AI & The Data Revolution

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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

  1. Organizational commitment
  2. Project team structure
  3. Top-level education and assessment customization
  4. Organizational communication
  5. 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

  1. Assignments aggregated and analyzed
  2. Executive report and presentation
  3. 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

  1. Team selection
  2. Team education
  3. Brainstorming and open exchange
  4. Scoring assessment and gap identification
  5. 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

  1. Team selection
  2. Team education
  3. Brainstorming and open exchange
  4. Scoring culture – assessment and gap identification
  5. 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

  1. Team selection
  2. Team education
  3. Brainstorming and open exchange
  4. Scoring assessment and gap identification
  5. 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

  1. Team selection
  2. Team education
  3. Brainstorming and open exchange
  4. Scoring assessment and gap identification
  5. 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

  1. Team selection
  2. Team education
  3. Brainstorming and open exchange
  4. Scoring assessment and gap identification
  5. 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

  1. Team selection
  2. Team education
  3. Brainstorming and open exchange
  4. Scoring assessment and gap identification
  5. 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

  1. Team selection
  2. Team education
  3. Brainstorming and open exchange
  4. Scoring assessment and gap identification
  5. 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

  1. ARA report creation
  2. ARA presentation preparation
  3. 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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