Rehan Jalil is CEO of cybersecurity infrastructure and data protection company SECURITI and former head of Symantec’s cloud security division.
AI and the use of business data with AI are at the heart of the future of innovation; however, this carries significant risks. Businesses are grappling with risks associated with shadow AI, data privacy breaches, cybersecurity threats, and unethical use of AI. Navigating this complex terrain requires methodical safeguards to govern, manage and secure the use of AI.
Risks of generative AI in business
The growing impact and complexity of generative AI not only exacerbates existing challenges, but also adds a layer of concern around AI governance. Companies are increasingly concerned that using these systems could result in a loss of control over their data, potentially exposing sensitive information and jeopardizing their regulatory compliance. Actually, 63% of practitioners are unprepared to face the risks associated with generative AI.
Many businesses are hesitant to adopt AI due to fears over data privacy and security. They fear losing control of the information they provide to AI systems. This could lead to leaks of sensitive data, exposing customers and the company itself. Additionally, businesses fear that AI systems will introduce new vulnerabilities into their networks, making them more vulnerable to cyberattacks.
Regulators are also imposing stricter guidelines to ensure compliance with evolving global AI regulations, including NIST IA RMFTHE European AI law and many other regulations in countries like Canada, China, Brazil and Singapore. Successfully navigating this regulatory environment requires proactive measures to promote transparency, accountability and ethical conduct throughout AI development and deployment.
Building a robust AI security and governance framework
Given these challenges, taking a proactive stance on AI governance becomes paramount. Companies should prioritize the development and implementation of robust AI governance frameworks focused on protecting data privacy and security.
These frameworks should encompass comprehensive risk assessments, ethical guidelines and regulatory compliance measures. By integrating governance and security principles into all stages of AI development, organizations can cultivate a culture of responsible data use and mitigate potential risks associated with emerging technologies.
To address and mitigate the complexities associated with AI deployment, organizations are taking a multifaceted approach. This includes meticulously identifying and documenting officially sanctioned and unauthorized AI systems in a variety of environments such as public and private clouds and Software-as-a-Service (SaaS) platforms. This effort aims to expose covert AI operations and the risks they pose.
A critical part of this strategy is conducting in-depth assessments of AI systems in the context of regulatory benchmarks and potential dangers, including issues of content toxicity, bias, operational inefficiency, copyright infringement, author and dissemination of false information.
To ensure comprehensive oversight, there is an ongoing commitment to mapping and monitoring AI systems, tracing their connections to data origins, processing frameworks and associated service providers and identifying both risks and regulatory compliance requirements.
Additionally, implementing sophisticated data and AI management practices is crucial. This includes anonymizing data before use in AI systems, establishing access controls and integrating large language model (LLM) firewalls, protecting sensitive data throughout its lifespan. life cycle.
Unlocking potential through security, governance and trust
Fostering a culture of security and governance in AI is essential. This philosophy, focused on responsibly harnessing AI capabilities, has the potential to significantly improve risk management protocols, ensure regulatory compliance, build consumer trust, and drive innovation . By committing to ethical deployment and rigorous AI governance, businesses are able to harness the vast potential of AI.
This approach protects against potential pitfalls and amplifies long-term value creation. By 2025, I believe that a focus on transparent, trustworthy and secure AI practices will result in a substantial increase in technology adoption, goal achievement and user satisfaction, highlighting the vital importance of ethical engagement in AI.
Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Am I eligible?
