Organizations are increasingly recognizing the need to leverage artificial intelligence (AI) to maintain a competitive edge. A recent MIT Technology Review Insights report highlights the growing imperative for businesses to keep pace with advancements in AI capabilities. However, this rapid adoption presents significant security challenges. The surge in the volume, velocity, and variety of security data, compounded by fragmented toolchains, is making it difficult for security and data teams to maintain a proactive and unified security posture. Data and AI teams face the challenge of rapidly delivering business results while simultaneously ensuring robust security and governance. Delivering securely on data and AI strategy requires a comprehensive approach that prioritizes threat detection and response against an expanding attack surface, insider threats, and supply chain vulnerabilities.
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Official guidance: NIST — official guidance for Delivering securely on data and AI strategy
Background Context
The pressure to innovate with AI is immense, but organizations must not compromise security in the process. Melody Hildebrandt, chief technology officer at Fox Corporation, emphasizes the importance of balancing innovation with security, stating, “I’m passionate about cybersecurity not slowing us down, but I also own cybersecurity strategy. So I’m also passionate about us not introducing security vulnerabilities.” This sentiment reflects the broader challenge of integrating AI while maintaining a strong security posture. Delivering securely on data and AI strategy is not merely an option but a necessity for sustained business success.
Nithin Ramachandran, global vice president for data and AI at 3M, notes that generative AI has reshaped the security landscape. “Our experience with generative AI has shown that we need to be looking at security differently than before,” he says. “With every tool we deploy, we look not just at its functionality but also its security posture. The latter is now what we lead with.” This shift underscores the need for a proactive, security-first approach when deploying AI technologies. The ability to effectively manage and protect data is a critical component of delivering securely on data and AI strategy.
Addressing Security Vulnerabilities in AI Deployment
A survey of 800 technology executives, including 100 chief information security officers, conducted in June 2025, reveals that many organizations struggle to balance the benefits of AI with its inherent security risks. This highlights the importance of implementing robust security measures throughout the AI development and deployment lifecycle. Delivering securely on data and AI strategy requires a holistic approach that addresses potential vulnerabilities at every stage, from data acquisition to model deployment and monitoring.
One key aspect of delivering securely on data and AI strategy is ensuring that AI models are protected from adversarial attacks and data breaches. Organizations must implement measures to prevent unauthorized access to sensitive data used for training AI models and to protect against techniques like model inversion and data poisoning. Furthermore, it is essential to establish clear governance policies and procedures to ensure that AI systems are used ethically and responsibly. This includes addressing potential biases in AI models and ensuring that AI-driven decisions are transparent and accountable.
The Role of Unified Security Posture
Maintaining a proactive and unified security posture is critical for organizations seeking to deliver securely on data and AI strategy. This involves integrating security tools and processes across different teams and departments to create a cohesive defense against cyber threats. A unified security posture enables organizations to detect and respond to threats more quickly and effectively, reducing the risk of data breaches and other security incidents.
Furthermore, delivering securely on data and AI strategy necessitates a focus on continuous monitoring and improvement. Organizations must regularly assess their security posture, identify vulnerabilities, and implement corrective measures. This includes conducting penetration testing, vulnerability assessments, and security audits to ensure that security controls are effective. By continuously monitoring and improving their security posture, organizations can stay ahead of emerging threats and protect their data and AI assets.
Future of Secure AI Implementation
As AI continues to evolve, organizations must adapt their security strategies to address new and emerging threats. Delivering securely on data and AI strategy in the future will require a focus on AI-driven security solutions that can automate threat detection and response, improve security intelligence, and enhance overall security effectiveness. These solutions can help organizations to keep pace with the increasing volume and complexity of cyber threats and to protect their data and AI assets more effectively.
The future of delivering securely on data and AI strategy also involves fostering collaboration between security and data teams. By working together, these teams can develop a shared understanding of the security risks associated with AI and develop effective strategies to mitigate those risks. This collaboration is essential for ensuring that AI is deployed securely and responsibly, and that organizations can realize the full potential of AI without compromising their security posture.
In conclusion, delivering securely on data and AI strategy is a critical imperative for organizations seeking to leverage the power of AI while mitigating security risks. This requires a comprehensive approach that prioritizes threat detection and response, establishes clear governance policies, and fosters collaboration between security and data teams. By adopting a security-first approach, organizations can unlock the full potential of AI and achieve their business objectives without compromising their security posture.
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