Ensuring security in the age of generative AI for product development

The Rise of Gen AI and Its Implications for Security

In today’s rapidly evolving market, the integration of gen AI into product development is not just a trend—it's reshaping how we approach product security. We are currently seeing firsthand the transformative impact of gen AI on the industry, and how organizations can navigate this new terrain effectively for continued growth.

The surge in AI capabilities brings a heightened risk of sophisticated threats that can exploit vulnerabilities in unprecedented ways. A proactive and holistic security strategy is imperative to safeguard products and protect users from potential breaches. As generative AI continues to advance, the urgency for robust security measures becomes more critical than ever, making it essential for companies to anticipate, understand, and mitigate these emerging threats to maintain trust and ensure a secure user experience.

Security risks associated with gen AI products can be categorized into various layers of the reference architecture, including application, infrastructure, and foundation models. These risks include sensitive data exposure, data poisoning, adversarial attacks, and model drift, among others. Addressing these risks requires a comprehensive security strategy that is integrated into the product development lifecycle.

Understanding today’s product security imperatives

In an industry (and era) where consumer trust is paramount, the security of a product directly influences its market success. Consumers are increasingly aware of data privacy and the security of the products they use. This heightened awareness, coupled with the rapid incorporation of gen AI in products, demands a robust approach to managing product security risks.

Product security risk encompasses the potential threats and vulnerabilities that could compromise the confidentiality, integrity, and accessibility of a product. These risks can lead to compliance failures, operational disruptions, data breaches, and more. Therefore, securing products from the design phase to launch and beyond is essential to minimize vulnerabilities and protect brand reputation.

Regulatory trends and the need for compliance

More stringent standards and regulations are being implemented to ensure product security and protect consumers. Notable developments include the EU AI Act and the USAI Executive Order, which reflect a proactive approach by governments to set the bar for AI and gen AI security standards. These regulations are not just about compliance; they are about building a foundation of trust with consumers who rely on the security of the products they use.

These regulations are coming from multiple angles, requiring companies to understand the intersection of the regulations and how to build trust with consumers while remaining compliant with security standards. For example, a platform leveraging AI to deliver better search results needs to ensure it is compliant under the Digital Marketplace Act (DMA) from a marketplace perspective which requires them to provide sellers with the data that is generated by their own activities. In addition to this consideration, under the EU AI Act, the platform needs to consider how it uses that data to drive recommendations and the safeguards that are required for the different levels of data.

By adhering to these regulations, the platform not only 44 enhances its operational integrity but also strengthens consumer trust. This trust is crucial for retaining customers and encouraging more frequent and diverse interactions on the platform, ultimately contributing to the platform's growth and reputation in the market.

How organizations can adapt and thrive

To navigate these challenges, organizations must take a proactive, risk-based approach. Our recent study, “Reinventing with a digital core” reveals that more than half of software and platform companies are addressing security in a more holistic way, at the core. This involves understanding the full spectrum of potential security risks associated with incorporating gen AI into the product lifecycle and implementing a comprehensive security strategy that addresses these risks from the core.

1. Establish a robust QA process: Our digital core research also revealed that 57% of software and platforms organizations have achieved a state of fully integrated security controls, automation, and monitoring, which is a critical step in this strategy. This process should aim to identify and address potential security issues before products reach consumers, thereby reducing the incidence of security breaches and maintaining customer trust. Nearly 60% of software and platforms organizations surveyed in our digital core study reported that they conduct advanced security testing on both IT and OT systems, ensuring comprehensive security coverage across the organization. Security should be integrated into the product development process from the beginning.
   
   
2. Invest in security from the start: Integrating security measures during the design and engineering phases—often referred to as "shifting left"—ensures that security is a foundational component of the product, rather than an afterthought. This approach significantly reduces vulnerabilities that could be exploited in later stages or after deployment. When security protocols are considered early in the product lifecycle, developers can identify and mitigate potential security flaws more effectively and at a lower cost.
   
   
3. Leverage advanced technologies: Our digital core research revealed that 56% of Software and Platforms organizations employ predictive analytics and threat intelligence for proactive mitigation while threat modeling. Utilizing advanced technologies and automation can enhance the efficiency and effectiveness of security measures. For example, AI can be used to automate the mapping of controls to regulations, reducing the manual effort required and allowing organizations to focus on strategic security initiatives.
   
   
4. Collaborate and share knowledge: In an environment where product security threats are evolving, no single entity can hold all the answers. Collaborative efforts enable the pooling of resources, insights, and expertise, which leads to a more robust understanding of emerging threats and more effective security strategies. Sharing knowledge across different teams within an organization ensures that security is a shared responsibility, not confined to the IT or security department. This internal collaboration fosters a culture of security awareness and empowers all employees to actively participate in safeguarding the company’s assets.
   
   Partnering with external companies and participating in industry forums can provide valuable insights into new security methodologies, tools, and practices. Such partnerships are crucial for staying ahead of adversaries and can lead to the development of standardized security practices. By sharing experiences and best practices, companies can collectively improve their defense mechanisms and respond more effectively to security incidents. Organizations should look to industry leaders, such as Google, which has made its gen AI safety framework publicly available, to learn from best practices and innovative approaches to security.
   
   
5. Holistic ownership: Product security, particularly when led by product owners and engineers in partnership with central security functions, is essential for creating a cohesive and effective security strategy. Product owners and engineers are intimately familiar with the technical nuances and operational contexts of their products, which positions them uniquely to identify and address potential security vulnerabilities from the outset.
   
   Their deep understanding of the product architecture and its use cases enables them to foresee how different security measures will impact product performance and user experience.
   
   Central security functions bring a broad perspective on security policies, compliance requirements, and the latest in security threats and defense mechanisms. By working closely together, product teams and security experts can ensure that security measures are technically sound and align with broader organizational security goals and compliance standards.
   
   This balanced approach builds proactive measures into the product without compromising functionality or user experience. It also ensures that security considerations are integrated throughout, from design through deployment and updates. Leading this collaborative effort from within the product teams, with support from security specialists, embeds security into the company culture, making it a fundamental aspect of product development rather than an external imposition. This integrated approach is crucial for developing products that are secure by design, meeting both customer expectations and regulatory demands.

Conclusion

The integration of gen AI into products is a game-changer that brings both opportunities and challenges. By understanding the landscape of product security risks associated with gen AI, staying abreast of regulatory changes, and implementing a proactive security strategy, organizations can protect their products, maintain consumer trust, and thrive in this new era of technological innovation. As we continue to navigate this complex landscape, the role of product security consultants becomes ever more critical in guiding organizations through the challenges and opportunities presented by gen AI.