Generative AI (GenAI) isn’t just a breakthrough — it’s redefining how enterprises innovate, compete, and create value. But realizing its full potential isn’t as simple as adopting the latest AI tool. The key to success lies in selecting the right GenAI use cases, ensuring they align with business goals, scale effectively, and mitigate risk.

Join top AI and data leaders at CDO Magazine’s Atlanta Leadership Summit on April 24, 2025, for the “GenAI Use Cases in Enterprise” breakout session, where industry experts will share real-world insights on AI adoption, strategic implementation, and lessons learned.

Panelists include:

• Eugene Agichtein, Professor of Computer Science, Emory University

• Mallory Freeman, VP, Global Enterprise Data Analytics & AI, UPS

• Srijan Kumar, Assistant Professor, Georgia Tech

• Moderator: Xiquan Cui, Senior Manager of Data Science, The Home Depot

Why Choosing the Right GenAI Use Case Matters

With AI capabilities evolving rapidly, enterprises must resist the urge to implement GenAI for the sake of innovation alone. Without a clear strategy, AI investments risk delivering little value—or worse, creating compliance and security challenges.

The most successful AI strategies focus on business value, feasibility, risk, and scalability. Identifying high-impact, practical AI applications ensures organizations maximize returns while navigating the complexities of AI adoption.

Industry-Specific GenAI Applications

GenAI is already transforming key industries by enhancing efficiency, personalization, and decision-making:

• Customer Experience: AI-powered chatbots, real-time language translation, and sentiment analysis.

• Supply Chain & Logistics: AI-driven demand forecasting, intelligent route planning, and automated risk assessments.

• Financial Services: AI-generated financial reports, fraud detection, and personalized financial advisory bots.

• Healthcare & Life Sciences: AI-assisted medical documentation, predictive analytics, and AI-driven drug discovery.

Challenges in Enterprise AI Adoption

Despite its potential, scaling GenAI across the enterprise presents significant challenges, including:

• Data silos and quality issues that impact AI model performance.

• Workforce readiness and AI integration hurdles.

• Governance, ethics, and regulatory compliance concerns.

• Scaling AI beyond proof-of-concept projects to enterprise-wide deployment.

Join the Conversation: “GenAI Use Cases in Enterprise”

With so many variables at play, how can enterprises drive measurable value with GenAI?

At the CDO Magazine Atlanta Leadership Summit on April 24, 2025, industry leaders will explore practical insights into selecting, scaling, and managing GenAI use cases.

Don’t miss this opportunity to gain actionable strategies for enterprise GenAI implementation.