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Introduction of Artificial Intelligence

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Introduction of Artificial Intelligence

  1. 1. Brief introduction August 2019 Introduction of Artificial Intelligence. Opportunities and potential for companies
  2. 2. Artificial Intelligence (AI) refers to the automation of intelligent behavior and is a cross-sectional technology incorporating various disciplines. 1 Philosophy Computer Science Psychology Neuro Sciences Mathematics Linguistic Economy Artificial Intelligence Source: Mücke Sturm Company Definition & basics of AI Cross-sectional areas involved in AI Overview Minsky McCarthy “Artificial intelligence …describes any task performed by a program or a machine that, if a human carried out the same activity, we would say the human had to apply intelligence to accomplish the task.” “Artificial intelligence … is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. ” “Artificial intelligence …is a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation.” Kaplan Haenlein “Artificial intelligence …is the ability of a digital computer or computer- controlled robot to perform tasks commonly associated with intelligent beings.” Künstliche Intelligenz „Artificial Intelligence“ Various definitions of „Artificial Intelligence“ Extract
  3. 3. Artificial intelligence has various fields of application and technologies which are based on human abilities and actions. 2 Artificial Intelligence – fields of application Source: Mücke Sturm Company; McKinsey, 2018 Machine Learning Independent Learning Computer Vision Understanding and capturing vision Natural Language Processing Language comprehension and interaction Smart Robotics Environmental manipulation Digital Virtual Agents Digital personal assistants Autonomous Vehicles Autonomous Driving Machine Learning Vision Speaking and listening Feel and act Decision and Knowledge Navigate through complex environments ▪ Learning based on specific results without the need for specific programming ▪ Use and transfer of existing knowledge to new problems ▪ Visual recording of the environment on e.g. pictures ▪ Evaluation and understanding of objects based on visual information ▪ Understanding of written or spoken words ▪ Evaluation and drawing of conclusions based on linguistic interaction ▪ Manipulation of the environment using mechanical systems such as gripper arms ▪ Recording and evaluation of interactions with the environment of the system ▪ Support and adaptation to individual needs and preferences ▪ Assumption of simple tasks ▪ (Partially) autonomous control and navigation ▪ Reaction to dynamic changes Field of application Description AI Technology Field of application Description AI-Technology
  4. 4. Potentials and chances through artificial intelligence have either evolutionary or disruptive character and involve products, business models and processes. 3 Artificial Intelligence – Potential and chances Source: Mücke Sturm Company; 1 CX – Customer Experience Evolution Disruption Evolution ▪ Increase of transparency using AI ▪ Increased efficiency through mechanization or automation ▪ Replacement of repetitive work (where possible) ▪ Use of AI for new or higher revenues ▪ Creation of competitive advantages through innovative business models ▪ Enabler for higher efficiency in existing business models ▪ Use of artificial intelligence for e.g. personalization or individualization of products ▪ Creation of new interaction possibilities for the customer with the product Products Business models ProcessesBusiness area Potential & chances selection Focus indicative Improvement CX1 New Revenues Increased Effectiveness High-level Goals indicative
  5. 5. The successful approach of chances and potentials of AI depend on the business direction & certain aspects which need to be considered during the introduction. 4 Challenges of implementing the first AI projects Alignment of AI projects Success story Lighthouse pilots HighLow HighLow Outlay Infrastructure, data, abilities, skills, etc. Scalability Extensibility,modularity,adaptability,etc. Question mark projects Guarantee for frustration ? Important steps for AI projects Selection Fail Fast Willingness to experiment. Fastest possible validation or falsification of ideas based on data. Fail Fast Convey your vision and strategy Definition and communication of your AI vision and strategy; inclusion and collection of all relevant stakeholders. Convey your vision and strategy Empower your organisation Adaptation of organization, teams and infrastructure to be able to implement AI. Empower your organization Source: Mücke Sturm Company
  6. 6. Mücke, Sturm & Company GmbH Head Office Munich Theresienhöhe 12 T +49 89 461399 0 80339 München F +49 89 461399 777 Germany 5 Matthias Mainone Munich www.muecke-sturm.de Associate Partner m.mainone@muecke-sturm.de This document is intended for personal use only. Distribution is only permitted without any changes or omissions – publication, in whole or in parts, requires prior written consent by MÜCKE, STURM & COMPANY and correct citation of sources. The herein published texts and graphics were used by MÜCKE, STURM & COMPANY in the context of a presentation; they themselves do not represent the presentation in its entirety. All mentioned company names, logos, brands, brand symbols and other copyrighted material are the sole properties of the respective company; they are only used for illustrative purposes. Copyright Kontakt & Copyright Dr. Daniel Nowakowski Project Manager d.nowakowski@muecke-sturm.de

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