Artificial Intelligence in Marketing & Sales: The ABB experience Subtitle: Building a model for technologically driven change management in a B2B multinational corporation

Thesis title: Artificial Intelligence in Marketing & Sales: The ABB experience Subtitle: Building a model for technologically driven change management in a B2B multinational corporation
Author: Edmundo, Ana
Thesis type: Diploma thesis
Supervisor: Brunet-Thornton, Richard
Opponents: Jirsák, Petr
Thesis language: English
Abstract:
Artificial Intelligence is becoming commonplace. Innovative corporations independently of their size feel the pressure to implement, in their operations, artificial intelligence (AI) systems. Yet insufficient research on how to successfully implement such systems exists. This thesis proposes to fill this gap, answering how can AI be successfully driven, when global teams introduce the change and local teams face the change. The method followed was grounded theory research and the data collection counted with the live experience of 20 individuals from four perspectives: vendors, B2B corporations, consulting implementation partners, and Artificial Intelligence researchers. As a result, the Artificial Intelligence Life Cycle (AILC) framework emerges containing eleven consecutive steps. To understand the global and local interaction the framework is then applied in a tangible ABB case study. This exploratory study aids to reach a new level of understanding on AI by advising best-practices and harmonising the “plug and play” expectations of practitioners.
Keywords: Artificial Intelligence; Marketing and Sales; Organizational Resistance; Change Management
Thesis title: Artificial Intelligence in Marketing & Sales: Building a model for an Artificial Intelligence roll-out in a B2B multinational corporation
Author: Edmundo, Ana
Thesis type: Diplomová práce
Supervisor: Brunet-Thornton, Richard
Opponents: Jirsák, Petr
Thesis language: English
Abstract:
Artificial Intelligence is becoming commonplace. Innovative corporations independently of their size feel the pressure to implement, in their operations, artificial intelligence (AI) systems. Yet insufficient research on how to successfully implement such systems exists. This thesis proposes to fill this gap, answering how can AI be successfully driven, when global teams introduce the change and local teams face the change. The method followed was grounded theory research and the data collection counted with the live experience of 20 individuals from four perspectives: vendors, B2B corporations, consulting implementation partners, and Artificial Intelligence researchers. As a result, the Artificial Intelligence Life Cycle (AILC) framework emerges containing eleven consecutive steps. To understand the global and local interaction the framework is then applied in a tangible ABB case study. This exploratory study aids to reach a new level of understanding on AI by advising best-practices and harmonising the “plug and play” expectations of practitioners.
Keywords: Organizational Resistance; Artificial Intelligence; Change Management; Marketing and Sales

Information about study

Study programme: Ekonomika a management/International Management
Type of study programme: Magisterský studijní program
Assigned degree: Ing.
Institutions assigning academic degree: Vysoká škola ekonomická v Praze
Faculty: Faculty of Business Administration
Department: Department of Management

Information on submission and defense

Date of assignment: 17. 11. 2017
Date of submission: 15. 5. 2018
Date of defense: 15. 6. 2018
Identifier in the InSIS system: https://insis.vse.cz/zp/63899/podrobnosti

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