This master thesis gives an overview of the topic Artificial Intelligence (AI) and analyses respective effects on jobs, related employee tasks and skills. The practical empirical research examines the perceptions of AI in Saarland SMEs focusing on the actual use and their opinion of AI changing the workplace.
Qualitative interviews with SMEs in Saarland was compared to existing surveys done concerning AI. 20 interviews have been conducted in total and data from the surveys was analysed with an explaining methodology as a confirmatory research approach.
Results of the empirical research show a lack of knowledge in both AI organizational implementation and the evaluation of existing job profiles impacted by AI. A two-pillar roadmap, consisting of Technology and People, is developed by taking existing evaluation models into account and developing an own AI implementation Canvas. This thesis is a contribution to the currently rarely discussed topic of AI in Saarland.
Artificial Intelligence (AI) is not a new topic and has been researched since the 1940s. But, due to technological improvements like increased computer power at reduced costs and the occurence of Big Data, it is the most promising technology driving digitalization.
Table of Contents
1 Introduction
1.1 Artificial Intelligence – Why Now?
1.2 Objective and Research Questions
1.3 Structure and Methodological Approach
2 Drivers and Megatrends of the Fourth Industrial Revolution and Future Workplaces
3 Artificial Intelligence
3.1 Definition Approaches of Artificial Intelligence
3.2 History of Artificial Intelligence
3.3 Artificial Narrow, General and Super Intelligence
3.4 AI Capabilities and its Sub-Technologies
3.4.1 Capabilities of Artificial Intelligence
3.4.2 AI Sub-Technologies
3.5 Excursus: Machine Learning, Neural Networks and Deep Learning
3.5.1 AI, ML, NN and DL in Context
3.5.2 Machine Learning – Origins and Definition
3.5.3 Machine Learning Types
3.5.4 Neural Networks and Deep Learning
3.6 AI Capabilities – Business Application Domains
3.7 Use Cases of Artificial Intelligence
4 Artificial Intelligence and Future of Work
4.1 Employment and Technology: From History to Today
4.2 Perceptions of Artificial Intelligence
4.3 Augmentation vs. Automation
4.4 Employee Tasks
4.5 Jobs
4.5.1 Stable, new and redundant Jobs
4.5.2 Classification of Jobs – Five Ways of Stepping
4.5.3 New Jobs due to AI: The Missing Middle
4.6 Employee Skills
4.6.1 General Skill Changes
4.6.2 Skills related to AI
4.6.3 How to overcome Skill Shortages
4.7 Pros and Cons of new Technologies and Labour Market Effects
5 Empirical Research – Perceptions of SMEs in Saarland
5.1 Methodology and Method
5.2 Sampling Method
5.3 Purpose, Design and Structure of the Questionnaire
5.4 Hypotheses
5.5 Survey Results
5.5.1 General Survey and Interviewee Information
5.5.2 Sample Characteristics
5.5.3 Hypothesis 1
5.5.4 Hypothesis 2
5.5.5 Hypothesis 3
5.5.6 Hypothesis 4
5.5.7 Hypothesis 5
5.5.8 Hypothesis 6
5.6 Summary of Findings
6 Recommendations for Companies
6.1 Technology - Roadmap
6.2 People – Roadmap
7 Conclusion and Outlook
7.1 Conclusion
7.2 Outlook for Future Research
Objectives and Scope
This thesis examines the impact of Artificial Intelligence (AI) on the future workplace, specifically focusing on how tasks, jobs, and skills are evolving. It aims to bridge the gap between technical AI developments and business-related practical applications for Small and Mid-sized Enterprises (SMEs) in the Saarland region, providing a roadmap for successful implementation.
- Analysis of AI sub-technologies and business application domains.
- Investigation of AI-driven changes in employment and job profiles.
- Empirical qualitative research regarding the perceptions of SMEs in Saarland.
- Development of a two-pillar roadmap (Technology and People) for AI integration.
- Exploration of augmentation vs. automation strategies for the future workforce.
Excerpt from the Book
Augmentation vs. Automation
Generally speaking of digitalisation and its impact on workers, two main impacting effects are (see OECD 2019, pp. 43-44):
Substitution effect, i.e. Automation: Replacing workers in tasks that can be easily automated. Routine and clearly structured tasks are most affected. This results in an elimination of humans at the workplace and the codification of tasks.
Complementary effect, i.e. Augmentation: As a human, tasks can be done more efficiently due to a technology that complements work activities. The goal is to enhance human work by AI as a support.
What are current perceptions about job automation potentials? Is augmentation a more valuable strategy than automation? Several studies have been analysed and will be explained in the next paragraphs.
Large-Scale Automation
Most of the conducted research about job automation was executed by breaking down jobs into their corresponding tasks and evaluating the automation potential. In cases that most tasks can be automated, the job has been classified as “automatable”. In 2013, Frey and Osborne were some of the first researchers that analysed the U.S. and U.K. jobs by breaking them down into tasks. According to their results, 47 percent of U.S. and 35 percent of U.K. jobs could be automatable within the next ten to twenty years (see Frey & Osborne 2013, p. 254). This research has received a lot of attention, but also criticism. Therefore, other universities and consulting firms conducted similar researches. According to an OECD-sponsored paper that has been conducted by German researchers, they criticize that findings of Frey and Osborne were focusing too much on jobs instead of tasks, thus estimating that only 9 percent of jobs are automatable across 21 OECD countries (see Arntz & Gregory & Zierahn 2016, p. 4). A study that has been conducted by PwC tried to find a compromise between the 9 and 47 percent, arguing that the last studies did not consider external conditions relating to the economy, legal and regulatory aspects.
Summary of Chapters
1 Introduction: Provides the relevance of the topic, the research objectives, and the methodological structure.
2 Drivers and Megatrends of the Fourth Industrial Revolution and Future Workplaces: Outlines the historical and technological drivers shaping the modern work environment.
3 Artificial Intelligence: Offers a deep dive into AI definitions, history, capabilities, sub-technologies, and specific business application domains.
4 Artificial Intelligence and Future of Work: Explores the impact of AI on jobs, tasks, and skills, contrasting automation with augmentation.
5 Empirical Research – Perceptions of SMEs in Saarland: Details the methodology, hypothesis testing, and findings from qualitative interviews conducted with Saarland SMEs.
6 Recommendations for Companies: Proposes a two-pillar implementation roadmap focusing on Technology and People.
7 Conclusion and Outlook: Summarizes the key findings and suggests directions for future research.
Keywords
Artificial Intelligence, Future of Work, SMEs, Saarland, Automation, Augmentation, Machine Learning, Deep Learning, Digital Transformation, Job Profiles, Employee Skills, Technology Roadmap, People Roadmap, SME Implementation, Human-Machine Interaction.
Frequently Asked Questions
What is the core focus of this thesis?
The work focuses on analyzing the impact of Artificial Intelligence on the future workplace and providing a practical roadmap for SMEs to implement AI technologies.
What are the primary areas covered in the research?
Key areas include the technical foundations of AI (Machine Learning, Neural Networks), the socioeconomic impact on jobs and tasks, and the specific perceptions of small and medium-sized enterprises in the Saarland region.
What is the central research question?
The research asks how AI impacts the future workplace regarding skills and tasks, and how SMEs in Saarland perceive and prepare for these changes.
Which methodology was chosen for the empirical part?
A qualitative approach was used, utilizing semi-structured interviews with representatives of 20 SMEs in Saarland to analyze their current knowledge and perceptions of AI.
What does the main body of the work address?
It covers technical AI definitions and technologies, historical and current trends of work, and offers a specific two-pillar implementation strategy for companies.
Which keywords best describe this study?
Core keywords include Artificial Intelligence, Future of Work, SMEs, Automation, Augmentation, and implementation roadmaps.
Why are SMEs in Saarland specifically chosen for this research?
The Saarland region is a specific geographic focus to highlight local industry adoption rates, awareness levels, and barriers to AI entry among regional SMEs.
What is the practical value of the "AI Implementation Canvas" mentioned?
It serves as a tool for business leaders to systematically evaluate problems, data needs, risks, and benefits before deciding on an AI technology investment.
- Arbeit zitieren
- Aline Hamm (Autor:in), 2019, Future of Work. How Artificial Intelligence will impact the Future Workplace, München, GRIN Verlag, https://www.grin.com/document/506762
