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Jun 19
27m 56s

EP 550: How a Transformative Data Strate...

Everyday AI
About this episode

You think using AI is your moat? Nope. 

Just using LLMs isn't enough to power your company's AI success. But do you know the real fuel? 

Having your data right is the ACTUAL key. So how do you do it? And how does your company's data strategy change with agentic AI? 

Find out from Deloitte's US Chief Data Analytics Officer, Ashish Verma.


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Website: YourEverydayAI.com
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Topics Covered in This Episode:

  1. Transformative Data Strategy for AI Success
  2. Importance of Data Strategy in AI
  3. Deloitte's Data Marketplace Approach
  4. Multi-Agent Orchestration Challenges
  5. Structured vs. Unstructured Data in AI
  6. Synthetic Data and AI Transformation
  7. Agentic AI and Data Labeling Essentials
  8. AI's Impact on Business Value Chain

Timestamps:
00:00 "AI Success Requires Data Strategy"

05:27 Data Integration and Utilization Insights

10:31 Contextual Data Marketplace Evolution

13:06 Structuring Unstructured AI Insights

17:02 Agent Reasoning and Orchestration Insights

20:37 Data Annotation Challenges

23:39 AI's Impact on Industry Evolution

26:09 "Data Strategy: Begin with the End"

Keywords:
transformative data strategy, AI success, generative AI, non-technical people, data teams, data strategy, business leaders, companies, careers, unedited podcast, livestream, Deloitte, US chief data and analytics officer, data analytics, GenAI, data experiments, third-party data, synthetic data, data marketplace, data concierge, chief data officer, compute environment, deterministic, probabilistic, AI transformation, digital transformation, data minder, CFO, CMO, public domain data, business partner data, metadata, business glossary, technical catalog, agentic AI, multi-agent orchestration, agent registry, agent orchestration, open standard protocols, economic AI, digital transformation strategy, data advantages, structured data, unstructured data, hybrid data, PowerPoint, staffing optimization, resource management, query engine, relevance-ranked search, annotation, data regulation, governance, data procurement, data curation, data feeds, data platforms, information indexing, future predictions.

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