TLDR: A 2025 report by ipoque, a Rohde & Schwarz company, in collaboration with The Fast Mode, reveals that Deep Packet Inspection (DPI)-driven traffic intelligence is crucial for the effective deployment of Generative AI (GenAI) in network management. The report identifies security risks and poor data mechanisms as major challenges, with 92% of vendors concerned about GenAI-related threats and 89.3% facing issues with data collection and analysis. DPI is highlighted as a key enabler for accurate network and traffic analytics, essential for training and fine-tuning GenAI models.
A new report, ‘Advancing network management with generative AI: The role of DPI-driven traffic intelligence,’ published on September 1, 2025, by ipoque, a Rohde & Schwarz company, in collaboration with The Fast Mode, underscores the critical role of Deep Packet Inspection (DPI)-driven traffic intelligence in the evolution of network management through Generative AI (GenAI).
The study, based on a survey of 75 leading networking vendors, identifies significant hurdles in GenAI adoption. The most prominent concern, affecting 92.0% of vendors, is security risks associated with GenAI, including the poisoning of training data and query-based data exposure. Following closely, 89.3% of vendors reported challenges with poor mechanisms in data collection, classification, and analysis, leading to critical gaps in the data and analytics used for GenAI. These issues include inaccurate categorization and labeling, conflicting data, and incomplete traffic capture.
Deep Packet Inspection is presented as an indispensable technology for overcoming these data-related challenges. According to Ariana Leena Lavanya, Principal Analyst at The Fast Mode, “Accurate network and traffic analytics are critical in training, testing and fine-tuning generative models such as LLMs, GANs and VAEs, as well as in providing references for models such as RAG. These insights are also important in enhancing user prompts and queries during inferencing.”
ipoque’s next-gen DPI engines, R&S®PACE2 and R&S®vPACE, are highlighted for their ability to provide real-time application and threat awareness. These engines integrate advanced classification techniques, encrypted traffic intelligence (combining machine learning and deep learning), and a rich set of Key Performance Indicators (KPIs) to identify traffic flows regardless of encryption or obfuscation. Martin Mieth, Director Network Analysis at ipoque, emphasized that their DPI solutions meet the essential criteria for GenAI implementations: scalability, real-time analytics, and seamless embeddability into traditional, cloud, and virtualized environments.
The report also reveals a growing trend in DPI adoption, with nearly half of the surveyed vendors having already deployed DPI, and two-thirds anticipating deployment within the next five years.
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In a broader industry context, the Generative AI in Telecom market is experiencing rapid expansion, with projections indicating a growth from $0.48 billion in 2024 to $0.73 billion in 2025, reflecting a compound annual growth rate (CAGR) of 53.5%. This surge is fueled by increasing demand for GenAI-powered chatbots, smart city initiatives, expanding digital penetration, and the proliferation of Internet of Things (IoT) devices. Experts predict that by 2025, GenAI will evolve beyond a co-pilot function to become an automation-driven enabler, facilitating autonomous reasoning, recommendations, and actions across network operations, customer interactions, and service management. This transformation is expected to lead to fully autonomous networks, with AI automating tasks, optimizing performance, and enabling proactive issue resolution. Furthermore, GenAI will be crucial in managing and optimizing hybrid network systems, including the increasing integration of satellite networks.
