From predicting future through the usage of historical data combined with statistical modelling, to using data mining techniques and machine learning, among others, Predictive AI is something which seems to have gained the attention of regulatory bodies, which deals with laws and regulations in business. Experts believe that AI-driven predictive analytics can play a proactive role in identifying potential threats, giving legal institutions the opportunity to strengthen their preventative defences before data breach-related threats create an impact. “With predictive AI-based security measures and automation solutions, legal entities stand poised not only to abate the susceptibility to breaches but also to mitigate the ensuing financial reverberations. This approach can safeguard both reputation and financial stability, which can be a crucial endeavour in an increasingly digital and interconnected economic landscape,” Jitender Ahlawat, founder, managing partner, HJA and Associates LLP, a legal advisory service firm, told FE Transform-X.
Industry experts believe AI and automation have significantly impacted data breach costs, by mitigating them. The global average cost of a data breach now is $4.45 million. Only 28% of organisations have used AI-based security extensively, which eventually reduced the costs related to data security. The average savings for organisations which used AI-based security and automation is $1.76 million in comparison to organisations that didn’t, as per a recent report by IBM.
Interestingly, AI-powered security tools are expected to enhance defence mechanisms. The market for artificial intelligence (AI) is expected to reach a value of nearly $100 billion and is expected to grow up to nearly $2 trillion by 2030, as per insights from Statista, a market research firm.
From what it is understood, these innovative technologies have the potential to enhance the legal sector by safeguarding sensitive client information, intellectual property and classified data, among others. Experts believe in contrary to this the combined use of such functions could need legal liabilities, erosion of trust and the imposition of financial penalties. “AI and automation might complicate liability and regulatory compliance. However, strong AI governance and accountability can be achieved through stricter data protection laws. Use cases such as the European GDPR restricts decision-making for data protection solely through automated processing, and provides the right to obtain human intervention.” Garima Mitra, co-founder, Treelife, a legal and finance firm, explained.
However, it is believed that this can also increase costs further and a balance between innovation and legal safeguards needs to be implemented as AI’s role in the data age evolves. “In the realm of cybersecurity, the integration of extensive security AI and predictive analysis isn’t just a defence mechanism but also can redefine the legal sector. The true measure of its impact is not just avoiding breaches, but allowing real-time responses that curtail financial vulnerabilities. Moreover, together they has the ability to create resilience against the financial impact of a breach,” Trishneet Arora, founder, CEO, TAC Security, a cybersecurity platform, concluded.
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