Forrester recently published a report, “Generative AI: What It Means For Security”, that explores the implications of generative AI (GenAI) on cybersecurity. It emphasizes the need for security leaders to understand the impact of GenAI, identify potential security challenges, and learn how to adopt it safely at the enterprise level.
The complimentary report highlights some of the opportunities and challenges of GenAI:
Third-party risk management
The surging popularity of GenAI tempts employees to use the technology to enhance productivity. However, without proper management and training, this can lead to leaks of protected information. The report emphasizes the need for organizations to have thorough security protocols in place to mitigate these risks.
The surging popularity of generative AI programs tempts users and employees alike to use the technology to boost their productivity. Companies that lack proper management of and training for employees on how to use external AI tools risk leaking protected information.
Challenges of trust
Among individual security practitioners, the adoption of GenAI may trigger the anxiety of possible job loss or the fear of making mistakes through the incorrect use of AI tools. Leaders must allay these concerns by showing how GenAI can be used to accelerate basic tasks, allowing teams to focus on more complex goals. Building trust and encouraging adoption is a leadership test that must be handled with care.
Enhancing incident detection
Generative AI offers the potential to boost detection capabilities and reduce the backlog for detection engineering teams. It enables security personnel without a full developer skill set to perform detection-as-code-related tasks, enhancing the overall efficiency and effectiveness of security operations teams.
Improving reporting capabilities
GenAI can automate report generation, reducing human error and the monotony of manual report creation. It has the potential to massively reduce the time needed to produce reports, freeing up time for humans to handle more complex, nuanced problems.
Risk management best practices
Generative AI can generate playbooks or checklists, recommending actions to guide analysts. By outputting plain text recommendations, it provides underlying context and reasoning, aiding in better decision-making and accelerating detection and response.
Best practices around GenAI include:
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Extending current governance measures and training teams on best practices around GenAI. Understanding the short and long-term security implications of this emerging technology is vital, and the report emphasizes the need for a fundamental understanding of the underlying cycle: identify, protect, detect, respond, and recover.
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Adopting and deploying detection-as-code principles. Learning these requirements now will pay off later, and the report encourages thinking about augmenting current security products and services with GenAI.
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Exercising caution and not rushing to adopt GenAI. Ensuring that existing security and data architectures are equipped to handle GenAI functions is crucial. The report warns against seeing GenAI as a panacea and emphasizes the need to solve more pressing security problems first.
Our three key takeaways
To successfully adopt GenAI within an enterprise environment, Forrester recommends:
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Mindfulness and preparedness: Organizations must be mindful of the risks and prepare thoroughly by implementing proper security protocols and governance measures.
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Trust and adoption: Building trust is essential for the successful adoption of GenAI. Leaders must communicate the benefits and address concerns effectively.
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Strategic use: GenAI must be strategically used to enhance detection, reporting, and decision-making capabilities without rushing into adoption.
Generative AI is a transformative technology with far-reaching implications for cybersecurity. While it offers significant benefits in detection, reporting, and automation, it also presents new challenges that require careful consideration and strategic planning.
By supplying a nuanced understanding of the landscape, the report serves as an essential resource for those looking to navigate the complex world of generative AI in the context of cybersecurity.
Check out the full report here.
