AI & The Data Revolution
AI & The Data Revolution: How Teams can Harness Disruption to Conquer Turmoil, by Laura B. Madsen
In an era where data is hailed as the new oil and AI as the engine driving innovation, navigating the disruptive landscape of technology can be daunting for data leaders. AI & The Data Revolution, a groundbreaking book by Laura Madsen, offers pragmatic advice and strategic insights tailored for data leaders in today’s fast-paced world.
Topics
Introduction
SECTION I―The Essentials
Chapter 1: Organizational Commitment
Will your organization have the discipline to do it?
An important note for leadership
Leader and management roles
Important questions
Chapter 2: An Overview of the Assessment Process
- Organizational commitment
- Project team structure
- Top-level education and assessment customization
- Organizational communication
- Questionnaires and worksheets completed
Business goals and initiatives
Leadership assessment
Culture assessment
Operations and structure
Industry and market assessment
People assessment
Data assessment
AI technology assessment
- Assignments aggregated and analyzed
- Executive report and presentation
- Remediation and projects start
The six foundations for AI success
Business knowledge
Data knowledge
AI and analytics knowledge
Technology stack
Culture
People
Chapter homework
Section II―The Assessment
Chapter 3: Business Goals and Initiatives
Problems/opportunities/business case strategy
Chapter homework
Projects
Plant nursery improves revenue and gains customers
Chapter homework
Chapter 4: Leadership Assessment
Why leadership is important to AI project success
Organizational alignment
Leadership assessment for your organization
- Team selection
- Team education
- Brainstorming and open exchange
- Scoring assessment and gap identification
- Share findings with oversight committee for aggregation
Questions for discussion
Communication
Independence and trust
Trust and positive relations
Willingness to reward the learning experience
How do you handle failure and setbacks?
Alignment and collaboration
Commitment
Scoring assessment and gap identification
Identification of strengths and weakness / potential failure points
Chapter 5: Culture Assessment
Why culture is important to AI project success
Foundations of the new AI and analytics culture
Culture’s role in AI projects
Culture lessons from the AI front
Target business problems
Before the AI solution
Potential of an AI solution
Cultural strengths that led to project deliverable success
Culture assessment for your organization
- Team selection
- Team education
- Brainstorming and open exchange
- Scoring culture – assessment and gap identification
- Share findings with oversight committee for aggregation
Questions for discussion
Flexibility / adaptability and ability to change
Community, team strength, and innovation
Loyalty, commitment, and risk taking
Learning, improvement, and innovation
Scoring culture – assessment and gap identification
Identification of strengths and weakness / potential failure points
Chapter 6: Operations and Structure
Why operations and structure are important to AI project success
AI projects for human-in-the-loop operations
AI projects for human-out-of-the-loop operations
Structure versus culture
Operations and structure assessment for your organization
- Team selection
- Team education
- Brainstorming and open exchange
- Scoring assessment and gap identification
- Share findings with oversight committee for aggregation
Questions for discussion
Access to people across functions, roles, and hierarchy
Repetitive environment or creative environment?
Machine-based work or human-based work?
Novel environment or conventional environment?
Scoring operations and organizational structure – assessment and gap identification
Identification of strengths and weakness / potential failure points
Chapter 7: Industry and Market Assessment
Why industry and market are important to AI project success
Industry affects regulation, compliance, and more
Industry and market affect AI projects
Industry and market assessment for your organization
- Team selection
- Team education
- Brainstorming and open exchange
- Scoring assessment and gap identification
- Share findings with oversight committee for aggregation
Questions for discussion
Industry standards and processes
Industry and market education and innovation
Ability to respond to outside forces
Scoring industry and market – assessment and gap identification
Identification of strengths and weakness / potential failure points
Chapter 8: People Assessment
Why people are important to AI project success
The importance of domain knowledge
Community of practices strengthen data and AI literacy
True benefits of diversity
People assessment for your organization
- Team selection
- Team education
- Brainstorming and open exchange
- Scoring assessment and gap identification
- Share findings with oversight committee for aggregation
Questions for discussion
Skills and knowledge
Aptitude / willingness to learn
Open mindedness
Emotional intelligence
Desire to make positive changes
Drive, tenacity, and willingness to succeed
Team attitude
Scoring people – assessment and gap identification
Identification of strengths and weakness / potential failure points
Chapter 9: Data Assessment
Why data is important to AI project success
Data for AI projects
Types of data
Locations of data
Access to useful data
Customer service
Data assessment for your organization
- Team selection
- Team education
- Brainstorming and open exchange
- Scoring assessment and gap identification
- Share findings with oversight committee for aggregation
Questions for discussion
Data as a strategic asset
Investment made in data technology
Investment made on human support of data
Data quality and consistency
Data availability to personnel
Data security, governance, and compliance
Scoring data – assessment and gap identification
Identification of strengths and weakness / potential failure points
Chapter 10: AI Technology Assessment
Why an AI technology assessment is important to AI project success
The importance of partner relationships
Buying a packaged analytics or mobile app solution is an AI project
Call center optimization
AI technology assessment for your organization
- Team selection
- Team education
- Brainstorming and open exchange
- Scoring assessment and gap identification
- Share findings with oversight committee for aggregation
Questions for discussion
AI technology as a strategic asset
Investment made in AI technology
Investment made on human support of AI technology
AI tool availability to personnel
Scoring AI technology – assessment and gap identification
Identification of strengths and weakness / potential failure points
SECTION III―Project Selection, Remediation, and Kickoff
Chapter 11: Assignments Aggregated and Analyzed
Example aggregation of mapping tools
Strengths and weakness / potential failure points
Chapter 12: Executive Report and Presentation
Report and presentation team
- ARA report creation
- ARA presentation preparation
- ARA presentation meeting
Chapter 13: Remediation and Projects Start
Next steps
Three major steps with recommendations
Future state
Chapter 14: Parting Thoughts
As digital transformation revolutionizes industries across the globe, businesses are increasingly turning to data-driven decision-making and AI-powered solutions to gain a competitive edge. However, with this rapid evolution comes many challenges and complexities that demand a fresh perspective and actionable strategies.
AI & The Data Revolution serves as a beacon of guidance amidst this turbulence, providing data leaders with a comprehensive roadmap to effectively harness the power of AI while mitigating risks and maximizing opportunities. Drawing upon Madsen’s years of experience in the field, this book offers a blend of theoretical frameworks and real-world case studies, equipping readers with the knowledge and tools needed to thrive in the age of AI disruption.
Key themes explored include:
- Understanding the fundamentals of AI and its implications for data leadership.
- Navigating the ethical and regulatory landscape surrounding AI and data privacy.
- Creating a sustainable model for technology disruption in your organization.
- Addressing the technical debt that will hold back innovation.
- Creating an AI framework with dynamic innovation in mind.
- Step-by-step guide on how to get started.
Unlike traditional textbooks or theoretical treatises, AI & The Data Revolution is designed to be a practical guidebook for data leaders, offering actionable insights and best practices that can be implemented immediately. Whether you’re a seasoned executive leading a data-driven organization or a newcomer looking to navigate the complexities of AI, this book is an indispensable resource for anyone seeking to unlock the full potential of their data assets.
About Laura
Laura Madsen is a global data strategist, keynote speaker, and author of four industry books. She advises data leaders in healthcare, government, manufacturing, and tech. Laura has spoken at hundreds of conferences and events, inspiring organizations and individuals alike with her iconoclastic disrupter mentality. Laura is a co-founder and partner in a Minneapolis-based consulting firm, Moxy Analytics, to converge two of her biggest passions: helping companies define and execute successful data strategies and radically challenging the status quo.
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