TLDR: Software spending is projected to achieve double-digit growth through 2029, primarily fueled by advancements in cybersecurity and artificial intelligence. Cloud security and identity and access management tools are key drivers, insulating the market from economic pressures. The integration of AI, particularly generative and agentic AI, is transforming security strategies, creating both opportunities and new vulnerabilities.
Global software spending is on a robust trajectory, anticipated to experience double-digit growth through 2029, with cybersecurity and artificial intelligence (AI) emerging as the primary catalysts. According to a report by Forrester, strategic investments in cloud security and identity and access management tools have played a crucial role in shielding the market from potential economic disruptions, including tariff-induced shocks.
The surge in cybersecurity spending is a direct response to an escalating threat landscape. Gartner forecasts global cybersecurity spending to reach an impressive $213 billion in 2025, a significant increase from $193 billion in 2024, with projections indicating a further climb to $240 billion by 2026. This sustained growth, estimated at 15.1% year-over-year for information security spending from 2024 to 2025, is driven by sophisticated cyberattacks, evolving regulatory mandates, a persistent talent shortage in the cybersecurity workforce, and widespread cloud adoption.
AI’s influence is multifaceted, acting as both a defensive and offensive force. The AI cybersecurity sector alone is projected to grow from $31.48 billion in 2025 to $93.75 billion by 2030, demonstrating a compound annual growth rate (CAGR) of 24.4%. This growth is spurred by the rising costs of data breaches, which averaged $4.88 million in 2024, compelling organizations to adopt AI solutions for real-time threat detection, automated responses, and predictive capabilities.
Leading technology companies are heavily investing in AI-driven security. Check Point has introduced new AI-infused prevention tools and cloud security modules. Microsoft has enhanced its Defender and Sentinel capabilities, integrating Copilot for Security to accelerate threat detection and response. SentinelOne launched an autonomous AI engine to boost endpoint protection and threat-hunting accuracy, and its Purple AI platform leverages large language models (LLMs) to simplify threat detection. Other innovators like Darktrace and IBM’s Watson for Cyber Security utilize natural language processing to analyze attacker behavior. Cisco CEO Chuck Robbins noted that network traffic is expected to reach ‘unprecedented levels’ as agentic AI and inferencing workloads proliferate, driving hardware refreshes.
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However, the rapid deployment of AI also introduces new challenges. An Infosys survey indicates that nearly all business leaders have experienced at least one problematic incident tied to AI, highlighting the critical need for responsible AI practices. Research from Zenity Labs reveals that AI agents are highly vulnerable to hijacking attacks, which could be exploited for data theft and manipulation. Despite low reported AI-related breaches, an IBM survey found that businesses reporting incidents often lacked proper access controls, leading to broader disruptions. This underscores the importance of robust AI governance frameworks to mitigate security risks and ensure responsible innovation.
