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Wednesday, May 13, 2026

Adapting to new threats with proactive danger administration


Unplanned downtime poses a serious problem for organizations, and is estimated to price World 2000 firms on common $200 million per yr. Past the monetary affect, it will probably additionally erode buyer belief and loyalty, lower productiveness, and even end in authorized or privateness points.

A 2024 ransomware assault on Change Healthcare, the medical-billing subsidiary of business large UnitedHealth Group—the most important well being and medical information breach in US historical past—uncovered the info of round 190 million individuals and led to weeks of outages for medical teams. One other ransomware assault in 2024, this time on CDK World, a software program agency that works with almost 15,000 auto dealerships in North America, led to round $1 billion price of losses for automobile sellers because of the three-week disruption.

Managing danger and mitigating downtime is a rising problem for companies. As organizations grow to be ever extra interconnected, the increasing floor of networks and the speedy adoption of applied sciences like AI are exposing new vulnerabilities—and extra alternatives for risk actors. Cyberattacks are additionally turning into more and more refined and damaging as AI-driven malware and malware-as-a-service platforms turbocharge assaults.

To organize for these challenges head on, firms should take a extra proactive method to safety and resilience. “We’ve had a standard method of doing issues that’s truly labored fairly properly for perhaps 15 to twenty years, nevertheless it’s been primarily based on detecting an incident after the occasion,” says Chris Millington, international cyber resilience technical skilled at Hitachi Vantara. “Now, we’ve received to be extra preventative and use intelligence to concentrate on making the techniques and enterprise extra resilient.”

Obtain the report.

This content material was produced by Insights, the customized content material arm of MIT Know-how Evaluation. It was not written by MIT Know-how Evaluation’s editorial workers. It was researched, designed, and written solely by human writers, editors, analysts, and illustrators. This consists of the writing of surveys and assortment of knowledge for surveys. AI instruments which will have been used have been restricted to secondary manufacturing processes that handed thorough human assessment.

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