Balancing trust and control to unlock AI-powered networking (www.techradar.com)

AI has increasingly embedded itself in enterprise networking, enhancing operations by automating core tasks such as performance monitoring and anomaly detection. By 2026, reports indicate that 90% of organizations are realizing a return on investment from AI in networking, with many achieving this within just a quarter. However, while there's a strong move towards automation, complete autonomy remains a concern; only 10% of leaders are willing to let AI make decisions without human oversight. This hesitation stems from worries about accountability, transparency, and reliability, especially given the critical nature of networking in supporting business operations. To address these concerns, organizations are adopting a model of "guided autonomy," where AI handles routine, lower-risk tasks while human oversight remains for critical decisions. This approach allows businesses to leverage AI's speed and efficiency without sacrificing control. The success of guided autonomy depends on clear boundaries and designed oversight, ensuring that AI’s capabilities are utilized effectively while maintaining necessary human accountability. As organizations build trust in AI and gradually increase its decision-making role, they can create a balanced environment that enhances operational efficiency while addressing crucial governance issues.