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Artificial Intelligence: Progress in business and society
Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
2018 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This thesis investigates the progress of corporate implementations of Artificial Intelligence and discusses the effects that this might have on the corporate sector as well as some implications on a societal level. The analysis is based on data from surveys conducted by Accenture, Bain & Company, Capgemini Digital Transformation Institute, Deloitte, Gartner Inc., McKinsey Global Institute and MIT Sloan Management Review & Boston Consulting Group.

Over the last 3 years the adoptions of Artificial Intelligence have increased 2-3 times and the trend is expected to continue in the coming years as well, since 40-55 % of the surveyed companies are in the initial stages of AI adoption. Further, the growth rate in AI investments has been even more radical and increased 15-20 times over the last 7 years.

Companies who have implemented AI report significant benefits and companies with a proactive strategy for Artificial Intelligence report higher profit margins than their industry competitors. Further the data indicates that companies that are successful in implementing AI have better general organizational capabilities, higher data & skills readiness and more AI focus in leadership and strategic planning.

Another result in the study is that most managers in companies implementing AI expect that the technology will enable them to enter new markets and also that new competitors will enter their market. This will probably lead to increased competition and the results from other technology transitions indicate that this might force more companies to adopt AI to stay competitive.

Regarding competence strategy some theorists have argued that companies without AI experience should compensate by acquiring a high tech start-up with the needed technology and competence. However, the data indicates that the most limiting factors for companies without AI experience are related to leadership and technical capabilities, not access to competence. It is only in later stages of the adoption process that access to competence becomes the primary limiting factor.

The data gives mixed indications on AI consequences on employment. Half of the companies implementing AI expect job losses in the organization in the coming 3 years, while almost a third expects AI to lead to new jobs. However, the data also suggests that existing employees will need to change their skill sets. Therefor both the public and private sector will need to adapt and find ways to support employees that need to re-educate themselves.

Place, publisher, year, edition, pages
2018.
National Category
Other Engineering and Technologies not elsewhere specified
Identifiers
URN: urn:nbn:se:bth-16483OAI: oai:DiVA.org:bth-16483DiVA, id: diva2:1218640
Subject / course
IY2578 Master's Thesis (60 credits) MBA
Educational program
IYABA MBA programme
Available from: 2018-06-26 Created: 2018-06-14 Last updated: 2018-06-26Bibliographically approved

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