Artificial intelligence has the potential to change virtually every internal and external process in all business segments. Indeed, it has long been pushing ahead with a transformation process...
Artificial intelligence has the potential to change virtually every internal and external process in all business segments. Indeed, it has long been pushing ahead with a transformation process that is disruptive on many levels. AI is thus the main trending topic for global technological development and the digital industry. Our stories, podcasts and other content devoted to AI offer valuable insights into various aspects of this field, which is as broad as it is exciting.
AI as a core idea with a concentric avalanche effect
Artificial Intelligence empowers technologies to solve specific tasks better than human beings can. Examples of this are facial recognition or automatic classification procedures. In the effort to gain the intelligence that this requires, ML or machine learning comes into play. With ML, a machine can train itself by processing large amounts of data and algorithms and performing tasks better and better.
If machine learning was to be implemented in a meaningful way, though, another technological revolution had to occur: Deep Learning. Thanks to its capacity for processing immense amounts of data, the neural network has now developed to the point that machines are more effective in performing tasks of image recognition than humans are. One area of application, for example, is MRI-based automatic tumor identification.
It is only thanks to deep learning that AI will experience a golden future of its own. That is because deep learning helps machine make the leap to practical areas of application, thus broadening the field of AI. Deep learning seems to be applicable to almost any machine application:
Speech and sentiment analysis in sales and after-sales to improve CX
Optimization of security architectures in cyber security and real-time monitoring of the public space
Risk minimization in financial transactions
Analysis and mastery of big data as part of Industry 4.0
AI was thus the first and main concept upon which ML followed. Deep learning ultimately ensures that the development of AI and machine learning will progress at an ever-faster pace and will fan out in a wide variety of directions as it spreads to more and more practical areas of application.
The three technologies and their concepts are therefore closely intertwined, interdependent and mutually supportive. The strengths and the mission of AI in this context are:
Analysis of huge amounts of data
Linking of data to create meaningful relationships
Identification of patterns
Derivation of results and predictions
Big data constitutes the database about which AI acquires knowledge. Then, with the aid of machine learning, it continuously trains this knowledge to arrive at structured decisions and automate processes based on them.
AI in marketing
There are many ways in which the marketing cosmos benefits from AI-based applications and their advancement. Artificial intelligence can be applied, for example, to:
Automatic and programmatic campaign management
Marketing automation, programmatic advertising, real-time analysis of target groups and performance, automated campaign optimization – if not for AI, none of this would be even remotely thinkable.
Ever since the GDPR and the ePrivacy Regulation, at the latest, though, target-group analyses and targeting are also tied to legal issues around the use of personal data for marketing and promotional purposes. But these regulations also help the industry make the most of its enormous innovative power in the effort to develop alternative, AI-based targeting and personalization processes.
AI in the customer dialog
In eCommerce and in B2B business, a positive CX makes for happy customers and a better conversion rate. AI has a valuable role to play here as well. In this context, AI-supported advancements in chatbots are of crucial importance.
Natural Language Processing is the type of AI that “understands” people’s natural language and helps chatbots respond to customer inquiries. AI can help offer each customer optimal service individually in this connection.
The possible fields of application of AI chatbots are diverse:
Assistance with product selection
Here, too, a look at China offers a glance at the kinds of things that are already technically possible. WeChat offers AI-based product advice in the form of a style-consultant bot. Coupled with VR/AR/XR applications that let users try on clothes right there on their smartphone app, this capability creates completely new shopping worlds – and fresh marketing opportunities at the same time.
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