Understanding the modern cybercrime landscape

2026-05-19 · Source: MIT Technology Review · Field: Technology & Digital — Cybersecurity & Data Privacy, Cloud Computing & IT Infrastructure, Artificial Intelligence & Machine Learning · Depth: Intermediate, short

Summary

HPE Threat Labs' "In the Wild" Report, based on 2025 observations, highlights the industrialization of cybercrime, characterized by automation, AI use, and corporate hierarchies to achieve greater scale, speed, and structure in campaigns. The report identifies five key factors shaping the contemporary cybersecurity landscape. These include rising expectations for network performance and security from users and leadership, coupled with financial pressures on CISOs to achieve more with less. Further complicating matters are increasingly complex, multivendor IT infrastructures resulting from digital transformation, and unpredictable geopolitical and economic conditions impacting budgets and supply chains. Finally, evolving cyber threats saw governments as the most targeted sector globally in 2025, followed by finance, technology, defense, and manufacturing, driven by espionage and organized crime. The report advocates for leveraging AI-driven network platforms for automated security management, policy enforcement, and threat mitigation.

Key takeaway

For CISOs and IT professionals planning cybersecurity strategies, the industrialization of cybercrime and the five dynamic landscape factors necessitate a re-evaluation of your network's role. You should embrace AI-driven network platforms to automate security policy enforcement, threat monitoring, and mitigation. This approach transforms your network into a powerful security sensor, improving defenses against sophisticated attacks while managing IT costs and simplifying operational oversight.

Key insights

Cybercrime is industrializing with AI and corporate structures, necessitating AI-driven network security to counter five dynamic landscape factors.

Principles

• Cybercrime operates with industrial scale and structure.
• Network reliance increases security expectations.
• Complex IT environments demand integrated defenses.

Method

Implement AI-driven network platforms for 24x7 automated security policy enforcement, threat monitoring, and mitigation across devices, users, and "things".

In practice

• Use the network as a security sensor.
• Apply zero trust policies automatically.
• Analyze data for dynamic protection.

Topics

• Cybercrime Industrialization
• Cybersecurity Landscape
• AI-driven Security
• Network Security
• Zero Trust
• Geopolitical Risk

Best for: Executive, Security Engineer, IT Professional, CTO

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Editorial summary, takeaway, and curation by AIssential. Original article published by MIT Technology Review.