FEATURE: TRENDS IN CYBERSECURITY SOLUTIONS
Modern day cybersecurity is being polarised by increasing levels of embedded AI, yet requires the skills of mature security administrators to derive the best results from these advanced solutions. AI and
Generative AI are making platforms intuitive and powerful and introducing usage of Natural Language
Processing. However, human oversight is important and teams need to be equipped with skills to understand, interpret, manage AI-driven security systems. Top executives from Acronis, Anomali, BeyondTrust,
Check Point, Cloud Box, Fortinet, GBM, Globant, Help AG, Infoblox, NETSCOUT, NTT, Palo Alto Networks,
Phosphorus, Positive Technologies, Proofpoint, Sophos, Tenable, comment on this polarisation.
From 2025 and beyond, cybersecurity solutions are expected to evolve to keep pace with rapidly interconnected systems and increasingly complex applications. A major trend is the surge in API security, driven by the need for seamless communication between modern applications and backend systems, especially as AI adoption grows across the region.
“ As businesses integrate AI into their operations, APIs become essential for enabling that communication, making their protection critical,” says Nikola Kukoljac, Vice President Solution Architecture, Help AG
“ Another innovation area is data security. As AI models require large datasets for training, there is now increased demand for data protection technologies like data classification, masking, and organisation to safeguard sensitive information,” adds Kukoljac.
Proactive and intelligent systems
AI and Generative AI are transforming cybersecurity by making platforms more intuitive and significantly more powerful. One major advancement is the use of natural language processing, which allows security professionals to interact with complex systems using plain English, eliminating the need for platform-specific query knowledge and accelerating adoption across teams.
AI is enhancing threat detection by analysing vast amounts of data in real time, identifying behavioural anomalies, and spotting early signs of attacks that traditional tools might miss.
Says Gerald Beuchelt, CISO Acronis,“ Following the popular rise and broad availability of LLMs since the early 2020s, cybersecurity vendors quickly began incorporating Generative AI into their offerings. This led to features like platform assistants, automated incident summarisation, and AI-assisted threat hunting.”
Today, vendors are developing more advanced applications, such as agentic AI capabilities for autonomous Security Operations Centres.“ At the same time, as the limitations of LLMs become better understood, we are seeing more intentional and practical feature design,” adds Beuchelt
“ Cybersecurity is about cleaning up the alphabet soup and converging into a unified, intelligent platform. In 2025, innovation means unified data platforms, not stitched-together stacks. The next frontier is about systems that think, learn, and act without compromise, at scale, speed, and precision,” says Alexandre Depret-Bixio, Senior Vice President, Anomali.
“ Cybersecurity innovation is defined by the convergence of intelligent automation, cloud-native defence and platform-driven architectures,” says Ram Narayanan, Country Manager at Check Point Software Technologies, Middle East.
“ The focus has shifted from reactive measures to predictive, adaptive security. Disruptive trends include quantum-resilient cryptography, Zero Trust models tailored for hybrid work and behavioural biometrics for identity assurance,” adds Narayanan.
As cyber threats become more sophisticated, the industry is moving toward integrated ecosystems that can self-heal, self-learn and scale dynamically. AI is becoming a crucial part of cybersecurity by boosting threat detection, automating tasks and speeding up responses. It can sift through enormous amounts of data to spot patterns and abnormalities, helping to stop security breaches.
Modern day cybersecurity: Enabled by AI, managed by human skills
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