By Dana Simberkoff, Chief Risk, Privacy and Information Security Officer, AvePoint
In the past, many organisations thought of their data as being static and finite; a pile of information to store, safeguard, and protect. While data security of course remains paramount today, AI has fundamentally changed the way that organisations must approach data protection. Because LLM-driven tools need a strong bedrock of optimised and secure data to operate efficiently, enterprise and personal data now require more dynamic and careful governance on a continual basis.
It’s no longer enough to lock up your data and closely guard the key. To succeed in the AI era, organisations will need to go beyond traditional security measures and adopt much more proactive, dynamic approaches to data governance and security.
How AI Alters Data Security
The arrival of artificial intelligence has completely disrupted traditional methods of safeguarding data and information.
Before AI, there often weren’t severe consequences for maintaining large, disorganised data estates with unregulated sensitive data. With AI, however, that’s no longer the case. Deploying AI in an environment teeming with disorganized or sensitive information—ranging from long-forgotten contracts to confidential specifications—poses genuine risks, like the accidental oversharing of confidential information. If not properly managed, AI could inadvertently expose private details, overstep regulatory boundaries, or damage client relationships. That’s to say nothing of AI-driven attacks themselves, which require proactive governance and continual monitoring.
To confront these challenges, it’s crucial for organisations to implement rigorous approaches to data anonymisation and removal of identifying details. They should also set up systems that enable the automatic tagging and classification of new data according to sensitivity, which prevents the most sensitive data from escaping containment.
By thoroughly preparing and securing information before AI is integrated, companies can prevent potential privacy violations and foster a culture where innovation and responsibility go hand in hand. These are the kinds of changes that data security professionals need to make to succeed in the short- and long-term.
Data Protection for the AI Age: 3 Actionable Strategies
Here are three key steps to strengthen your organisation’s information protection in the AI age:
1. Think Critically About Data Retention
Carefully evaluate your data estate and ask tough questions about what’s needed and what isn’t. How long should a particular kind of piece of data remain in storage? What might happen if it’s compromised? Set clear steps for keeping and disposing of data, and in general try to limit the amount of unnecessary data that your organisation stores.
A thoughtful approach to data retention and destruction considers not just compliance, but also the operational and ethical dimensions of data retention. Regular audits, policy reviews, and engaging stakeholders across the business can ensure that data is kept only as long as it serves a real purpose: minimising risks and supporting secure, responsible AI integration.
2. Anonymise Data and Institute Guardrails
Prioritize careful data cleansing and anonymisation before introducing AI into your systems. To use AI securely, you should also establish comprehensive, multi-layered security protocols to insulate sensitive information, ensuring that the power of AI can be harnessed without endangering privacy or regulatory compliance. This includes routine data audits, robust encryption, and access controls that are updated as technology evolves.
By weaving privacy-by-design principles into every stage of your data lifecycle, you empower your organisation to innovate with confidence, knowing that risks are actively managed. A proactive approach to data governance not only safeguards your assets but builds trust with users and stakeholders.
3. Don’t Fight AI Adoption
AI is already here, and your employees are likely to use it with or without authorisation. According to McKinsey, over 70% of organizations already use AI. Because it’s now a norm, many employees will use and/or demand it regardless of whether or not your company has widely adopted.
Acknowledge that your employees will use AI with or without authorization and invest in training, tools, and processes to integrate it responsibly. Maintain human oversight to catch biases or errors and foster a culture of trust and transparency with your customers and employees. These steps will limit risk and ensure that your
AI is Here; Act Now to Stay Secure
Cybersecurity is now an essential pillar for business survival. As AI rapidly develops, our strategies for protecting data must adapt just as quickly. Instead of waiting to react to new risks, organizations must take the initiative and address them head-on.
The way companies navigate and manage this AI-driven transformation will shape their future success. By focusing on strong data lifecycle management, modern security practices, and ongoing education, businesses can set themselves up to flourish in this new era while safeguarding their most crucial asset: information.
