunities. The goal of these Summits is to help build community amongst like-minded individuals.

The world’s top VC’s and early-stage AI startup founders take the stage. Startup founders give shorter, 10 minute “pitch” presentations. This track will provide insight into the most cutting edge innovations going on in AI, as well as how leading investors in AI evaluate these transformative opportunities.

Who should attend: This track is a NON-TECHNICAL: Startup Founders, Investors, and Leaders interested in the cutting edge of AI and the industry outlook should attend. 

Topics Include:

  • Cutting Edge AI Products 
  • The AI Industry Outlook
  • Trends in the AI Startup Ecosystem
  • What VCs Look for in AI Investments
  • Scaling AI Startups: Challenges and Opportunities
  • Funding Opportunities for AI Startups
  • AI Disruption Across Industries
  • Future Trends in AI Startups and VC Investments

This technical track will bring together leading researchers and practitioners to discuss the latest advancements in AI research. Explore cutting-edge breakthroughs in AI, from novel algorithms to new approaches in machine learning, neural networks, and natural language processing. This summit is designed to facilitate deep technical discussions and collaborations, providing a platform for the AI research community to exchange ideas and push the boundaries of AI innovation. Most presenters will also have a poster exhibition!

Who should attend: This track is TECHNICAL: AI researchers, data scientists, machine learning engineers, and technical experts involved in AI research should attend.

Topics Include:

  • Breakthroughs in Machine Learning and Neural Networks
  • Advancements in Natural Language Processing (NLP)
  • New Approaches in AI Algorithms and Architectures
  • Multimodal, Ensemble and Agents
  • AI Research for Robotics and Autonomous Systems
  • Cutting Edge Research of all Types
  • Future Trends in AI Research and Development

This track will address the key policy challenges and opportunities that come with the rise of AI. As AI reshapes industries and societies, governments and policymakers are grappling with how to regulate and govern this powerful technology. Learn about the current state of AI regulation, global AI policy frameworks, and the role of policymakers in shaping the future of AI. This summit will offer insights into balancing innovation with ethical considerations, privacy concerns, and the public good.

Who should attend: This track is NON-TECHNICAL: Policymakers, business leaders, and professionals involved in AI governance and regulatory policy should attend.

Topics Include:

  • Current AI Policy and Regulatory Frameworks
  • Balancing Innovation with Ethical Governance
  • Global Perspectives on AI Regulation
  • AI and Data Privacy: Policy Considerations
  • The Role of Governments in AI Development
  • Future Trends in AI Policy and Regulation

If you are new to AI, this is the track for you! We will cover the basics – what is AI? How can AI be of use to organizations and workers? What are the critical ingredients for deriving value from AI? What are the challenges and risks associated with AI? How is the AI market shaping up and who are the major players and companies? All are welcome, and expect to leave these sessions feeling more confident for the rest of the event sessions. This track will take place in the beginning of the Ai4 2025 conference. You will leave the Ai4 2025 conference ready to educate your colleagues!

Who should attend: AI Beginners! No AI experience required!

Topics Include:

  • What is AI?
  • What is Responsible AI? 
  • Common Use Cases for AI
  • Foundational Models
  • Industry Application of AI
  • Challenges of AI Adoption

This track will focus on the importance of fostering diversity in AI development, from representation in AI teams to ensuring diverse perspectives are considered in AI applications. As AI systems increasingly influence society, it is crucial that the technology reflects the diversity of the world it serves. Learn how companies are promoting diversity in AI development, the benefits of diverse teams, and strategies to overcome the challenges of bias in AI systems. This track will inspire leaders to create more inclusive AI ecosystems that drive innovation and equity.

Who should attend: This track is NON-TECHNICAL: Business leaders, DEI professionals, and executives focused on fostering diversity within AI teams and technologies should attend.

Topics Include:

  • Promoting Diversity in AI Teams and Leadership
  • Reducing Bias in AI Systems
  • The Role of Diversity in AI Innovation
  • Strategies for Building Inclusive AI Ecosystems
  • Case Studies: Companies Leading the Way in AI Diversity
  • Future Trends in Diversity and Inclusion in AI

Technical Tracks

Our technical tracks provide a platform for researchers, engineers, and practitioners to explore cutting-edge innovations in machine learning, deep learning, natural language processing, computer vision, robotics, and more.

This track will delve into the technical aspects of AI agents—systems designed to autonomously perform complex tasks while reasoning and interacting with their environments. Learn about the latest advancements in agent architectures, multi-agent systems, and how agents can be used to solve real-world problems. We’ll cover the technical details behind building, training, and deploying intelligent agents across various use cases.

Who should attend: This track is TECHNICAL: AI engineers, data scientists, and researchers involved in the development and deployment of AI agents should attend.

Topics Include:

  • Architectures for Autonomous AI Agents
  • Multi-Agent Systems: Coordination and Communication
  • Training AI Agents: Reinforcement Learning and Beyond
  • AI Agents for Real-World Applications
  • Ethical Considerations in Autonomous Agents
  • Future Trends in AI Agents

This track will explore the technical foundations and innovations in computer vision, from image recognition and object detection to advanced visual understanding. Learn how cutting-edge algorithms and neural networks are transforming industries like healthcare, automotive, and retail. We will discuss the latest advancements in deep learning for computer vision, challenges in model accuracy, and how to optimize vision models for real-world applications.

Who should attend: This track is TECHNICAL: AI engineers, data scientists, and researchers working in computer vision should attend.

Topics Include:

  • Deep Learning for Image Recognition and Object Detection
  • Advanced Techniques in Visual Understanding
  • Optimizing Computer Vision Models for Scale
  • Applications of Computer Vision in Healthcare, Automotive, and More
  • Addressing Bias and Accuracy Challenges in Vision Models
  • Future Trends in Computer Vision
  • Deepfakes

This track will explore the latest advancements in AI model architectures, focusing on state-of-the-art techniques that are pushing the boundaries of AI performance. Learn about new neural network architectures, optimization techniques, and innovations in transfer learning. We will also cover the technical challenges of deploying cutting-edge models in production environments and optimizing them for performance at scale.

Who should attend: This track is TECHNICAL: AI researchers, data scientists, and machine learning engineers involved in model development should attend.

Topics Include:

  • Next-Generation Neural Network Architectures
  • Innovations in Transfer Learning and Meta-Learning
  • Optimizing AI Models for Performance at Scale
  • Overcoming Challenges in Model Deployment
  • Cutting-Edge Architectures for NLP, Vision, and Reinforcement Learning
  • Creative Approaches to Difficult Technical Problems
  • Ensemble Approaches
  • Future Trends in AI Model Architecture

This track will focus on the technical challenges and best practices in preparing data for AI and machine learning models. Learn how to clean, preprocess, and transform data to ensure optimal model performance. We will cover advanced techniques for feature engineering, handling imbalanced datasets, and preparing large-scale datasets for AI applications. This track will help data scientists and engineers streamline the data preparation process for more efficient modeling.

Who should attend: This track is TECHNICAL: Data engineers, data scientists, and AI professionals responsible for data preparation should attend.

Topics Include:

  • Data Cleaning and Preprocessing for AI Models
  • Feature Engineering Techniques for Model Performance
  • Handling Imbalanced Datasets in AI Applications
  • Scaling Data Prep for Large Datasets
  • Data Transformation and Encoding Methods
  • Future Trends in Data Preparation for AI

This track will cover the technical details of generative models, from large language models (LLMs) to generative adversarial networks (GANs) and small language models (SLMs). Explore the underlying algorithms, architectures, and applications of generative models across a variety of domains. We will also discuss challenges in training and deploying these models and how to fine-tune them for specific tasks.

Who should attend: This track is TECHNICAL: AI researchers, data scientists, and engineers working on generative models should attend.

Topics Include:

  • Large Language Models (LLMs): Training and Fine-Tuning
  • GANs: Adversarial Learning and Applications
  • Small Language Models (SLMs): Efficient Architectures
  • Applications of Generative Models in NLP, Vision, and More
  • Overcoming Training Challenges in Generative Models
  • Future Trends in Generative AI

This track will dive into the hardware advancements driving the next wave of AI innovation. From GPUs to custom AI chips, learn about the technologies that are enabling more powerful and efficient AI computations. We will cover the evolution of hardware for AI workloads, discuss the importance of hardware-software co-design, and examine the performance trade-offs in choosing the right hardware for your AI projects.

Who should attend:This track is TECHNICAL: Hardware engineers, system architects, and AI professionals working with advanced AI hardware should attend.

Topics Include:

  • AI Chips: Architectures and Capabilities
  • GPUs for AI: Scaling Performance
  • Hardware-Software Co-Design for AI Efficiency
  • Balancing Power, Performance, and Cost in AI Hardware
  • Custom AI Accelerators for Specific Workloads
  • Future Trends in AI Hardware

This track will focus on the technical challenges and best practices for managing machine learning (ML) operations at scale. Learn how to build and maintain ML pipelines, automate workflows, and deploy models in production environments. We will cover the latest tools and platforms for ML Ops, ensuring your team can manage the end-to-end machine learning lifecycle efficiently and reliably.

Who should attend: This track is TECHNICAL: Data engineers, ML engineers, and IT professionals involved in machine learning operations and infrastructure should attend.

Topics Include:

  • Building and Managing ML Pipelines
  • Automating ML Workflows and Deployment
  • Monitoring and Scaling ML Models in Production
  • Best Practices for Model Versioning and Experimentation
  • ML Ops Tools and Platforms
  • Future Trends in ML Ops

This track will dive into Retrieval-Augmented Generation (RAG), a cutting-edge technique that combines generative AI with retrieval systems. Learn how to build RAG models that enhance language model outputs with real-time data retrieval. We will cover the technical aspects of implementing RAG, from model training to integrating retrieval systems, and explore real-world use cases that show the value of combining retrieval with generative AI.

Who should attend: This track is TECHNICAL: Data scientists, AI engineers, and researchers working on generative AI and retrieval systems should attend.

Topics Include:

  • Retrieval-Augmented Generation: Key Concepts and Architectures
  • Integrating Retrieval Systems with Generative Models
  • Building and Training RAG Models
  • Optimizing RAG for Real-Time Data Retrieval
  • Applications of RAG in Search, Knowledge Management, and More
  • Future Trends in Retrieval-Augmented Generation

This track will focus on the technical intricacies of building and optimizing recommender systems. Learn about collaborative filtering, content-based filtering, and hybrid approaches to recommendation algorithms. We will explore how companies are deploying recommender systems to personalize user experiences and the engineering challenges involved in scaling these systems across large datasets.

Who should attend: This track is TECHNICAL: AI engineers, data scientists, and machine learning practitioners building and optimizing recommender systems should attend.

Topics Include:

  • Collaborative and Content-Based Filtering Techniques
  • Hybrid Recommender Systems: Combining Multiple Approaches
  • Scaling Recommender Systems for Large Datasets
  • Optimizing Recommendation Algorithms for Personalization
  • Evaluating Recommender System Performance
  • Future Trends in Recommender Systems

This track will cover the latest advancements in reinforcement learning (RL) and its applications across various industries. Learn how RL models are trained, the challenges in reward engineering, and the technical details of deploying RL in real-world environments. We will discuss both on-policy and off-policy RL methods, multi-agent RL, and the growing intersection of RL with deep learning.

Who should attend: This track is TECHNICAL: AI researchers, machine learning engineers, and data scientists working on or interested in reinforcement learning should attend.

Topics Include:

  • Fundamentals of Reinforcement Learning: On-Policy and Off-Policy Methods
  • Multi-Agent Reinforcement Learning
  • Reward Engineering and Policy Optimization
  • Applications of RL in Robotics, Gaming, and Operations Research
  • Combining RL with Deep Learning
  • Future Trends in Reinforcement Learning
  • Human in the Loop