DIGITAL ECOSYSTEMS
n today ’ s world , businesses in all industries across the globe are being forced to be more efficient and streamline processes .
One such solution is intelligent workflows : automated or semi-automated business processes that are enhanced by technologies such as AI , machine learning and data analytics to improve decision-making , efficiency and outcomes . Unlike traditional workflows , which often involve a series of predefined steps and rules , intelligent workflows can adapt to changing conditions , analyse vast amounts of data , and even make decisions to optimise process performance .
Defining Intelligent Workflows : A paradigm shift “ Traditional automation integrates actions where variation is contained and decisions can be more easily programmed . It is more rigid ,” explains Cassiano Surek , CTO at design agency Beyond . “ Intelligent workflows combine automation , AI and analytics to adapt to different conditions , adjusting themselves as environments evolve . A good example is continuously training a model to detect abnormalities as they appear : new ones will come up over time and the workflow will evolve accordingly .”
Echoing Surek ’ s sentiments , James Dodkins , Tech Evangelist at Pegasystems , characterises traditional workflows as akin to a “ well-worn path ,” whereas intelligent workflows “ forge their own path .” These workflows , Dodkins explains , use smart tech like AI to constantly learn , adapt , and optimise processes , reacting to new data and changing circumstances on the fly .
“ They ’ re not merely about automating processes ; they ’ re about optimising them , learning from data patterns ,
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