AI

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• Reality and misconceptions about the future of artificial intelligence (AI).

  AI clearly has a key role to play in the business world - now and in the future. It holds unprecedented potential for efficiency gains and new business models. Because AI is unlike any other technology, it also holds the potential for unexpected consequences and disruption on an unprecedented scale. No company should deploy AI blindly and without strategy, and no responsible board can afford not to engage with and understand its potential.

  AI & Machine Learning•Britta Daffner•16 Dec 2020•6 minutes

  

• Identify and implement applications for artificial intelligence (AI) - Data-driven business architecture

  Artificial intelligence (AI) has many practical applications for businesses. Think of AI as a larger framework that provides different capabilities. Companies implementing AI should review their vision and develop an AI strategy that aligns with their larger goals and focus. To implement, data-driven use cases are the basic requirement. Also, a flexible and modular architecture should be chosen from the beginning, which can be expanded and improved as needed in the future.

  Strategy / Vision•Britta Daffner•15 Dec 2020•4 minutes

  

• Data-Driven Business Architecture - Executive Guide Artificial Intelligence (AI)

  In today's era of big data, Artificial Intelligence (AI) and cognitive technologies are becoming a powerful focal point for businesses. They are increasingly being used to intelligently automate and accelerate business processes, make valid predictions, create more engaging and personalized customer interactions, and ultimately recommend the best possible approach to assess a business problem. And in doing so, create an enterprise that is data-centric, agile, and future-focused: the Cognitive Enterprise.

  AI & Machine Learning•Britta Daffner•15 Dec 2020•5 minutes

  

• 3 steps for a strategic Robotic Process Automation (RPA) implementation and integration

  Numerous companies are currently working on the introduction of Robotic Process Automation as a strategic technology for the automation of their processes. The complexity of introducing Robotic Process Automation is low from a technical point of view due to the non-invasive technology and the simple application architecture. Nevertheless, many things have to be taken into account when introducing Robotic Process Automation in order to place the technology successfully in the company.

  Processes•Marcel Schneider•9 Dec 2020•5 minutes

  

• 9 points for successful Robotic Process Automation (RPA) - Which processes can be automated?

  The suitability of a process for automation with Robotic Process Automation can be easily checked by means of 9 factors. These 9 factors are presented and explained in detail in this article. The factors presented are of both technical and business nature. Especially in the field of process automation the following is very important and should always be considered: Just because the automation of a process makes sense from a technical point of view, it does not necessarily mean added value for the company from a business point of view. And vice versa, it is also true that just because a process should be automated from a business point of view, it is also technically possible.

  Processes•Marcel Schneider•9 Dec 2020•5 minutes

  

• "Talk to me" – Conversational Banking

  How the use of chatbots and voice assistants will change banking. The Millenials Generation in particular wants to experience services differently and we show how.

  Banking & Financial Services•andrion ag•1 Dec 2020•7 minutes

  

• Machine Learning - Basics and definition explained for beginners and managers

  In order to be able to assess the potential of machine learning for its own business, the organization must first use technical terms correctly. This article explains "Machine Learning" in a generally understandable way and beyond the hypes.

  Technology•Stephanie Fischer und Dr. Christian Winkler•29 Sept 2020•8 minutes

  

• The 3 Strategic Goals of Machine Learning for Marketing

  AI-driven marketing leverages models to automate, optimize, and augment the transformational process of data into actions and interactions with the scope of predicting behaviors, anticipating needs, and hyper-personalizing messages.

  AI & Machine Learning•Alex Mari•15 May 2019•4 minutes

  

• A voice on the Internet - Voice assistants for customer communication

  Many large corporations are working at full speed to further develop their voice assistants. Assistants like Siri, Alexa and Google Asssistant are already familiar to many and have at least used it on their mobile phones. But where are the chances in this technology and what are voice-supported assistance systems?

  Beginner / Basic•Benjamin Talin•26 Oct 2018•6 minutes