NVIDIA and Deloitte: AI in IT Ecosystems

TL;DR

Deloitte Consulting's Steve Brown discusses AI adoption in Enterprises, focusing on cloud-based tech, team building, infrastructure, and natural language processing.

Transcript

foreign we're here today at Gartner iocs 2022 and I'm joined by Steve Brown from Deloitte Consulting welcome Steve thanks Charlie hi everyone I'm Steve Brown I'm a managing director in our Ai and data operations practice at Deloitte and I run our managed Services across all of the Nvidia platforms yeah and you know Steve we've been working together... Read More

Key Insights

• 😶‍🌫️ Clients start AI adoption with cloud-based technologies before moving to on-premises solutions for scalability.
• 👨‍💼 Focus on driving business growth, efficiency, and communication internally through AI.
• 😵 Building cross-functional teams, or pods, with diverse skills is crucial for successful AI projects.
• 😶‍🌫️ Hybrid environments, utilizing both cloud and on-premises infrastructure, are common in AI projects.
• ❓ Natural language processing is crucial for communication within enterprises and with customers.
• ❓ Clients are specializing natural language processing for industry-specific functions.
• 😶‍🌫️ Infrastructure plays a significant role in AI projects, with a transition from cloud to on-premises solutions for scalability.

Questions & Answers

Q: How do clients usually start their AI adoption journey?

Clients typically start with cloud-based technologies to test AI applications before transitioning to on-premises solutions for scalability and power.

Q: What is the importance of building cross-functional teams for AI projects?

Cross-functional teams, known as pods, are essential as they bring together diverse skills including business, technology, and data science to drive successful AI projects quickly and efficiently.

Q: How do clients utilize infrastructure for AI projects?

Clients usually begin with cloud technologies for AI projects due to its cost-effectiveness but often transition to on-premises solutions for increased power and scalability as AI models grow.

Q: How are clients leveraging natural language processing in their businesses?

Clients are integrating natural language processing for communication with customers, internal communications, and revenue growth, with a focus on specialization within specific industries and functions.

Summary & Key Takeaways

• Steve Brown discusses customers starting with cloud-based technologies for AI adoption.

• Clients focus on driving business growth, efficiency, and communication using AI internally.

• Building cross-functional teams called pods is crucial for successful AI projects.