- Task execution is now dependent on more final points than ever before
- Businesses are struggling to control, manage and maintain AI
- All of this threatens companies with “digital chaos”
Process automation and orchestration platform provider Camunda have warned that companies could face “digital chaos” if they do not focus on getting their AI implementation right in the midst of increasingly complex ecosystems.
The number of final points companies depend on performing tasks has now risen to 50, an increase of 19% in five years.
Camunda explores the increasing complexity across business processes that threaten control, and ultimately warn of an “Automation Armageddon.”
Complexity can cause “chaos”
Four out of five (82%) are now reporting increased compliance risks due to the lack of control constructed by a more complex landscape, with three -quarters (77%), which highlights higher risks to core business errors.
Camunda SVP for customer success Kurt Petersen summarized: “Today’s digital infrastructures and processes are both complex and interdependent, making it a significant challenge.
“In a constantly evolving landscape, organizations often struggle with extinguished tools and technologies, which prevents their ability to streamline operations or achieve full visibility.”
The report criticized companies for using artificial intelligence, machine learning and automation to tackle a single task rather than taking a wider, business approach.
It found that 85% face challenges in scaling and operationalization of AI across their businesses, despite 93% acknowledging that AI must “fully integrate” into their processes to maximize their ROI.
Even those who implement AI across their processes are not happy with the results, with four -fifths (79%) that lack a way to control, control and maintain it effectively.
Petersen concluded: “If organizations are to operate AI across their entire business, AI applications and services must be orchestrated as any other end point in automated business processes. This will ensure that they remain compatible and maximize the return on investments from their AI investments. “
