COMMENTARY: For more than a decade, enterprises have been drowning in point products, dozens of tools stacked on top of each other, each promising visibility, automation, or analytics.Yet none of them delivered what organizations actually needed: outcomes.In 2026, that will change. AI will become the operating system for cybersecurity, IT, and enterprise workflows, not just a mere assistant. And the companies built on agentic architectures — not cloud-first or workflow-first models — will rewrite the rules.[SC Media Perspectives columns are written by a trusted community of SC Media cybersecurity subject matter experts. Read more Perspectives here.]Here are the seven trends that will define AI in 2026 — and why they signal the most significant shift since the rise of cloud computing.Expect the market to enter a once-in-a-generation transition in 2026. The companies that win will build for an agentic, AI-native world — not those that bolt AI onto legacy workflows. AI will become the new architecture, agents are the new workforce and in 2026, enterprises will finally realize the old stack cannot compete with what comes next.Anurag Gurtu, chief executive officer, AirrivedSC Media Perspectives columns are written by a trusted community of SC Media cybersecurity subject matter experts. Each contribution has a goal of bringing a unique voice to important cybersecurity topics. Content strives to be of the highest quality, objective and non-commercial.
- Point-product cybersecurity will collapse: Point products have officially reached their saturation point. Enterprises now run 70–120 tools across security and IT, yet still struggle with alert fatigue, analyst burnout, and fragmented data. In 2026, the market will finally acknowledge what insiders have known for years: no single-feature product can compete with an AI system that can read, reason, act, and improve over time. AI agents are now capable of executing complex workflows end-to-end, from threat detection to investigation, response, and audit. Instead of stitching together dashboards, enterprises will shift to horizontal, agentic platforms that break down silos. This is the first year CISOs begin sunsetting tools rather than adding more. Expect the valuation gap between AI-first platforms and legacy cybersecurity vendors to widen sharply. A wave of consolidation will follow.
- Agentic platforms become the new digital workforce: The upcoming year will see the rise of agentic platforms in which systems composed of autonomous and semi-autonomous agents collaborate, learn from feedback, and deliver operational outcomes. Unlike chatbots or workflow engines, agentic systems operate more like digital workers: They understand enterprise context; coordinate across identity, endpoint, network, and cloud; adapt from human reinforcement; and reduce manual workloads by orders of magnitude. For enterprises, this means the first real path to scalable digital labor. For vendors, it means the next $50–100B category has emerged. By the end of 2026, agentic platforms will become the most sought-after acquisition target for hyperscalers and cybersecurity giants, the same way cloud platforms were a decade ago.
- Legacy vendors lose ground: Legacy enterprise software companies built around rules engines, ticketing systems, or static analytics will face their toughest year yet. The problem isn’t that they lack AI features. It’s that their architectures were never designed to support reasoning systems that operate continuously and autonomously. AI-first companies move faster, deploy faster, and deliver outcomes traditional vendors simply can’t match. Their systems require fewer integrations, learn from operational behavior, and collapse dozens of workflows into a single agentic mesh. In the upcoming year, customers will start questioning why they need four to five categories of tooling when a single AI-native system can do the work. Expect several well-known cybersecurity and IT vendors to see revenue declines, restructuring, or to become acquisition targets.
- Token costs collapse and AI becomes nearly free: The economics of AI will shift dramatically in 2026. Token costs, the basic unit of LLM inference, will drop by 70–90% as specialized AI hardware, quantization techniques, and MoE-based architectures mature. The cost reductions will transform the industry. Once inference becomes cheap, always-on agents become feasible. Security operations, IT workflows, compliance cycles, and monitoring systems will all run continuous, AI-driven processes that were previously cost-prohibitive. Cheap tokens unlock a new era: AI not as a feature, but as infrastructure.
- China shifts the global balance with its new LLMs: The Chinese will introduce LLMs that rival and in some cases surpass the performance of leading Western models at a fraction of the training and inference costs. Chinese labs have leaned heavily into low-precision training, lightweight architectures, massive multilingual corpora, and integrated agentic reasoning modules. These models will expand quickly across Asia, Africa, Latin America, and emerging economies, forcing Western enterprises and regulators to confront a new competitive reality: AI supremacy is no longer regional. The global cost curve for AI will fall even faster, and the competitive pressure this creates will be profound.
- AI talent wars escalate: The war for AI talent was intense in 2023–2025 and will reach a new peak in 2026. Microsoft, Google, OpenAI, Anthropic, Amazon, Meta, and a handful of elite AI-first startups will offer compensation packages that break previous benchmarks. Top-tier LLM researchers, agentic system architects, and reinforcement learning experts will routinely receive $10M–$20M+ packages. Many companies will bring on highly-skilled people via acquisition. Many legacy vendors simply won’t be able to keep up. Without competitive talent, they’ll struggle to innovate and will fall even further behind AI-first competitors.
- Cybersecurity and AI converge: Cybersecurity and AI will converge, ceasing to function as separate domains. SOCs won’t just use AI — they will operate with AI. Agentic systems will have the following features: suppress alerts automatically, run investigations in seconds, correlate exposures across cloud, identity, endpoint, and network, generate remediations, validate changes, and maintain continuous controls. By the end of 2026, large enterprises will see 30% or more of SOC workflows executed by agents, not humans.
