An AI powered approach to data security and privacy

Data is one of the most valuable commodities that a business has, so they have a duty to ensure that customer and staff data is protected at all costs.

The task of protecting that data has admittedly become more challenging over recent years, with data security and privacy risks increasing in both volume and cost. IBM's recent data estimates that the global average cost of a data breach in 2023 was $4.45 million. But these breaches go beyond the financial risk, they jeopardise reputation and customer trust, which can have a costly long-term impact on businesses.

The cost of failing to protect data

When a data breach occurs, the repercussions can be severe. Businesses may face large regulatory fines, encounter significant costs for remediation, and may face legal fees.

Beyond the immediate financial burden, failing to protect customer data can put long-term relationships at risk, as customers wariness of data protection may view the loss of data as a breach of trust and leave. This damage extends further, impacting a company’s reputation in the industry and directly impacting the bottom line as a result.

As of January 2024, about 21 percent of organisations in the United Kingdom reported experiencing a data breach accident once a month, highlighting how common these breaches are in the business sector.

As data threats are becoming more frequent and sophisticated, data privacy and

protection protocols need to keep pace.

To effectively combat these challenges, businesses should set robust data protection policies to ensure that data is collected, stored and handled in a trustworthy way, mitigating the risk of data loss and ensuring customer data remains protected. These policies must also draw from wider data policies, such as GDPR, to ensure data compliance at all times.

The role of AI in protecting data

Many businesses have adopted AI to enhance the efficiency of tasks such as data analysis, forecasting and customer services through AI-powered chatbots. However, AI can also play an important role in improving the management, security and protection of data, both internally and for customers.

This is especially true given that 90 per cent of the world’s data has been created in the last two years alone, and is set to continue rising exponentially, so traditional methods of data management need to evolve.

AI’s ability to sift through vast amount of data and identify patterns, or anomalies when it comes to breaches, goes far beyond human capacity.

This capability enables faster detection of abnormal activities, significantly enhancing data protection efforts. AI tools can analyse large data sets, identify malicious files and URLs, and recognise phishing attacks, providing crucial support to tech teams.

AI excels in real-time threat detection and predictive analytics.

Automation is another significant advantage offered by AI in data protection. AI can autonomously identify anomalies, detect unusual activity, and either automate responses or alert IT teams to investigate further.

Commitment to Privacy and Security

It is important to develop AI with a focus of ethical guidelines and robust data privacy measures. In KPMG's ‘Corporate Data Responsibility: Bridging the Consumer Trust Gap’ report, 60 per cent of consumers believe that companies often misuse their personal data.

When using AI as part of the solution, KPMG’s research highlights the need for businesses to place data privacy and security at the heart of AI development, ensuring that systems respect and protect customer data adhering to stringent ethical standards and privacy protocols.

Since phishing attacks are on the rise, companies must do more to reduce the risk for customers. One of the most effective applications of AI in data security is its ability to detect and prevent phishing attempts through machine learning. AI analyses communication patterns and identifies suspicious activities that may indicate a phishing attack. For example, Zoho's secure QR code sign-ins, powered by AI, offer a safer method of user authentication by reducing the risk of unauthorised access.

Transparency and trust should be fundamental within data policies and AI implementation, intersecting to ensure that data privacy and security are at the heart of business operations and, ultimately, keeping customer data safe. Data is among the most valuable assets a business possesses, so they have an obligation to protect customer and staff data at all costs.

This commitment not only enhances customer loyalty and satisfaction but also boosts the company's reputation, mitigates the risk of costly data breaches, and provides a competitive advantage in the marketplace. Prioritising transparency and trust can help businesses to achieve sustainable growth and long-term success.