Build a GenAI-Ready Organization with Best Practices and Key Considerations

GenAI readiness is a bit like preparing for a wild roller coaster ride. It’s exciting, a little scary and definitely something organizations want to be ready for. Many organizations find themselves in this predicament and are eager to use GenAI. But they are unsure where to start.

One hurdle is data. GenAI models are data-hungry, and organizations need to ensure they have high-quality, diverse and ethical data to train their models. Another challenge is talent. GenAI requires a unique blend of skills, from data scientists and machine learning engineers to domain experts and ethicists.  Finding and retaining these talented individuals can be tough, especially in a competitive market.  

Then, there's the issue of infrastructure. Training and deploying GenAI models can be computationally intensive and requires significant hardware and software resources.  

Yes, GenAI readiness is a challenge. And a serious question often comes up. Is GenAI readiness a challenge worth tackling?

Maybe having the correct resources can help, and there is an opportunity for that during a Generative AI Expo 2025 session titled “Evaluating and Enhancing GenAI Readiness in Organizations,” taking place from 2:00-2:45 p.m. February 11 at the Broward County Convention Center in Fort Lauderdale, Florida. Registration is available on the Generative AI Expo agenda.

By attending this session, participants will gain valuable insights into how to accurately evaluate their organization's AI maturity level. They will learn to identify strengths, weaknesses and potential areas for improvement, such as data quality, model development and deployment.

Armed with this knowledge, attendees can develop a roadmap to enhance their AI capabilities and align them with their strategic business objectives.

The session will also look into the essential elements of building a strong AI foundation. Participants will learn how to attract and retain top AI talent, establish effective data governance practices and create a scalable AI infrastructure.