Automated business-continuity plans: generate, test & maintain with AI

Many mid-to-large enterprises—about 200,000 potential customers in the target cohort—struggle to produce and maintain business-continuity plans that regulators, insurers and auditors will accept. Plans are often static PDFs or tribal runbooks, tests are ad hoc, and organizations lack continuous evidence that recovery time objectives (RTOs) and recovery point objectives (RPOs) are met. You could build an AI-first BCP platform that ingests CMDBs, cloud inventories, incident history, contracts and runbooks, uses RAG-enabled LLMs to auto-generate structured continuity plans and executable runbooks, and pairs them with a test harness that runs scheduled tabletop and automated validation (including mocked failovers) while continuously capturing tamper-evident audit trails. The product would surface prioritized gap analyses and remediation workflows, produce audit-ready compliance artifacts for regulators and insurers, and be sold to mid-to-large enterprises under an approximate $30K ACV model combining software and professional services. This opportunity is timely: regulators and insurers are tightening requirements, buyers now demand outcome evidence rather than PDFs, and recent advances in LLMs and retrieval tooling make automated plan generation and repeatable testing technically feasible, supporting a roughly $6.0B market. To win in a medium-competition landscape you must emphasize audit-grade evidence, deep integrations with ITSM/CMDB/security tools, and rigorous validation to mitigate LLM hallucination and legal liability—clear strengths, but ones that require upfront investment in security, standards alignment, and longer enterprise sales cycles.