Algorithmic Business—On the Way Towards Self-Driven Companies

The effects and implications of algorithmics and AI affect the entire corporate value added chain. According to the focus of the book, the “business

layer” of the AI business framework has foregrounded the “customer facing” processes and functions. In this chapter, the potentials for the entire

corporate value creation are briefly described. It will be shown that artificial intelligence can change the way of working in classical company areas

both sustainably and radically: By using artificial intelligence, companies can

not only exploit efficiency and productivity potentials but also cater better

to customers and thus create added value. In addition, the significance of the

ideas and potentials of so-called Conversational Commerce (Sect. 4.2) for

internal company functions and processes will be illustrated and explained

(Conversational Office). Finally, the areas of marketing, market research

and controlling (as relevant cross-sectional function) will be described and

explained in more detail. Furthermore, algorithmics and AI also have the

potential of reinventing business models; these topics will also be treated in

this chapter. Finally, it will be investigated whether it makes sense to install

the position of a chief artificial intelligence officer in companies.

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Possible Limitations of AI-Based Bots

The examples above already show the present-day potential of AI-based bots. At present, these systems are still in an early stage and still have certain limitations and potentials for optimisation. Twitter Bot Tay by Microsoft Most bots at present are reactive service bots. Engagement bots that actively interact with the users as market and brand ambassadors go one step further. The most famous example here is the chatbot Tay by Microsoft. Microsoft removed Tay from the web apologetically within one day. The example shows that the uncontrolled training of bots by the community can lead to fatal consequences. AI systems still have to learn ethical standards. It thus becomes apparent that even bots require a kind of guideline. Like a journalist has to observe editorial guidelines, bots have to observe certain standards. The next generation of AI-based bots must control and create the possible room for communication. IBM Watson has been able to celebrate quite a few respectable resul...

What is Machine Learning

The term machine learning (ML) as a part of artificial intelligence is ubiq- uitous nowadays. The term is used for a wide number of various appli- cations and methods that deal with the “generation of knowledge from experience”. The well-known US computer scientist Tom Mitchell defines machine learning as follows: A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E (Mitchell 1997). An illustrative example of this would be a chess computer program that improves its performance (P) in playing chess (the task T) by experience (E), by playing as many games as possible (even against itself ) and analysing them (Mitchell 1997). Machine learning is not a fundamentally new approach for machines to generate “knowledge” from experience. Machine learning technology was used to filter out junk e-mails a long time ago. Whilst spam filters that tack- ...

AI the Eternal Talent Is Growing Up

The subject of AI is nothing new—it has been discussed since the 1960s. The great breakthrough in the business world has failed to appear, but for a few exceptions. Thanks to the immensely increased computing power, the methods can now be massively parallelised and intensified. Innovative deep learning and predictive analytics methods paired with big data technology facilitate a quantum leap of AI potential benefits for business applications and problems. In the last ten years, the breakthrough with regard to the applicability in business practice has succeeded due to this further devel- opment. At present, the discussion is, on the one hand, shaped by hardly realistic science fiction scenarios that postulate computers taking over man- kind. On the other hand, there is a strongly informatics-/technology-laden discourse. In addition to that, there are singular popular science publications as well as articles in the daily press. The latter adhere to the exemplary level without holis...

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