Enterprises facing challenges with AI automation can find hope by acknowledging a crucial factor: the lack of process intelligence. Many organizations invest in AI agents expecting seamless integration and performance. However, without a clear understanding of their workflows, these agents merely replicate existing inefficiencies, leading to underwhelming results and high cancellation rates of AI projects predicted by Gartner. Celonis highlights the importance of process intelligence, which provides the contextual backdrop that AI agents need to operate effectively. As organizations shift from passive process mining to active decision-making frameworks, they can transform AI agents from inefficient executors to reliable operators. This requires a focus on understanding workflows before implementing automation, as poor clarity can escalate minor issues into significant failures. Ultimately, for effective AI deployment, companies must prioritize process intelligence to enhance operational efficiency and ensure measurable outcomes.
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