Artificial Intelligence in Value Creation

Table of contents. 2



1. Value creation and competitive advantage models. 5



1.1. Introduction. 5



1.2. The value creation and competitive advantage models. 10



1.2.1. Introduction. 10



1.2.2. The influence of technology on the logics of value creation. 11



1.2.3. Value chains. 13



1.2.4. Motivation for extending the concept of value chains. 19



1.2.5. Value constellations. 21



1.2.6. Value shops. 22



1.2.7. Value networks. 27



1.2.8. Value grid. 36



1.2.9. Value structures in service-dominated logics. 42



1.2.10. Conclusion. 45



1.3. The role of data, information and knowledge in generating value. 47



1.3.1. Knowledge as a key resource of an organization. 47



1.3.2. Data, information, knowledge and wisdom in knowledge management. 48



1.3.3. The concept of the knowledge value chain. 51



1.3.4. Transformation processes in the knowledge chain. 53



1.4. The influence of information technologies on value configurations and competition. 55



1.4.1. Liquefied information in the value chain. 55



1.4.2. Influence of information technologies on the value chain. 56



1.4.3. The impact of information systems on competitiveness and value structures. 57



1.5. Value networks in the telecommunications and IT industries. 59



1.5.1. Motivation for the development of new methods for assessing business potential in the IT and telecommunications industries. 60



1.5.2. The model of control points as the basis of the business potential analysis method. 61



1.5.3. The value network models in the telecommunications and digital media industries. 64



1.6. Competencies necessary to achieve a competitive advantage. 67



2. Artificial intelligence methods and techniques. 71



2.1. Data, information and knowledge in contemporary information systems. 71



2.1.1. Smart, connected products. 72



2.1.2. Data sources. 74



2.1.3. Data complexity. 77



2.1.4. Data processing methods. 79



2.1.5. Conclusion. 83



2.2. Concept and basic methods of artificial intelligence. 85



2.2.1. Definitions of artificial intelligence. 85



2.2.2. Classification of environments. 91



2.2.3. Solving problems by searching. 93



2.2.4. Knowledge and planning in certain situations. 98



2.2.5. Knowledge and planning in a state of uncertainty. 102



2.2.6. Learning. 104



2.2.7. Perception, communication and action. 107



2.2.8. Creative and prognostic capabilities. 109



2.2.9. Summary. 111



2.3. The most important AI technologies. 113



2.4. Cognitive Computing Systems. 118



2.4.1. Features of Cognitive Computing systems. 119



2.4.2. Components and principles of Cognitive Computing systems design. 121



2.4.3. CC class systems as a new quality in management. 124



2.5. Summary. 128



3. Influence of artificial intelligence on activities and competitiveness of an organization 129



3.1. Objectives, subject, method and quantitative analysis of research results. 129



3.1.1. Objectives and the subject of research. 129



3.1.2. Research methodology. 130



3.1.3. Detailed analysis of value offered. 132



3.2. Adoption of artificial intelligence systems in contemporary organizations. 139



3.2.1. Investments in AI and adoption of this class of solutions. 139



3.2.2. Key success factors. 142



3.2.3. Barriers and risk factors. 149



3.2.4. Summary. 151



3.3. The impact of AI systems on activities in the value chain. 152



3.3.1. Design. 152



3.3.2. Production and logistics. 169



3.3.3. Sales and marketing. 182



3.3.4. Personalization, service and after-sales service. 197



3.3.5. Human Resource Management. 205



3.3.6. Information and knowledge management. 209



3.4. AI influence on competitiveness and markets. 217



3.4.1. Manufacturers. 218



3.4.2. Customers. 224



3.4.3. Suppliers. 225



3.4.4. New players. 226



3.4.5. Markets. 227



3.4.6. Sources of competitive advantage. 228



3.5. The influence of artificial intelligence on the role and competencies of human. 233



3.5.1. New competencies. 234



3.5.2. New roles in organizations. 236



3.6. Summary. 238



4. Model for value generation in companies and cognitive networks. 239



4.1. Classification of AI technology in the context of value generation. 239



4.1.1. Knowledge value chains and data transformation processes in information systems 239



4.1.2. Classification of AI systems according to a place in the knowledge value chain. 246



4.1.3. Classification of AI systems according to cognitive functions. 253



4.2. Value generation model - organization level. 256



4.2.1. Value generation process. 256



4.2.2. Value generation model 266



4.3. Cognitive networks. 268



4.3.1. Classic constellations of values â â and value systems based on AI 271



4.3.2. Cognitive network concept. 285



4.3.3. Key competencies of organizations operating in cognitive networks. 289



4.4. Summary. 291



5. Summary and recommendations for future research.. 293



Appendix 5.1. Summary of desirable competencies in organizations implementing AI solutions. 296



Domain competencies. 296



Managerial competencies. 298



Competencies of people constructing, maintaining and developing AI systems. 299



Competencies and the culture of an organization. 299



Appendix 5.2. Challenges related to the implementation of artificial intelligence systems. 301



Challenges in specific areas of activity. 301



Challenges and barriers to design and implementation. 304



Appendix 5.3. The list of analyzed projects and companies using AI or supporting its design. 305