Are your AI and cyber security strategies in lockstep?

As we are now in the last week of October 2024 for ‘Cybersecurity Awareness Month’ we have thought about the most important thing companies should be aware of. And the winner is …. AI!

Australian businesses now know that they need to embrace AI technologies in order to remain competitive. The technology is already having a profound impact on everything from businesses’ ability to enhance customer experiences, to creating more efficient and reliable supply chains.

But jumping into AI without careful consideration of the new risks and your existing cyber security framework and posture might endanger your business. 

Here’s the top 6 cyber security considerations before deploying AI

1. Increasing Threat Landscape

The explosion of AI technologies has also been accompanied by a rise in the number and sophistication of cyber threats.

Hackers are leveraging AI to develop smarter, more sinister ‘weapons’ rendering traditional security measures increasingly redundant. For example, adversaries are employing machine learning algorithms to identify vulnerabilities, automate attacks, and even to help craft more beguiling phishing schemes.

As AI systems become more integral to operations, the attack surface expands, underscoring the need for robust cybersecurity measures during the development and deployment phases.

 2. Data sensitivity and privacy

AI systems typically need large datasets to be effective.

And often they can contain highly sensitive information about individuals, or proprietary business data. It goes without saying that inadequate security risks data breaches, exposing sensitive information with all the resulting legal and reputational issues that usually follow.

Australia has quite stringent cyber security regulations, with failure to comply attracting heavy fines, and increasingly harsh media scrutiny elevating the issue beyond tech teams to the board.

Companies must therefore prioritise cybersecurity to protect sensitive data and ensure compliance during every step of their AI journey.

3. Bias and ethics

Cybersecurity is about more than just protecting data within AI systems: It also need to take account of the ‘integrity’ of AI models.

For example, AI systems can inadvertently perpetuate bias, leading to unfair or unethical outcomes, which malicious actors can manipulate.

Using techniques like ‘adversarial attacks’, they can exploit biases or alter decision-making processes to their advantage, potentially resulting in discriminatory practices in hiring, lending, or law enforcement.

AI systems, those with questionable integrity can expose organisations to inaccurate outputs or even total system failures. This can have serious implications, especially in sectors like healthcare where compromised AI systems can seriously jeopardise patient safety.

By properly embedding cybersecurity into the AI design process, businesses can mitigate against these risks and promote ethical AI use.

4. Supply chain risks

AI systems often depend on third-party vendors and integrations, which can increase cybersecurity vulnerabilities. For instance, a breach in a third-party system can have a domino effect on organisations.

This means that companies deploying AI solutions must devise a fully comprehensive cybersecurity strategy that considers the entire supply chain before its deployed. This includes properly communicating with all partners and ensuring that they adhere to rigorous cybersecurity standards, so as to mitigate risks associated with external vulnerabilities.

While of course something of a truism, it’s still important to stress that cyber security isn’t just about technology. It’s also about ‘people’.

In any organisation, employees play an increasingly critical role in maintaining security protocols, especially with so much use of digital tools and platforms, from email to SaaS applications.

User experience therefore needs to be taken into account when designing AI solutions, while organisations must ensure that staff are adequately trained to understand best practice cybersecurity when using AI tools.

This might include helping staff to recognise potential security threats, or better understanding the importance of data privacy. Ultimately, a culture of security awareness can significantly reduce the risk of human error, which is often a primary factor in cybersecurity incidents.

A robust cybersecurity posture contributes to long-term business sustainability and resilience. A single data breach can lead to financial losses, hefty fines, legal repercussions, and reputational damage, any of which can take years to recover from, if businesses recover at all.

By embedding cybersecurity into the core strategy and the design and deployment of their AI solutions will not only protect their assets but also build customer trust and loyalty. This proactive approach can differentiate businesses in a competitive landscape where consumers are increasingly concerned about data privacy and security.

In conclusion, just as AI is transforming businesses of all type and size across every industry, it’s also redrawing the cyber security landscape, demanding new thinking and approaches to ensure the technology is a boon, and not a ‘bust’ creating new risks that can actually threaten a business.

If you would like to discuss your security requirements to ensure your data and staff are protected email here to get in contact with one of Enablis’ security experts.