Dayton AI Day 2026 Call For Presentations

Submit by: April 15, 2026

Speak at Dayton AI Day

Dayton AI Day
The Future, Applied.
Dayton AI Day is about moving AI from concept to capability. We bring together leaders and practitioners who are turning emerging AI ideas into real-world results. This is not speculation or surface-level demos. It is practical insight on how AI is being implemented today, what is coming next, and how organizations can apply it responsibly and at scale. Join the conversation shaping how the future of AI actually shows up in work, decisions, and outcomes.

Date: August 26. 2026
Location: Sinclair Conference Center, Dayton, OH

Possible topics:
1. Agentic & Generative AI
Focus: Building, deploying, and managing AI agents and generative systems.

Designing and Deploying Agentic AI in the Enterprise
From problem statement to production agent.
When to Use Machine Learning vs. Generative AI vs. Agents
Decision frameworks for solution selection.
Building AI Agents that Integrate with Existing Business Processes
Workflow mapping and orchestration.

2. Business AI Strategy & Implementation
Focus: Organizational design, governance, collaboration, and enterprise rollout.

Organizing AI Inside the Enterprise: IT, Finance, or Independent Function?
Governance models and operating structures.
Developing an Enterprise AI Strategy
From experimentation to formal roadmap.
Business–IT Collaboration for AI Initiatives
Structuring problem discovery before discussing technology.
AI Implementation Methodology: From Problem Statement to Deployment
Structured engagement models for leaders and technologists.

3. AI for Non-Technical Professionals
Focus: Practical, accessible AI usage for business users and leaders.

AI for Non-Technical Leaders
Practical applications without coding.
Everyday AI for Small Business & Vendors
Real-world productivity gains without development resources.
How to Safely Use AI Without Being a Technologist
Risk awareness, data protection, and safe experimentation.

4. Technical Deep Dive & Emerging Infrastructure
Focus: Advanced architecture, development, and AI engineering.

AI Infrastructure: Edge AI, Unified AI Servers & Emerging Hardware
Case example: Cisco Unified Edge AI server.
AI-Assisted Software Development
Impacts on coding, documentation, and developer workflows.
Training Data Strategy & Model Performance Optimization
Avoiding common performance pitfalls.

5. AI Governance, Risk & Ethics
Focus: Bias, hallucinations, compliance, oversight, and policy design.

AI Governance in Practice
Structuring oversight across generative and ML initiatives.
Understanding and Mitigating Bias & Hallucinations
Root causes and remediation strategies.
State, National & Global AI Policy Landscape
Regulatory direction and enterprise impact.

6. AI by Functional Area (Applied Use Cases)
Focus: Function-specific adoption (HR, Marketing, Finance, IT, etc.).

AI in Finance: Forecasting, Automation & Data Strategy
Including Excel + AI integrations.
AI in HR & Talent Operations
Productivity tools, screening, workforce transformation.
AI in Marketing & Customer Experience
Generative content, personalization, automation.

7. AI & Cybersecurity
Focus: Defensive, offensive, and operational implications.

AI and Cybersecurity: Defensive Innovation & New Risks
How AI is reshaping cyber operations.