The Myth of Permanent Automation

Hendrik Flamme
Head of Data Science
Table of contents
Heading 2

Is Automation Ever Truly Complete?

Many assume that once a document extraction system works perfectly for a set of documents, the task is permanently solved and automated. Unfortunately, this is far from the truth. Numerous exceptions and rules often become apparent only during actual system use by customers.

The Importance of Adaptivity

An adaptive system is needed to learn from new data and feedback, ensuring that similar future cases are handled correctly. Even if the extraction functions flawlessly for a particular set of documents initially, the task is not permanently resolved and automated. Numerous exceptions and rules only become evident to process experts during the system's operational use by the customer. An adaptive system is required to learn from new data and feedback, ensuring that future similar cases are accurately managed. Furthermore, no process is static or permanently fixed. Processes, including the extraction of data from documents, continually evolve over time from customer to customer. New products and product variants are introduced, additional data collection requirements emerge, or subsequent processes change, imposing new demands on the extraction mechanism. What may have been an accurate extraction result two months ago could now be outdated and thus partially incorrect. By definition, general, non-adaptive extraction systems are incapable of addressing these challenges.

The Dynamic Nature of Document Extraction

What was a correct extraction result two months ago might now be outdated and partially incorrect. By definition, general, non-adaptive extraction systems cannot handle these issues. They require constant updates and adjustments to keep up with the evolving nature of business processes.

Conclusion

In conclusion, automation is never truly complete. It requires adaptive systems that can learn from new data and feedback and evolve with changing business processes. By investing in adaptive automation solutions, businesses can ensure the accuracy and efficiency of their document extraction processes over time.

automaited comes into play by intelligently automating with adaptive AI. Our AI Agent Ada, is able to adapt to changing processes by adjusting the existing automations over time. This allows for continuous improvement and process efficiency.

‍

Is Automation Ever Truly Complete?

Many assume that once a document extraction system works perfectly for a set of documents, the task is permanently solved and automated. Unfortunately, this is far from the truth. Numerous exceptions and rules often become apparent only during actual system use by customers.

The Importance of Adaptivity

An adaptive system is needed to learn from new data and feedback, ensuring that similar future cases are handled correctly. Even if the extraction functions flawlessly for a particular set of documents initially, the task is not permanently resolved and automated. Numerous exceptions and rules only become evident to process experts during the system's operational use by the customer. An adaptive system is required to learn from new data and feedback, ensuring that future similar cases are accurately managed. Furthermore, no process is static or permanently fixed. Processes, including the extraction of data from documents, continually evolve over time from customer to customer. New products and product variants are introduced, additional data collection requirements emerge, or subsequent processes change, imposing new demands on the extraction mechanism. What may have been an accurate extraction result two months ago could now be outdated and thus partially incorrect. By definition, general, non-adaptive extraction systems are incapable of addressing these challenges.

The Dynamic Nature of Document Extraction

What was a correct extraction result two months ago might now be outdated and partially incorrect. By definition, general, non-adaptive extraction systems cannot handle these issues. They require constant updates and adjustments to keep up with the evolving nature of business processes.

Conclusion

In conclusion, automation is never truly complete. It requires adaptive systems that can learn from new data and feedback and evolve with changing business processes. By investing in adaptive automation solutions, businesses can ensure the accuracy and efficiency of their document extraction processes over time.

automaited comes into play by intelligently automating with adaptive AI. Our AI Agent Ada, is able to adapt to changing processes by adjusting the existing automations over time. This allows for continuous improvement and process efficiency.

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