Redazione RHC : 19 September 2025 07:14
By Umberto Pirovano, Senior Manager Technical Solutions at Palo Alto Networks
Generative Artificial Intelligence (GenAI) is redefining the technology and business landscape at an astonishing rate. According to Palo Alto Networks’ report “The State of Generative AI in 2025,” GenAI traffic is expected to surge more than 890% in 2024. This explosive growth is attributable to the maturation of AI models, increasing business automation, and increased deployment, driven by increasingly evident productivity returns. The increase in adoption and use marks a definitive shift: GenAI is no longer a novelty, but an essential utility.
According to Research by the Artificial Intelligence Observatory of the Polytechnic University of Milan, in 2024, GenAI drove the artificial intelligence market in Italy: a full 43% of spending on this type of solution was exclusively on GenAI or hybrid projects, which also included traditional AI.
However, this rapid expansion brings with it significant challenges, particularly regarding data security. GenAI-related data loss prevention (DLP) incidents have more than doubled: by 2025, the average monthly number increased 2.5-fold, now accounting for 14% of all data incidents. GenAI applications amplify a growing vector of information loss, as unauthorized or careless use can lead to intellectual property leaks, regulatory compliance issues, and breaches.
Companies detected an average of 66 GenAI applications in use, 10% of which were classified as high risk. The widespread use of unauthorized tools, the lack of clear AI policies, and the pressure to rapidly adopt this technology—without adequate security controls—can expose businesses to significant risks.
The majority of GenAI transactions (83.8%) come from four main use cases: writing assistants, conversational agents, enterprise search, and developer platforms. These tools are popular among employees because they directly perform daily, repetitive tasks. Writing assistants, for example, support users in the various stages of writing, from drafting emails to generating posts to creating reports. Conversational agents, on the other hand, offer instant, natural language responses to a wide range of questions, making them useful for customer service, learning, and productivity.
It’s clear that GenAI technologies are already having a positive impact in numerous areas, as highlighted in the Gartner report “Inform Your Generative AI Strategy With Healthcare Provider Case Examples.” In the healthcare sector, for example, automated clinical documentation, clinical decision support, and personalized patient care pathways are among the areas that can be cited.
Even in Italy, crucial sectors such as Oil & Gas are experiencing a significant impact. Gas, financial services, insurance, and healthcare industries, which manage and store highly sensitive data and information, are integrating GenAI into their operations to optimize operations, streamline processes, and increase efficiency and productivity. However, their use poses an inherent risk given the potential for users to enter sensitive information, thus exposing it to theft or exfiltration. Indeed, despite having applications controlled and protected by their company, not all employees use them, relying instead on third-party apps, perhaps perceived as more efficient, convenient, or simply easier to use.
By virtue of its advanced predictive analytics capabilities, artificial intelligence also represents a fundamental pillar of prevention. By processing historical data and real-time information, AI systems are able to predict and flag potential issues before they can lead to negative consequences. For example, in the financial context, this translates into the ability to detect fraudulent transactions, mitigating economic losses; in healthcare, AI can help save lives by predicting patient outcomes and suggesting appropriate preventative measures.
Artificial intelligence is an emerging technology that is attracting considerable interest. However, it is crucial to be aware of the potential challenges and complexities it entails. With an increasing number of companies experimenting with third-party GenAI apps, it’s important to fully understand the risk landscape:
In conclusion, while GenAI offers unprecedented opportunities for innovation and efficiency, it is imperative that enterprises take a proactive and strategic approach to risk management. Awareness, user training, and the implementation of robust policies and concrete security measures are essential steps to fully exploit the potential of GenAI and protect your most valuable asset: data.
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