AI Resilience Report forBusiness Continuity Planners

Right now, AI is mostly being used to augment business continuity planners — helping them work faster — rather than replacing them outright. The Business Continuity Institute reports that AI-powered platforms can automate documentation, policy creation, and compliance tracking, while natural language processing tools generate tailored business continuity plans ^[1] that meet ISO 22301 requirements. Machine learning models also rank risks by likelihood and impact, and AI-driven Business Impact Analyses (BIAs) update continuously based on live operational data ^[1].

Consultants in the Disaster Recovery Journal describe using generative AI to accelerate maturity assessments and reduce billable time on client engagements ^[2]. On the threat-monitoring side, Aon warns that AI is also creating new risks planners must manage, including third-party AI service outages and "shadow AI" data leakage ^[3] — keeping humans firmly in the loop.

Adoption is real but uneven. DRI International notes that 65% of U.S. workers say AI has had a positive impact on their productivity, yet 89% of business leaders surveyed by NBER reported no measurable AI impact on labor productivity over three years ^[4] — even when 69% are actively using it. That gap suggests tools exist and are cheap, but training and trust lag behind.

The World Economic Forum recommends an “AI + human-in-the-loop” model where automation handles execution and humans handle judgment, creativity, and relationships ^[5] — exactly the skills continuity planners use during a real crisis. Because mistakes during disasters can cost lives and millions of dollars, legal and ethical caution will slow full automation. The good news: your judgment, stakeholder communication, and crisis leadership are exactly what employers still need humans for.