Artificial intelligence has given hackers new ways to scale cyber attacks; operations by AI-enabled adversaries rose 89% year over year, and the average network breakout time from an initial foothold to other connected machines fell to just 29 minutes in 2025. However, AI is also simultaneously giving the good guys a greater ability to counter these growing threats.
Security operations centers (SOCs) and security information and event management (SIEM) solutions are increasingly adopting and adapting artificial intelligence tools of their own to keep pace with cyber attackers working at machine speed. SWK Technologies has put together this article to help your business understand how AI is changing SOC and SIEM work and where human analysts still fit:
AI in the Hands of Hackers
Artificial intelligence has not handed attackers a new playbook, but it has made familiar tactics like phishing faster and cheaper to run at scale. The median threat actor now researches or uses AI assistance across 15 documented attack techniques, with phishing accounting for 44% of AI-assisted initial access vectors. Most of that activity automates techniques defenders already know how to catch, so proven detection methods still carry most of the weight in your security stack.
One in four malicious breaches are now AI-enabled, and those incidents cost an average of $6 million, more than the almost $5 million average seen with other types of cyber attacks combined. However, businesses running artificial intelligence-powered security and automation in their own defenses have also cut down breach costs by almost $2 million on average.
Agentic Attacks and AI-Powered Malware
Some attackers have started handing entire campaigns to AI agents, with one state-sponsored group using agentic solutions to carry out 80-90% of an espionage campaign against roughly thirty targets. The same agent occasionally hallucinated credentials and overstated what it had stolen, the kind of mistakes a watchful analyst can catch when the activity reaches a monitored network.
Malware gangs have picked up the same habit, with several families now querying large language models while they run and an underground trade in illicit AI tools lowering the barrier for less experienced hackers. The most advanced of these strains is still experimental, though behavioral detection matters more every time malware gains the ability to change its own code between infections.
Behavioral Analytics in SIEM Technology
SIEM platforms have always collected and correlated log data from across your network, though rule-based correlation only catches the patterns someone thought to write a rule for in advance. Behavioral analytics build a baseline for each user, host and application, then score activity that strays from it so analysts can start with a spike in failed sign-ins instead of the oldest alert in the queue.
Generative artificial intelligence adds a plain-language layer on top, letting analysts summarize complex alerts and turn a written question into a query across your security data. Junior staff can leverage this to sniff out related activity without writing query-language scripts by hand, which will enable you to shorten the gap between an alert being triggered and reacting to it.
AI-Assisted Triage in the SOC
Inside the SOC, artificial intelligence increasingly handles the first pass of triage that analysts used to perform by hand for every alert in the queue. Agentic triage tools investigate alerts, add threat intelligence context and return a verdict with an explanation, while analysts keep control of high-impact actions like isolating a device. That split cuts down the alert fatigue that wears on security teams and lets your analysts spend their time on confirmed threats instead of false alarms.
Most security teams are still early in that shift, with only 33% using AI to investigate incidents and 26% using it to respond. Excessive false positives are a complaint for 66% of those teams, so every AI verdict still needs an analyst to confirm it before anyone disables an account. AI-driven SOC tools speed up triage and investigation, though they also bring new staffing, upskilling and tool cost pressures for security leaders.
The Skills Behind an AI-Assisted SOC
Running AI tools well takes analysts who know when to question them, and artificial intelligence experience ranks as one of the most pressing skills need for 41% of cybersecurity professionals. However, only 28% of professionals have integrated AI into their operations so far, while the ability to use artificial intelligence in threat detection and response tops the list of skills their teams want most.
Generative assistants also often produce inaccurate, incomplete or outdated responses when the data sources behind them are missing or stale, so the analyst reading the output needs enough experience to spot a bad answer before acting on it. That gap between tools and talent is where managed detection and response (MDR) fills in for businesses that cannot staff a full SOC on their own.
A Layered Defense Around AI
Most successful attacks still start with basic security gaps, with the vast majority of intrusions still tracing back to fundamental human and procedural failures. Detection assisted by artificial intelligence works best as one layer in a layered cybersecurity defense that also covers prevention, response and the people who use your network every day:
- Detection – SIEM technology with behavioral analytics correlates activity across endpoints, servers, cloud services and network devices.
- Response – Analysts in a 24/7 SOC confirm threats, contain affected devices and accounts and record each step of the response.
- Prevention – Multifactor authentication, prompt patching and regular vulnerability assessments close the openings attackers automate their scans to find.
- People – Security awareness training with phishing simulations prepares employees for lures that no longer contain obvious spelling mistakes (the old giveaway most training relied on).
Learn More About AI Cybersecurity with SWK Technologies
Artificial intelligence will keep changing how attackers operate and how SOC and SIEM tools respond, which makes a layered defense more valuable with every new threat. SWK Technologies will help you build that defense, pairing around-the-clock SOC monitoring and automated SIEM technology with human-based intelligence and response that catches what automated tools miss.
Contact SWK here to learn how a layered approach to cybersecurity can help keep AI-driven threats in check for your business.