AI Governance for CISOs: How to Manage Risk Without Blocking Innovation
The governance of Artificial Intelligence has emerged as one of the newest challenges facing Chief Information Security Officers (CISOs).
It’s an aspect of the typical CISO remit that has only recently grown in both relevance and important due to the speed of AI’s evolution. PureCyber has already seen its huge impact on sensitive data, regulatory obligations, operational resilience, and business decision-making in our day-to-day work.
Naturally, security leaders are expected to lead the way when it comes to ensuring AI is used correctly, but there’s a delicate balance that must be struck for any CISO.
Many business leaders will be familiar with the pressure to leverage AI for productivity, innovation, competitive advantage, and cost reduction. But simultaneously, the adoption of AI technology is outstripping the ability of most organisations to govern it effectively, and with more solutions rapidly becoming embedded across all departments of a business, the associated risks rise with them.
So, with AI increasingly being used for everything from enhancing daily processes to influencing business decisions with big ramifications, where does that leave security leaders? Let’s take a look.
What does the AI risk landscape look like?
When it comes to external risk, organisations should be at least aware of these dangers, with the level of risk varying depending on your sector:
AI-powered Phishing - AI tools craft more realistic and personalised emails that are more likely to catch employees out.
Deepfakes - Digitally created or altered content such as images, videos and audio recordings made to trick employees into compromising their organisation.
Synthetic Identities - A growing form of identity theft blending real data (names, addresses etc) and fake information into a fake persona, building credibility/credit and then disappearing, often leaving hefty debts, bills or expenses behind that can’t be recouped.
Autonomous Cyber Attacks - the use of AI and machine learning to enhance phases of cyber attacks. In some cases, we’ve seen AI conducting attacks without direction or authorisation.
For internal risk, all organisations should be both aware and mitigating the impacts of the following:
Shadow AI - the unsanctioned or unapproved AI tech such as generative chatbots or browser extensions often expose an organisation to increased risk.
Data Leakage - throwing sensitive data into AI tools without appropriate guard rails has caught organisations out before, and is regarded as a huge data breach.
Governance Failures - the latest solutions may speed up processes, but without clear ownership, constant oversight and monitoring after deployment, they are almost certainly failing existing governance and increasing risk with each use.
While any organisation should have good visibility and understanding of the risks posed to them by AI, internal risks should be the primary concern because they remain largely within your control. Typically, governance controls, policies, and oversight mechanisms are often not implemented quickly enough to keep pace with AI adoption.
How can AI be governed effectively?
In a nutshell, AI governance requires a framework of policies, controls, accountability, and oversight that enables organisations to use AI safely and responsibly. When done correctly, effective governance creates visibility, accountability, transparency, and trust, while still enabling the crucial innovation that leaders are seeking.
As part of our AI Audit, PureCyber focuses on uncovering AI mismanagement within an organisation. Once we’ve uncovered the AI usage throughout the company, PureCyber helps with the creation and implementation and awareness of the policies and processes you’ll require for effective control of AI. Overall, these are some of the key aspects of AI governance that we encourage any organisation to consider:
Data access permissions and controls
AI safeguards to block unsafe solutions or content
Your existing compliance and regulatory requirements and how AI use impacts them
Before jumping into building that framework, a word of caution - organisations should approach the process of creating AI governance as a starting point that is regularly iterated from, not a one-time exercise. To be continuously effective, compliance needs to be treated as an iterative process, and the pace of AI’s evolution makes that approach even more vital. AI-powered technology and solutions can enhance all aspects of work, but as we’ve already noted, they simultaneously creating new compliance issues if not handled correctly.
The following points are also worth considering when it comes to implementing AI governance across your workforce:
Humans are still accountable for AI-driven tasks
Complete visibility of AI usage across your business is unrealistic
AI risk will evolve faster than your controls
Training and awareness exercises then become an essential part of your approach to successful AI governance and maintaining compliance. A workforce that understands how to use AI safely and compliantly is less likely to unwittingly create regulatory headaches or security breaches than one that isn’t. Given the difficulty in getting full visibility of AI usage; building awareness and setting expectations are essential, especially as a culture of trust cannot always account for damaging mistakes or malicious acts.
How can we help?
As organisations increasingly integrate AI into business processes, governance needs to be looked at as a continuous process that protects and enhances your organisation, as a compliance exercise. That means that the organisations best placed to succeed will be those that establish clear governance, maintain human accountability, and build trust whilst enabling AI-powered innovation.