AI Adoption Is Inevitable: How to Balance Innovation with Security Risks

According to EY, 96% of enterprises are planning to use AI in the next 12 months, compared to 43% today.

Integrating AI and large language models (LLMs) into business operations unlocks new possibilities for innovation and efficiency, offering the opportunity to grow your top line revenue, and improve bottom line profitability. As with any new technology, however, security must be designed into the adoption of AI in order to minimize potential risks. Many AI-related components and tools are still in their infancy; these applications have the potential to expose sensitive corporate data, and the top down push to develop AI-powered applications is forcing development teams to compress already aggressive timelines. The combination of new technology with a short window makes security even more difficult than with traditional applications.

This furthers the opportunity for hackers to target AI systems, exploiting vulnerabilities that can compromise data integrity, operational functionality, and regulatory compliance. How can you close security gaps related to the surge in AI apps in order to balance both the benefits and risks of AI?

The Importance of Securing AI by Design

AI systems handle sensitive personal, financial, and proprietary information, so unauthorized access or manipulation can have damaging repercussions. It is important that organizations can confidently build and use AI-powered apps, while also prioritizing the integrity of AI security frameworks from development to deployment.

The need for robust security measures is underscored by several key factors.  AI and LLMs process vast amounts of sensitive information, including personal data, financial records, and proprietary business insights, making data sensitivity a critical concern. Unauthorized access to this data can lead to significant financial losses, legal consequences, and reputational damage. Moreover, AI systems are integral to automating and optimizing business operations, and a security breach could compromise these systems, resulting in operational disruptions, decreased productivity, and impaired decision-making. Additionally, as regulations surrounding data protection and AI usage become increasingly stringent, businesses must ensure compliance with relevant laws and standards.

Impact of Robust Security Solutions

With so much at stake, you need a solution specifically designed to protect enterprise AI apps, models and data from both AI-specific risks or threats and foundational network risks, including those that traditional cloud security solutions might not cover.

Palo Alto Networks AI Runtime Security is purpose-built to automatically discover your AI applications, models and data and defend against threats. It addresses the challenges inherent in the secure deployment of AI in business applications in several unique ways:

1. Discover Your AI Ecosystem: AI Runtime Security enables you to map out your entire AI application ecosystem. This includes all applications, models, data sources, users, plug-ins, and internet exposure across your cloud environment. By providing a detailed view of this ecosystem, the solution helps you understand how your AI applications interact with models and other data, and where weaknesses must be mitigated.
2. Protect Against Threats: AI Runtime Security defends against both known and zero-day AI-specific attacks. Powered by Palo Alto Networks Precision AI security services, and backed by the industry’s leading threat research team, AI Runtime Security protects against prompt injection, sensitive data leakage, malicious responses, and more. This robust protection ensures that your AI applications are safeguarded from attackers seeking to exploit the new risks that AI components bring to an application infrastructure.
3. Monitor for New Threat Vectors – With both threats and your applications constantly evolving, it’s critical to vigilantly protect and continuouslymonitor the runtime risk exposure of your AI ecosystem. With AI Runtime Security, you can analyze your AI Runtime risk posture, evaluate new and unprotected AI applications and identify risky communication pathways from AI applications.

As businesses increase their development and deployment of AI applications, securing these technologies is more critical than ever. Enterprises can manage AI risks at every step of the journey with AI Runtime Security. It is a comprehensive solution to protect AI systems from a range of threats, ensuring their safe and effective use, and paving the way for secure innovation and growth in today’s rapidly evolving technological landscape.

Committing to a platform approach is not just about better security and lower costs to operate, it is also a means of delivering innovation at the pace enterprises need. Network security teams can now deliver Secure AI by Design- learn more here.