Assessing the Potential of AI for Project Success in Cybersecurity
How To Leverage AI The Right Way
How to Leverage AI the Right Way
Predictice Analytics and Large Langugae Models are apparently the next big thing — also in Cybersecurity.
However, not every security inititative should be powered by AI. While it is certainly a powerful technology that can empower Cyber Defense and Offense capabilities alike, deciding which initiatives to tackle with AI can be challenging.
To solve this problem, here are some major criterias for evaluating each opportunity.
Big Picture:
The first factor to consider when prioritizing problems for AI is how it fits to the organizations big picture. How does the opportunity fit into your company or department’s overall goals and strategic plan? Will it increase revenue or cut costs? How might this change the products and services that your company offers? Typically, opportunities are evaluated against a mid- to long-term time horizon.Opportunity Size:
The second factor to consider is the opportunity size. Is the opportunity big enough to warrant an AI solution, or can an older technology or your employees adequately solve the problem? Conversely, even if this specific opportunity can be solved more cheaply or easily with human power for now, can an AI-based solution be leveraged for similar tasks in the future?Investment Level:
The third factor to consider is the investment level required. How much time and money will you need to allocate toward the problem? Don’t forget to include internal costs, such as project management and opportunity costs, in your evaluation.Return on Investment
While the return on investment (ROI) is never certain, you should estimate an upper and lower bound and a likelihood of success. Understand your break-even number and the internal costs for project management and opportunity costs in your evaluation.Risk:
The fifth factor to consider is the risk. What is the likelihood that this project will succeed and deliver on the projected ROI? Set the performance level that a new technology needs to achieve to be deemed successful. Also, consider the industry risk of your competitors adopting AI for a core function. Would you lose your competitive advantage if you failed to take action?Business Stakeholders:
Finally, consider if other business stakeholders are bought into the AI solution. Most projects will require an interdepartmental effort to gather data, train systems, launch new products, and maintain performance. Furthermore most AI projects require at least a few months of investment before producing positive results for your business.
The weighting of each factor will change depending on your business priorities. Overall, prioritizing problems for AI is a challenging task, but by considering these factors, you can make informed decisions that mitigate the risk to project failure in future.
About Tobias Faiss
Tobias is a Senior Engineering Manager, focusing on applied Leadership, Analytics and Cyber Resilience. He has a track record of 18+ year in managing software-projects, -services and -teams in the United States, EMEA and Asia-Pacific. He currently leads several multinational teams in Germany, India, Singapore and Vietnam. Also, he is the founder of the delta2 edventures project where its mission is to educate students, IT professionals and executives to build a digital connected, secure and reliable world and provides training for individuals.
Tobias’ latest book is ‘The Art of IT-Management: How to Successfully Lead Your Company Into the Digital Future’. You can also contact him on his personal website tobiasfaiss.com