While companies are enticed by the potential benefits of generative artificial intelligence (AI), from helping enhance data analytics, increase efficiency, and reduce administrative tasks, to name a few, cybersecurity leaders are cautious about the potential challenges that may arise in an already precarious environment.
Just a year and a half ago, the use of gen AI in the enterprise was minimal. However, a study published in May by research firm International Data Corporation (IDC) found that 65% of companies had begun using gen AI, which increased to 71% by September. An additional 22% planned to adopt it within the next year. Moreover, cloud-based gen AI tools like ChatGPT have made gen AI adoption nearly ubiquitous across companies.
The widespread adoption of gen AI, coupled with the pressure from CEOs and boards, is causing security leaders to lose sleep. Threat actors are exploiting generative AI to orchestrate large-scale social engineering attacks, create more realistic deepfake audio-visual content, develop sophisticated self-evolving malware strains, and launch phishing attacks. They understand that they must keep up or risk being left behind.
Sanjoy Paul, Senior Technology at Hero Vired, a Hero Group Company into digital training, mentioned that generative AI significantly increases the risk associated with password security, enabling cybercriminals to crack passwords more effectively, especially weak or reused ones. It also introduces new forms of malware that can bypass traditional security systems, posing a significant challenge to cybersecurity defenses.
IT networking firm Cisco’s 2024 Data Privacy Benchmark Study, published in January, revealed that organizations have several concerns regarding the use of Gen AI. The top concerns include threats to an organization’s legal and intellectual property rights (69%) and the risk of information disclosure to the public or competitors (68%).
Despite these concerns, most organizations recognize the need to reassure their customers that their data is being used only for intended and legitimate purposes in AI. However, little progress has been made in addressing these concerns.
Dev Stahlkopf, Cisco’s Chief Legal Officer, emphasized that Gen AI must be viewed as a fundamentally different technology with unique challenges that must be addressed. He stressed the importance of thoughtful governance in preserving customer trust.
A Deloitte report published in January also echoed similar concerns about Gen AI. It revealed that only a quarter of leaders believe their organizations are adequately prepared to address governance and risk issues associated with Gen AI adoption. Additionally, only 47% agree that their organizations are effectively educating employees about the capabilities, benefits, and value of Gen AI.
It is also necessary to bake in security in every product, such as encryption, believes Sudip Banerjee, field chief technology officer (CTO) for APJ, Zscaler, explains. “Oftentimes, IT developers think about decreasing costs and speeding time to market when they are building applications on the cloud. However, integrating the security functionality in the cloud product in the early stages can help reduce security risks,” he said.
“As more companies integrate coding tools into their technology stack, monitoring tools to ensure results meet expectations is crucial,” believes Rakesh Ravuri, CTO and SVP – Engineering at Publicis Sapient. CIOs who provide generative coding tools with a solid code base will find that their teams generate better code using the same tools.
Furthermore, jobs in gen AI are on the rise. With generative AI sparking enthusiasm across industries, the demand for professionals skilled in AI and machine learning (ML) is increasing in India.
Staffing firm Randstad reports that hiring for AI and ML roles has been growing by 30% annually since the pandemic, while demand for other digital skills has been increasing at half that rate. It is estimated that there are approximately 200,000 professionals skilled in AI/ML in the country.
As generative AI continues to evolve, roles such as AI cloud architects, AI data engineers, AI ethicists, and AI security professionals will become more prominent. However, these skills require continuous upskilling to be used effectively and securely, said Ravuri.
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