Cybersecurity in the AI Era

The era of artificial intelligence has brought forth many questions about applicability, opportunities and challenges, which society – businesses, people and governments alike – is now navigating. Understandably, we place significant importance on the ethical implementation of AI and the large language models that it uses to work.

These ethical considerations range from AI’s explicability, its transparency, the privacy protections that are in place for its use, how robust it is, and how it is calibrated to offer fair outputs. 

In addition to these ethical pillars, leaders across companies and industries need to begin thinking about how to implement artificial intelligence in lockstep with a comprehensive cybersecurity strategy. Doing so is as relevant to ensure people (employees and users alike) are protected, to comply with data governance schemes that ensure operational sustainability, and to contribute to the potential for growth that AI for business represents.

The Cost of a Data Breach 

The latest report commissioned by IBM on the cost of data breaches in Latin America shows that, on average, a data breach can cost as much as US$2.76 million, which represents a staggering 12% increase over  last year. For certain companies, the cost can be even higher; for example, in the industrial sector, the cost reached US$3.54 million on average, the financial sector showed a data breach can reach a cost of US$3.22 million on average, and the services sector showed an average of US$2.9 million. 

These aren’t just numbers that look shocking on a page. They are a reality that exists today and that leaders, cybersecurity experts, and technology experts face – and manage – daily. But the cost of a data breach is not only felt within organizations, since the cost of these incidents is usually transferred to consumers. Sixty-three percent of organizations worldwide stated that they would increase the cost of goods or services due to a breach this year (versus 57% last year). This marks the third consecutive year that the surveyed organizations stated that they would take this action.

If we inspect these numbers, it is clear that unless a top-notch cybersecurity strategy is put in place, this cycle of cost-generation will continue hurting both companies and their  internal and external clients. 

Where Do AI and Cybersecurity Meet? 

The relation between AI and cybersecurity is much like that of the egg and the chicken. AI has pushed the possibility to automate processes and to replicate imagery so considerably that we now need cybersecurity for AI. However, at the same time – and precisely because of the advancements of artificial intelligence – we also need to apply it to cybersecurity processes and paradigms. 

In short, this technology era requires that we think about implementing AI for cybersecurity and cybersecurity for AI.

The report I have referenced here also shows that AI plays a crucial role in reducing the impact of data breaches on Latin American organizations, with 31% of companies in the region now widely using AI-powered security and automation to prevent and address breaches, which has led to a reduction in life cycles. In fact, organizations with extensive use of AI-powered security and automation experienced breaches that were 83 days shorter on average, compared to those not using these technologies.

The implementation of AI in cybersecurity is as important as it is imminent, and the types of actions that organizations can implement with the help of AI are already a realit including: 

1. Anomaly Detection: AI-powered systems can identify patterns and anomalies in network traffic, allowing for early detection of potential threats.

2. Predictive Analytics: AI-driven predictive analytics can forecast potential attacks, enabling organizations to take proactive measures to prevent breaches.

3. Automated Incident Response: AI-powered incident response systems can quickly respond to security incidents, reducing the risk of data breaches.

The capacity to accelerate cybersecurity efforts and methodologies is not just a matter of catching up with the times or the competition, but rather a key action that can have direct impact on the potential cost of cyberthreats and data breaches. According to the “The Cost of a Data Breach” report, the average life cycle of a leak is 301 days in Latin America. However, companies that took less than 200 days to identify and contain a breach incurred an average cost of US$2.4 million. On the contrary, leaks with life cycles greater than 200 days cost US$3.12 million, on average.

Evidently, there are clear financial benefits to closing the gap between AI for cybersecurity and vice versa, and while this is an important motivator that should be considered in companies’ digital transformation and financial planning, it is also incredibly relevant to consider that the AI era requires that organizations navigate new challenges and landscapes. It's essential to prioritize cybersecurity awareness, training, and AI-powered security measures, not just to continue pushing growth forward, but to benefit technology users, and to make their lives better.