In the early phases of the industrial revolutions, technological innovations
replaced or relieved human muscle power. In the era of AI, our intellectual
powers are now being simulated, multiplied and partially even substituted
by digitalisation and AI. This results in fully new scaling and multiplication
effects for companies and economies.
Companies are developing increasingly strongly towards algorithmic
enterprises in the digital ecosystems. And it is not about a technocratic or
mechanistic understanding of algorithms, but about the design and optimi-
sation of the digital and analytical value added chain to achieve sustainable
competitive advantages. Smart computer systems, on the one hand, can
support decision-making processes in real time, but furthermore, big data
and AI are capable of making decisions that today already exceed the quality
of human decisions.
The evolution towards the algorithmic enterprise in the spirit of the
data- and analytics-driven design of business processes and models directly
correlates with the development of the Internet. However, we will have to
progressively bid farewell to the narrow paradigm of usage of the user sit-
ting in front of the computer accessing a website. “Mobile” has already
changed digital business significantly. Thanks to the development of the IoT,
all devices and equipment are progressively becoming smart and proactively
communicate with each other. Conversational interfaces will equally change
human-to-machine communication dramatically—from the use of a text-
based Internet browser down to natural language dialogue with everybody
and everything (Internet of Everything).
Machines are increasingly creating new scopes for development and
possibilities. The collection, preparation and analysis of large amounts of
data eats up time and resources. The work that many human workers used
to perform in companies and agencies is now automated by algorithms.
Thanks to new algorithmics, these processes can be automated so that
employees have more time for the interpretation and implementation of the
analytical results.
In addition, it is impossible for humans to tap the 70 trillion data points
available on the Internet or unstructured interconnectedness of companies
and economic actors without suitable tools. AI can, for example, automate
the process of customer acquisition and the observation of competition so
that the employees can concentrate on contacting identified new customers
and on deriving competitive strategies.
Recommendations and standard operation procedures based on AI and
automated evaluation are often eyed critically by companies. It surely feels
strange at the beginning to follow these automated recommendations that
are created from algorithms and not from internal corporate consideration.
However, the results show that it is worthwhile because we are already sur-
rounded by these algorithms today. The “big players” (GAFA = Google,Apple, Facebook, Amazon) are mainly to solely relying on algorithms that
are classified in the category “artificial intelligence” for good reason. The
advantage: These recommendations are free of subjective influences They are
topical, fast and take all available factors into consideration.
Even at this stage, the various successful use and business cases for the
AI-driven optimisation and design of business processes and models can
be illustrated
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