AI is already influencing our lives today. Be it the
automatic speech and face recognition in our smartphones or the translation
function in Google. In the future, AI will also play a decisive role in
auditing.
And while we tend to associate artificial intelligence with
robots and self-driving cars, some processes in the p2p process can already be
automated today. When it comes to implementation, we differentiate between weak
and strong AI.
Weak AI
Weak AI can determine performance indicators based on the
analysis of a given amount of data, for example when extracting invoice data,
which allows process managers to initiate process optimizations. The advantage
is obvious. The determination of the key performance indicators, which
previously had to be calculated manually with hard work, can now be put
together in a fraction of the time using algorithms provided.
Strong AI, on the other hand, not only includes the analysis
of the previous amount of data but can also use this analysis to independently
predict future scenarios precisely and initiate the necessary work steps.
Despite all the euphoria for automation, humans are still not able to optimize
processes with strong AI.
Machine Learning
In addition to machine learning, artificial intelligence
includes deep learning. While machine learning recognizes patterns and
regularities based on existing data and algorithms, for example, deep learning
in process mining does not only include the analysis of processes and their lead
times. Deep learning is a specialization in machine learning and uses neural
networks and large amounts of data to optimize itself.
The ideal picture for operational business processes is
holistic end-to-end automation. The reality is often different. In practice, it
has been shown that some processes are already running digitally and some of
them are also automated. However, this does not apply to all existing
processes. But there is good news. For example, we are currently able to
determine the invoice documents that are suitable for background posting in the
future. This means that fully automated processing of an invoice is basically
possible. Especially when no manual activities are required in the individual
process steps. The decision as to whether future invoices should be posted in
the background is currently still made by the user himself.
With pi.a analytics you are already able to specify the
parameters for process optimization today. As a result, process optimization is
no longer like using a dowsing rod that hopefully shows us hidden resources.
Based on existing digital traces and self-learning algorithms, future
optimizations can be made based on objective performance indicators. We would
be happy to show you how you can optimize your company processes in a live demo.
Comments
Post a Comment