Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying The Chief AI Officer's Handbook
  • Table Of Contents Toc
  • Feedback & Rating feedback
The Chief AI Officer's Handbook

The Chief AI Officer's Handbook

By : Jarrod Anderson
4.8 (6)
close
close
The Chief AI Officer's Handbook

The Chief AI Officer's Handbook

4.8 (6)
By: Jarrod Anderson

Overview of this book

Chief Artificial Intelligence Officers (CAIOs) are now imperative for businesses, enabling organizations to achieve strategic goals and unlock transformative opportunities through the power of AI. By building intelligent systems, training models to drive impactful decisions, and creating innovative applications, they empower organizations to thrive in an AI-driven world. Written by Jarrod Anderson, Chief AI Officer at SYRV.AI, this book bridges the gap between visionary leadership and practical execution. This handbook reimagines AI leadership for today’s fast-paced environment, leveraging predictive, deterministic, generative, and agentic AI to address complex challenges and foster innovation. It provides CAIOs with the strategies to develop transformative AI initiatives, build and lead elite teams, and adopt AI responsibly while maintaining compliance. From shaping impactful solutions to achieving measurable business outcomes, this guide offers a roadmap for making AI your organization’s competitive edge. By the end of this book, you’ll have the knowledge and tools to excel as a Chief AI Officer, driving innovation, strategic growth, and lasting success for your organization.
Table of Contents (25 chapters)
close
close
Lock Free Chapter
1
Part 1: The Role and Responsibilities of the Chief AI Officer
6
Part 2: Building and Implementing AI Systems
14
Part 3: Governance, Ethics, Security, and Compliance
19
Part 4: Empowering AI Leadership with Practical Tools and Insights

Questions

  1. What are the criteria for determining whether a project component should be managed as an artifact in AI project management?
  2. How does this chapter suggest addressing the challenge of resource allocation in AI projects?
  3. What role does data augmentation play in AI project development, according to this chapter?
  4. In the context of AI project management, what is the significance of “sprint planning”?
  5. What approach does this chapter recommend for pilot testing an AI system?
  6. How does this chapter suggest balancing technical expertise and domain knowledge in AI project teams?
  7. What strategy is proposed for ensuring continuous improvement of AI models after deployment?
  8. How does this chapter address the challenge of integrating AI technology with existing business systems?
  9. What’s the importance of feasibility assessment in the initial stages of an AI project?
  10. According to this chapter, how can organizations manage change...
Visually different images
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
The Chief AI Officer's Handbook
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon