Disaster Recovery Journal Fall 2024

The Benefits of a BCP-Driven Approach n Accelerated AI adoption : Leverage

u Aggregate and preprocess data from various sources, including BCP documentation, DRP test results, and other relevant business systems. u Consider augmenting your data with external sources if necessary to improve the accuracy and robustness of AI models. 4. Pilot project at recovery site: u Select a non-critical process or a smaller component of a critical process for your initial AI pilot project. u Leverage your disaster recovery site as a controlled environment to test and refine the AI solution before deploying it in live operations. u Gather feedback from users and stakeholders during the pilot to identify any issues or areas for improvement. 5. AI model development and validation: u Work with AI experts to develop and train AI models tailored to your specific business processes and goals. u Validate the models using a separate dataset to ensure their accuracy and effectiveness. u Iteratively refine the models based on feedback and performance metrics from the pilot project. 6. Integration and deployment: u Integrate the AI solution into your existing workflows and systems, ensuring seamless data flow and communication between AI components and other business applications. u Deploy the AI solution in a phased approach, starting with the pilot process and gradually expanding to other areas as confidence and experience grow. 7. Monitoring, maintenance, and continuous improvement: u Establish robust monitoring mechanisms to track the performance of your AI solutions in real time. u Regularly maintain and update AI models to ensure they remain accurate and effective as business processes and data evolve.

u Continuously gather feedback from users and stakeholders to identify areas for improvement and further optimization. Additional Considerations However, there are some key differ ences and additional considerations: n Granularity : BC/DR plans may not be as granular as needed for AI implementation. They often focus on the high-level steps and may not capture the nuances and variations that occur in day to-day operations. n Data accessibility : Data identified in BC/DR plans may not be readily accessible or in a format suitable for AI algorithms. Additional data integration and preparation efforts may be required. n Goals and objectives : BC/DR plans aim for business continuity and recovery, while AI implementation may have broader goals, such as efficiency improvement, cost reduction, or enhanced customer experience. While BC/DR plans are a valuable starting point, organizations need to: 1. Augment BC/DR information : Supplement existing BC/DR documentation with more detailed process information, real-time operational data, and insights from subject matter experts. 2. Adapt data for AI : Ensure that critical data identified in BC/DR plans is accessible and in a format AI algorithms can easily process and analyze. 3. Incorporate human factors : Consider

existing knowledge and data to streamline AI implementation.

n Targeted solutions : Focus AI efforts on the most critical areas of your business. n Improved risk management : Proactively identify and mitigate potential risks associated with AI. n Enhanced efficiency and productivity : Optimize processes and automate tasks to improve overall performance. n Mature foundation : Tying your AI adoption to a program your organization has matured, updated and tested regularly over a long period, increasing the chances of fast and successful adoption. n Competitive advantage : Gain a competitive edge by leveraging AI in a strategic and responsible way. Conclusion By harnessing the power of your busi ness continuity plan and disaster recovery procedures, you can unlock a strategic roadmap for AI integration that is both efficient and effective. This approach not only accelerates AI adoption but also ensures AI solutions are aligned with your business goals, mitigate risks, addresses regulatory compliance and contributes to long-term resilience and success. If all this sounds like too much to you. Simply invite key members of your AI integration team to the next DR test and let them see for themselves. In the ever-evolving landscape of AI, including a BCP-driven approach can be the key to staying ahead of the curve and harnessing the full potential of this trans formative technology. v

the impact of AI on employees and incorporate their feedback into the implementation process.

Erik Borgen is a business continuity man ager, turned Investor, with a rare perspec tive on what is currently happening with AI adoption. His investor side simply got tired of waiting. He wondered, “Why is it taking

4. Align goals : Clearly define the goals and objectives of the AI implementation and ensure they align with the overall strategic priorities of the organization, not just with BC/DR goals.

so long for organizations to make good use of this tech nology?” On the BC side, Borgen considered how some organizations struggle to integrate AI may be able to ben efit from utilizing artifacts they have already created. This may enhance the speed and accuracy of AI adoption while anchoring it responsibly in a mature risk-based framework. Faster, better, cheaper, and reduced risk. Why not?

16 DISASTER RECOVERY JOURNAL | FALL 2024