Chief AI Officer (C.AI.O)
Professional Association

Chief AI Officer (C.AI.O) Professional AssociationChief AI Officer (C.AI.O) Professional AssociationChief AI Officer (C.AI.O) Professional Association

Chief AI Officer (C.AI.O)
Professional Association

Chief AI Officer (C.AI.O) Professional AssociationChief AI Officer (C.AI.O) Professional AssociationChief AI Officer (C.AI.O) Professional Association
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What could you achieve with an AI manager's peer group?

What could you achieve with an AI manager's peer group?What could you achieve with an AI manager's peer group?What could you achieve with an AI manager's peer group?

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What could you achieve with an AI manager's peer group?

What could you achieve with an AI manager's peer group?What could you achieve with an AI manager's peer group?What could you achieve with an AI manager's peer group?

Join Co-Elevation Network

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What is unique about the Chief AI Officer (C.AI.O) compared to Chief Innovation Officer (CIO) and Chief Information Officer (CIO)?

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IS A CHIEF DATA OFFICER ALSO A CHIEF AI OFFICER?


Organizations can use the 2 titles in a broad way to gain agility, but if clarity in the mission and focus is the priority, the use of different role names and performance objectives is the right tool. While The Data Officer is in charge of the quality and value of the data usage, the AI Officer is in charge of the quality and competitive advantage of the prediction.

  

WHAT ARE THE RESPONSIBILITIES OF AN CHIEF AI OFFICER?  


1. Manage the Value of AI

  • Generating and Proving Cognitive Solution Hypothesis For Value;
  • Lower TCO and Speed Of Prediction;
  • Increase Precision/Accuracy Of Prediction and Liability Cost of Errors;
  • Machine Learning Standards, Vendor Management, RFP Writing, and Awarding ML contracts;

2. Secure Governance

  • New Business Cognitive Models On Governance with IT/Cloud and LOB(Line Of Business);
  • Data Science/AI Talents Leadership, On-Boarding, Career Management/Path;
  • Orchestrating Cross-Divisional Collaboration with Scientists; 
  • Change Management AI.

3. AI-Driven Data Strategy

  • Vision And Strategy On Capitalizing on Company Data; 
  • Data Explorations and Sharing;
  • Generating New Data With External Data Acquisition 

4. Liabilities Oversight

  • AI Ethics, Privacy, and Legal Compliance Accountability;
  • Policy-based on Researcher Access;
  • Training path and career model for scientists.

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Prof. Giuseppe Mascarella Interviews Maurizio Sanarico


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