This year, some exciting innovations in the field of AI (artificial intelligence) are expected. Does individual communication with customers and colleagues fall by the wayside, or does it finally benefit significantly from this?
Deep neural networks (DNS) are the focus of this year’s developments. They mimic the learning behavior of the human brain and thus form an independent process to evaluate data not only in large quantities, but to formulate these into solutions, adapted to each situation and influences. Simply put, the system is learning.
So far, AI is very appealing to many users, but not very understandable. Entrepreneurs, meanwhile, are increasingly preparing for the market launches of mature AI modules in order to optimally design and adapt future production and marketing processes. Much of the expectation is to get more information from collected data, e.g. about customer behavior, marketing strategies, logistical tasks but also in-house structures.
- So-called capsule networks are a sub category of DNS and process mainly visual information. New to these systems is the recognition of hierarchies, which the developers hope for a more accurate classification of the analyzed data.
- Deep Reinforcement Learning (DRL) software learns through observation, interaction with the environment, and reward. This offers decision-making levels, ie strategists probably a lot of profitable support in the future.
- The General Adversarial Networks (GAN), on the other hand, compete against each other in a digital scenario, creating forged data and then differentiating it. In this way, the programs should learn independently and henceforth be better able to protect against cyber attacks.
Despite the many and very promising forecasts, the AI still has to face some problems. One of these is the lack of availability of appropriate data necessary for deep learning. At this point it is necessary to communicate with the target group or the information carriers. Important input is e.g. from SMS surveys, email newsletters, etc., which can be controlled by gateway with HTTP APIs targeted, on the other hand, the results can be immediately transferred by data export in the own AI-Sortware and continue to process there.
Communication = data acquisition?
Every entry in a search engine, newsletter opt-in, linking, registration, timestamp etc. provide valuable data. However, this alone doesn’t “feed” the art learning networks enough to gain specific analysis, such as buying behavior, personal preferences, interests or needs.
Amazon evaluates e.g. customer evaluations by means of artificial intelligence, in order to propose besides suitable products also a dynamic pricing. Therefore, the Group depends on authentic feedback from its customers in order to provide the AI software with suitable data.
Unlike robots or complex equipment that performs tasks according to fixed programming, such AI concepts are subject to the constant influence of new factors. As a result, they have to work beyond the level of dehumanized interactions and not interfere with communication, as often accused, but actually enrich it.
Benefits for companies
How do artificial intelligence and communication influence ideally?
From any form of communication, whether by email, SMS, surveys, search queries, account registrations, newsletter subscriptions, etc., essential information can be obtained. It’s important to process and analyze these sensibly. Thanks to deep learning, AI can record detailed data and present very characteristic solutions for further evaluation. Entrepreneurs only need to know to use them strategically.
Ideally, at this point, it will be useful to provide the customer with information that is useful to the customer, e.g. for product selection, new releases, flavor, size advice, price segmentation and much, much more.
Internally, however, employee communication can be significantly improved and capacities can be used as required in the given situation. Thanks to AI, the entire workflow becomes even smoother.