Future Directions in Autonomous and Self-Optimizing Enterprise Systems

Authors

Velangani Divya Vardhan Kumar Bandi
Director AI/ML Engineering

Synopsis

Autonomy enables enterprises to react to their environments without human intervention. The race to become autonomous is driven by large investments in remote sensing, AI-enabled decision-making, and robotic hardware. Although true autonomy has not been achieved, core capabilities are being developed and demonstrated in industry. Traditional enterprise resource planning (ERP) systems and business process automation, although important, function as reflexes in response to human impulses and decisions. Advances in AIS, applied AI, and autonomous systems suggest that future enterprise systems may no longer rely on humans to sense, reason, and act in all but the most extreme situations. Such systems could be termed autonomous, a definition that encompasses but is not limited to the commonly used term self-driving or self-riding.

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Published

14 February 2026

How to Cite

Bandi, V. D. V. K. . (2026). Future Directions in Autonomous and Self-Optimizing Enterprise Systems. In Modern Enterprise Intelligence Systems: Engineering Adaptive, Multi-Cloud Data Platforms (pp. 148-162). Deep Science Publishing. https://doi.org/10.70593/978-93-7185-496-2_10