Everyone everywhere is experimenting with AI, or at least talking about it. It is touted as having the power to transform many aspects of business, including productivity and customer service. However, while AI may not be a panacea, there are certain areas where AI is expected to make a big difference.
One such area is Business Continuity and Disaster Recovery (BCDR), which has historically relied on multiple tools, processes, and plans that require continuous testing and refinement.
“AI has a lot of potential in these areas because it can gather information about what is happening in the environment, parse logs, and suggest solutions in plain English,” said Enterprise. said Christophe Bertrand, Senior Analyst at Strategy Group.
What are the benefits of AI in BCDR?
AI offers many benefits for business continuity and disaster recovery.
First, AI can greatly enhance BCDR planning by improving organization and providing guidance. Whether a company is rewriting an existing plan or creating a new plan, AI can be used to analyze ISO standards, professional best practices, and other relevant documents to create a solid starting point for planning. increase.
Strata Results Group senior project manager Jason Rubens highlighted the effectiveness of generative AI in evaluating BCDR plans. In a blog post, Rubens explained that he had asked ChatGPT to evaluate the plan against the standards of the Federal Financial Institutions Review Council (FFIEC). ChatGPT he absorbed the FFIEC Business Continuity Plan booklet and identified potential gaps and areas for improvement.
“This is very surprising, especially considering how much effort it takes for humans to extract this kind of information from standards and review plans for gaps,” said Rubens. mentioned in a blog post.
AI also has valuable applications in analyzing business impact and conducting risk assessments. Not only can AI analyze machine logs and other related documents, but it can also identify data interdependencies that can cause problems over time.
In the event of a disaster, timely and accurate communication is critical, and AI can help expedite this process. “One of the big problems people face during a disaster is getting accurate information and not getting misinformation, rumors or duplicate information,” says Betty, a business continuity management consultant at Kildow Consulting. Kildow explains. “When data comes in from so many sources, AI can be very helpful in classifying the data much faster and better than what humans can do.”
Additionally, AI can be widely applied to decision-making scenarios such as incident response. You can assess various aspects of an incident, including the impact of the incident, and make recovery and evacuation recommendations as needed. AI is also ideal for forecasting, as it can provide decision makers with a high-level perspective on current and potential risks.
Another important use case for AI is automating the testing, modeling, and execution of business continuity and disaster recovery plans. For example, AI can suggest specific scenarios for testing or executing a plan and trigger reordering of activities.
Finally, AI can help restore both business operations and technology. On the business side, AI can initiate incident-related actions such as contacting members of staff or deploying devices to off-site locations. Similarly, on the technology side, AI will enable failover procedures, allowing technology resources to migrate from remote locations or the cloud.
In all these applications, AI is actively working to make environments more resilient and make data more manageable.
“[AI] On the one hand, we are influencing the larger story of business intelligence and analytics, and on the other, we are increasing the integration of cybersecurity resilience processes through automation,” Bertrand said.
AI is a tool, not a magic solution
AI will make a big difference to both the operation and management of BCDR, but its effectiveness depends on the availability of accurate, high-quality data inputs.
This doesn’t always happen. “AI is not magic. bobby williams Former Senior Manager of Disaster Recovery at Advance Auto Parts, now Business Continuity/Team Leader at Cyber Security Consulting Firm. “For example, if you document an outage with the tag ‘summer high power outage,’ you cannot infer anything other than that it was an outage.”
In other words, the quality of input determines the quality of output. “It’s amazing, but the heart of AI is tools,” says Kildow. “This is a hammer and we still have to manage it.”
To determine whether AI will benefit a particular organization, a small implementation can be used as a point of comparison with what is already in place. Kildow suggested using AI for risk assessment. This is a task most organizations are already working on. Evaluating the output of an AI tool and comparing it to existing evaluations can reveal its effectiveness.
The bottom line is that AI is still evolving and improving. Over time, as the technology matures and its benefits and limitations become more apparent, AI is likely to be accepted and integrated into standard practice.
“We saw the same thing early on with business continuity software,” Kildow said. “When this first came out, it had the same backlash that I see with AI today.
