"From IT outages to global crises, modern organizations increasingly require rapid, reliable response and recovery capabilities to keep their digital operations running and their people safe. To a great degree, ever-higher expectations for operational resilience must be met by significant advances in automation -- which leading solution providers are making possible by AI and machine learning. That's the core takeaway from a 30-minute podcast-style video chat I had the pleasure of participating in."
"I kicked things off by noting a stronger market focus on resilience, in three dimensions: operational resilience (technologies, business processes), personal resilience (people), and business resilience (strategic outcomes). Recent research findings show companies are ramping up their investments in capabilities to detect, respond, and recover to complement their capabilities to identify, protect, and govern (acknowledgment of the six verbs of NIST CSF 2.0)."
Organizations face escalated stakes for continuity across IT outages and global crises, requiring rapid, reliable response and recovery to protect digital operations and personnel. Ever-higher expectations for operational resilience necessitate significant automation advances enabled by AI and machine learning. AI-powered incident management tools automate detection, communication, troubleshooting, mitigation, and recovery, reducing reliance on manual processes that undermine efficiency and increase cost. Companies are increasing investments to detect, respond, and recover, complementing identification, protection, and governance capabilities aligned with NIST CSF 2.0. Operational, personal, and business resilience require coordinated technology, process, and strategic outcomes.
Read at ZDNET
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