In 2025 the cybersecurity playing field is shifting. The adversary is no longer only human – they’re increasingly aided by artificial intelligence (AI) agents that can reason, act and adapt. At the same time, defenders are facing an imperative: move from reacting to threats toward anticipating and dismantling them. The recent announcements from Google mark a major inflection for how threat intelligence and security operations will evolve.

Why this matters

Google has openly declared a vision of what they call the “agentic SOC” – that is, a security operations centre where intelligent AI agents work alongside (and in some cases ahead of) human analysts.
In their blog, Google states that agents will “identify, reason through, and dynamically execute tasks to accomplish goals — all while keeping human analysts in the loop.”
That shift means that the architecture of threat defence is changing:

• Tools will no longer just alert — they will act, triage, investigate, and perhaps even remediate.
• Intelligence will no longer be static reports — it will be embedded in workflows and decision-making logic.
• Manual toil will have to be dramatically reduced if defenders are to keep up with adversaries using AI.

For CISOs this is a strategic moment: either build towards this model or risk falling behind adversaries who already are.

What Google announced

Some of the key pieces from Google’s announcements that CISOs should be aware of:

• Agentic capabilities: Google introduced agents such as an Alert Triage Agent and a Malware Analysis Agent in their roadmap. These are designed to automatically triage alerts, gather evidence, analyze code/files, and produce verdicts or next steps.
• Unified Security Platform: Under the umbrella of Google Unified Security, Google is combining threat intelligence (including via Mandiant), cloud security, secure enterprise browsing and agentic AI into a single fabric.
• Curated detections & rule-packs: Based on findings from the 2025 edition of M‑Trends 2025 (which draws on 450,000 + incident investigation hours), Google is delivering detection rule-packs for common vectors such as exploits (33 % of breaches) and stolen credentials (16 %).
• AI protection for AI workloads: Recognising that organisations themselves are adopting AI, Google has extended protections to agent-and-model spaces — for example in their “AI Protection” framework.
• Open protocols and labs: Google is also moving toward interoperability via protocols such as Agent2Agent and Model Context Protocol (MCP), and launching its SecOps Labs to pilot early AI-security workflows.

What this means for your organisation

For CISOs, the shift to agentic threat intelligence implies both opportunity and risk. Here are key implications and recommended actions.

Shift from reactive to proactive/hunting mindset

Traditional SOC models emphasise detection of known signatures, manual investigation and periodic hunting. In the agentic architecture, hunting becomes continuous, automated and intelligent. Google’s blog emphasises: “the agentic SOC … will enable a greater focus on complex threats, helping to deliver autonomous security operations workflows and exponential gains in efficiency.”
Action: Ensure your SOC roadmap includes automation/hunting workflows, not just alerting. Evaluate how detection engineering, threat intel, and triage can be automated.
Consideration: Are you still spending too much analyst time on triage and false positives? Agentic models aim to reduce that burden.

Threat intelligence must embed into workflows, not only into reports

Google is shifting threat intelligence from “here’s a report, go figure out what to do” to “here’s intelligence, built into the system, ready to act”.
Action: Re-evaluate how your organisation integrates threat intel. Does your SOC platform ingest + operationalise intelligence (play-books, detection rules, automation)?
Consideration: If your intelligence feed still arrives as PDF documents or static dashboards, you may be lagging.

Make sure your AI/ML estate is secure

As your organisation itself adopts AI (large language models, generative systems, agents), adversaries will target these environments. Google emphasises AI protection (agent runtime threats, prompt injection, model/jailbreak risk).
Action: As a CISO you must assess not only traditional assets but also your AI/agentic environments. Identify:

• What agents or models are deployed?
• What are the attack surfaces of those assets?
• Do you have detection/response mechanisms in place for them?
  Consideration: Agentic AI introduces novel risks (for example, agent-to-agent interaction vulnerabilities, autonomous decision-making). The research community is already exploring “secure and verifiable agent-to-agent interoperability”.
  Here the implication is: you may need new risk frameworks to cover agentic systems.

Prioritise interoperability and open frameworks

Google’s announcements emphasise open protocols (Agent2Agent, MCP) and a move away from vendor-lock-in.
Action: When selecting or evolving your SOC/THREAT-INTEL stack, favour systems that interoperate via open APIs and can integrate agentic behaviours.
Consideration: A fractured stack or siloed intelligence that cannot be operationalised rapidly may hinder your ability to move at machine-speed.

Re-think metrics, budget and staffing

With agentic intelligence, the measurement of SOC effectiveness will shift. Metrics like “alerts handled” or “tickets closed” may become less meaningful; instead outcomes such as “time to detection”, “time to containment”, “hunting coverage” and “percentage of triage automated” may matter more.
Action: As a CISO, review your KPIs and budgets for the SOC and threat-intelligence teams. Ask:

• What proportion of our workload can be automated?
• Are we re-investing manual effort into more strategic tasks?
• Can we redeploy analyst time toward complex investigations or strategic threat-reduction?
  Consideration: Agentic systems aim to free up human effort — don’t lose the opportunity to uplift your team’s role rather than simply cut headcount.

Challenges and caveats

While the promise is significant, there are also important caveats that CISOs must address.

• Governance & human-in-the-loop: Even autonomous agents must operate under control, with auditability and human oversight. Google emphasises transparency of agent reasoning and audit logs.
  Risk: If you deploy agents without proper governance, you may introduce new attack surfaces, blind spots or inadvertent errors.
  Mitigation: Implement oversight, logging, validation and human-fallback processes.
• Model/adversary arms-race: Attackers are also leveraging AI. The agentic model is not just a defence play — it’s two teams racing. Google’s announcements imply that defenders must match adversary speed.
  Risk: If your organisation lags, you may find your SOC overwhelmed by adversaries with superior automation.
  Mitigation: Evaluate your maturity now. Build the roadmap; partner with vendors; allocate investment.
• Data quality and pipelines: Agents depend on quality inputs — good telemetry, clean threat-intel feed, robust data fabric. If your data is poor, your agentic model will falter. Google emphasised data-management as a component of the agentic SOC.
  Risk: Automation amplifies flaws; noisy data or mis-engineered rules may cause errors at scale.
  Mitigation: Invest in data hygiene, telemetry completeness, unified logging and context enrichment.
• Skill shift: Analysts will need new skills — e.g., orchestration, agent-tuning, detection-engineering, prompt-engineering, AI governance. The role of “Tier1 triage” may decline.
  Risk: Without training, you may have a mismatch between tools and people.
  Mitigation: Upskill your team; redefine roles; partner early with your vendor ecosystem.