Artificial Intelligence (AI) tools have the potential to transform industries, but in the wrong hands, they can become powerful tools for cybercriminals. From deepfakes to phishing and ransomware attacks, malicious actors are using AI to target organizations in every industry, and across the world.
As AI-driven cyber threats grow more sophisticated, it’s more important than ever for organizations to prioritize cyber defenses and allocate funds to invest in it. Looking ahead to 2025, here are the key AI-driven cybersecurity trends to watch.
1. AI-powered Threats
AI-enabled malware and phishing schemes are becoming increasingly sophisticated, allowing attackers to tailor their tactics to exploit specific technical vulnerabilities. In the coming years, expect more AI-powered attacks that can adapt in real-time and evade traditional defenses, making them more challenging to mitigate.
To stay ahead of these threats, organizations must invest in AI-driven security tools that can detect and respond to attacks quickly and effectively. Transitioning to quantum-safe encryption methods and adopting a Zero Trust security model will also be critical to ensure that systems remain secure. As AI-driven cyberattacks become more common, businesses that fail to adapt may become easy targets for increasingly sophisticated hackers.
2. Data Privacy and User Information
One of the biggest ongoing concerns for businesses is the potential for data breaches caused by improper use of AI tools. With the ability to process vast amounts of data, AI systems can inadvertently expose sensitive information – if not carefully managed.
Employees using AI platforms can unknowingly input confidential data – such as financial reports or client information – into unsecured AI systems. These platforms could store and process this data in ways that open the door to potential breaches, especially if this data is accessed by unauthorized users. In response, organizations must implement stricter controls over AI usage, ensuring that tools are used safely and within the boundaries of organizational policies and privacy regulations.
With the advent of new regulations governing data privacy, including the EU’s AI Act regulation and the SEC’s cybersecurity disclosure rules, businesses will face increasing pressure to comply with legal data protection frameworks. These regulations are designed to strengthen security postures, but they also add layers of operational complexity which requires major investment in compliance efforts and security infrastructure.
3. AI in SaaS Solutions
The integration of AI into Software-as-As-Service (SaaS) platforms is changing how businesses manage security. For example, AI-enhanced tools are helping organizations automate threat detection, analyze vast data sets more efficiently, and respond to breaches or incidents more quickly. However, this innovation also introduces new risks such as hallucinations and an over-reliance on potentially poor data quality, meaning AI-powered systems need to be carefully configured to avoid outputs that mislead and are disadvantageous to defenders.
Third-party AI tools also risk introducing significant data and intellectual property (IP) risks to organizations, particularly through data mishandling and unauthorized access. To mitigate these threats, businesses must ensure that SaaS providers implement adaptive, robust security measures to protect sensitive information. Key AI-driven solutions include:
- Data Leakage Prevention (DLP) tools to detect unauthorized sharing and access
- Identity and Access Management (IAM) platforms to monitor account behavior and flag suspicious activity
- Cloud security vulnerability assessment tools and reviews to proactively identify risks
- Encryption tools for secure data handling with robust automated key management.
4. AI Governance and Accountability
As 2025 approaches, establishing clear internal business guidelines for the ethical use of AI will be vital, not only for compliance but for building trust. Businesses must ensure that AI systems are transparent, unbiased, and accountable for their actions, especially when it comes to security decisions. Proactivity here is key – business leaders should not wait for regulatory mandates to implement robust AI governance policies. By establishing their own guidelines now, they can pre-emptively address potential risks and build a secure, ethical foundation for AI that can adapt to future compliance requirements.
AI auditing tools will help organizations assess whether AI models are making decisions based on biased or discriminatory data – a concern that could lead to legal and reputational challenges. As AI technology becomes more embedded in organizational operations, ethical considerations must be at the forefront of AI governance to help businesses avoid unintended consequences.
Board members must be proactive in understanding the implications of AI on data security and ensuring that their companies are following best practices in AI governance for compliance with evolving legislation. Without C-suite support and understanding, and collaboration between executives and security teams, organizations will be more vulnerable to the potential risks AI poses to data and intellectual property.
5. Regulatory Changes
The growing presence of AI in cybersecurity will bring with it a surge in new regulations. Governments and industry bodies are already introducing new regulations to ensure that AI is used responsibly and securely. For example, in the U.S., the Securities and Exchange Commission (SEC) is pushing for greater transparency and accountability in AI use, particularly in areas like financial services and consumer protection.
These new regulations will place additional pressure on organizations to ensure their AI systems comply with privacy and security standards. Compliance will require continuous monitoring and adaptation to ensure that AI systems are not only secure but also transparent and fair in their operations.
To be fully prepared for the security challenges of 2025 and beyond, businesses must evaluate their IT spend to make way for cybersecurity and AI compliance investment. Using an analytics and insights engine can help optimize IT spending to reduce waste and unlock funds for investment in crucial cyber defenses. 
Laurence Dale is CISO at Surveil – an analytics and insights engine – which can help optimize IT spending to reduce waste and unlock funds for investment in crucial cyber defenses. Throughout his 25-year technology career, Laurence has gained invaluable global experience through several senior IT leadership roles. Laurence has been responsible for driving the digital, security, and commercial capabilities of multi-national organizations across the FMCG, technology, and manufacturing industries, as well as the UK public sector. In 2017, Laurence took the position of Chief Information Security Officer (CISO) at Essentra PLC., where he led the cyber-risk and privacy management transformation programs. This was followed by a promotion to Group IT Director (interim CIO), leading the global IT team through two major divisional divestments.