Impact of Generative AI

Productivity, Creativity, and the Future of Work
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Content

Productivity Effects

Examining the impact of generative AI on professional tasks

Value Creation

Understanding how generative AI creates and destroys value

Job Landscape

Exploring the transformation of work roles and emerging skills

Examples

Productivity Effects in Writing Tasks

Study

  • A study by Noy and Zhang (2023) provides experimental evidence on the effects of ChatGPT on mid-level professional writing tasks [1].

Experimental Design

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flowchart LR
    A[444<br>College<br>-educated<br>Professionals] --> B[Task 1:<br>Occupation<br>-specific<br>Writing]
    B --> C{Random<br>Assignment}
    C -->|50%| D[Task 2:<br>Without ChatGPT]
    C -->|50%| E[Task 2:<br>With ChatGPT]
    
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Experimental Design

  • 444 college-educated professionals
  • Two occupation-specific writing tasks
  • Random assignment: ChatGPT access for second task
  • Evaluation by experienced professionals (blinded)

The study provides valuable insights into the immediate effects of generative AI on professional writing tasks.

Key Results

The treatment group showed significant improvements in both time efficiency and output quality when using ChatGPT.

Implications and Limitations

  • Significant boost in productivity with ChatGPT access
  • Lower-ability workers experienced increases in grades and decreases in time spent
  • Higher-ability workers maintained grades while reducing time spent
  • ChatGPT primarily substituted for worker effort

While the study reveals promising productivity gains, it’s important to consider its limitations, such as the short-term nature of the tasks and potential variations across occupations and skill levels.

Value Creation and Destruction

Scientific experiment conducted by Boston Consulting Group (BCG) in collaboration with different scholars [2].

Experiment Design

  • 758 junior consultants

  • Two sets of tasks: creative product innovation / business problem solving

  • Treatment group: Used GPT-4

  • Control group: No GPT-4 use

  • Blinded grading process

Key Findings

Generative AI shows significant performance boosts in creative tasks but may hinder performance in complex problem-solving tasks.

Implications

  1. Develop a “generative AI lab” for continuous experimentation
  2. Regularly reassess the collaboration model between humans and AI
  3. Be prepared for counterintuitive or uncomfortable findings
  4. Revise mindsets and approaches to work

Success in the age of AI depends on an organization’s ability to learn and change faster than ever before.

State of AI Adoption

Study

  • In May 2024, McKinsey released a comprehensive report on the state of AI adoption and its impact on businesses worldwide [3].

Survey Methodology

Aspect Details
Time Period February 22 to March 5, 2024
Participants 1,363 respondents
Scope Full range of regions and industries; various company sizes; diverse functional specialties

Key Findings

Result

  • AI adoption has increased dramatically, with 72% of respondents reporting AI use in at least one business function, up from 55% in 2023.

Business Functions Leveraging Gen AI

  1. Marketing and sales (34% adoption)
  2. Product and/or service development (23% adoption)
  3. IT (17% adoption)

These areas align with previous research indicating where gen AI could generate the most value.

Risk Awareness and Mitigation

  • Inaccuracy is the most recognized and experienced risk (63% consider it relevant)
  • Intellectual property infringement and cybersecurity are significant concerns
  • 44% of respondents report experiencing at least one negative consequence from gen AI use

Organizations need to be aware of and mitigate risks associated with gen AI use.

Job Landscape

Transformation of Work Roles

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flowchart LR
    subgraph SKILLS["Skills"]
        S["Enable us to<br>carry out tasks"]
    end
    subgraph TASKS["Tasks"]
        T["Activities performed to<br>achieve work outcomes"]
    end
    subgraph WORK["Work"]
        W["The outcome<br>created"]
    end
    SKILLS --> TASKS
    TASKS --> WORK

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    class SKILLS,TASKS,WORK title;
    linkStyle default stroke:#000000,stroke-width:1px;

Skills, Tasks, and Work Flow

Generative AI is affecting the skills and tasks which influence work outcomes, necessitating a reevaluation of how we approach work and skill development.

Evolution of Job Roles

  1. Content Creators → AI Prompt Engineers and Content Curators
  2. Software Developers → AI-Assisted Code Optimizers
  3. Data Analysts → AI Strategy Orchestrators
  4. Customer Service Representatives → AI-Human Interaction Specialists

The World Economic Forum predicts AI will create 97 million new jobs by 2025 while displacing 85 million jobs.

Emerging Skills for an AI-Enhanced Workplace

  1. AI Literacy
  2. Ethical AI Usage
  3. Human-AI Collaboration
  4. Complex Problem Solving
  5. Emotional Intelligence

Professionals across industries need to develop new skills to thrive in an AI-enhanced workplace.

Reskilling and Upskilling Initiatives

  • Amazon’s $700 million investment in upskilling 100,000 employees in AI and machine learning
  • Google’s AI education initiatives for professionals across various fields
  • World Economic Forum’s “Reskilling Revolution” initiative

Organizations and educational institutions are investing heavily in reskilling and upskilling programs to prepare the workforce for an AI-driven future.

Summary

Productivity Boost

Generative AI significantly enhances productivity in creative tasks but may hinder performance in complex problem-solving

Rapid Adoption

AI adoption has increased dramatically, with 72% of organizations using AI in at least one business function

Job Transformation

Generative AI is reshaping job roles and required skills, necessitating continuous learning and adaptation

References

  1. Noy, S., & Zhang, J. (2023). “Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence.”
  2. Boston Consulting Group (2023). “How People Can Create—and Destroy—Value with Generative AI.”
  3. McKinsey & Company. (2024). “The state of AI in early 2024: Gen AI adoption spikes and starts to generate value.”
  4. Chui, M., et al. (2023). “The economic potential of generative AI: The next productivity frontier. McKinsey Global Institute.”
  5. Deloitte (2023). “Generative AI and the Future of Work. Preparing your organization for the boundless potential of AI in the workplace and its impact on jobs.”
  6. World Economic Forum. (2020). “The Future of Jobs Report 2020.”
  7. Amazon. (2019). “Amazon Pledges to Upskill 100,000 U.S. Employees for In-Demand Jobs by 2025.”
  8. Google. (2023). “Grow with Google.”
  9. World Economic Forum. (2020). “The Reskilling Revolution: Better Skills, Better Jobs, Better Education for a Billion People by 2030.”

Jan Kirenz