AI is no longer just a productivity tool. It has become a weapon, sharpened by attackers and wielded by defenders. In this new battlefield, algorithms face off at terrifying speed.

And for today’s security leaders, keeping up isn’t good enough; they need to stay ahead in a war where code writes code, and intelligence, artificial or not, decides the victory.

How are Attackers Using AI?

AI has turbocharged cybercrime. Phishing emails are now personalized, fluent, and eerily convincing, generated by language models trained to mimic tone and context. Malware can be crafted or disguised with a single prompt.

Deepfake technology enables voice and video impersonation, fooling employees with synthetic messages from CEOs, often to approve fake payments. Reconnaissance is faster than ever. AI scans for vulnerabilities, harvests open source data, and builds full profiles of targets, all within seconds.

The result? Attacks are smarter, harder to spot, and nearly impossible to defend against manually. And they are multiplying. 

Losses from cybercrime are projected to hit $23 trillion by 2027, more than doubling from $9.5 trillion in 2024.

What about Defenders?

Fortunately, AI defends as well as it attacks. Behavioral analytics now power endpoint detection and response (EDR)_and extended detection and response (XDR) systems, detecting anomalies that people miss. LLMs triage alerts in real time, summarize logs, and flag risks faster than any Security Operations Center (SOC) analyst could alone.

Natural language processing helps catch phishing attempts before they land. Threat intelligence platforms use AI to enrich data, connect signals, and prioritize action. And when something slips through? AI isolates compromised endpoints in seconds, stopping lateral movement before it spreads.

But even the best tools need a human partner. Automation is not a silver bullet, it’s a force multiplier. Used wisely, it makes good teams great. Used carelessly, it amplifies risk.

What are the Hidden Risks?

Every tool has a dark side, and AI is no exception. Prompt injection and adversarial inputs can trick models into revealing secrets or making bad decisions, and poisoned training data can corrupt the models themselves.

There's also the risk of overconfidence. AI sometimes hallucinates, and people believe it. AI hallucinations occur when, in a large language model (LLM) usually a generative AI chat bot, detects patterns, or objects that don’t exist or that aren't visible to humans, then produces outputs that are inaccurate. Automation bias can lead teams to follow flawed guidance, skipping critical review.

Then there's the explainability problem. When AI blocks a connection or triggers an alert, it often can’t say why in a way that helps with incident response.

Unvetted tools (Shadow AI) may be leaking sensitive data into unknown hands. Add in a flood of new vendors and rushed copilots, and then there’s a sprawl of tools with overlapping functions, poor integration, and high noise.

Finally, attackers benefit too. AI lowers the skill barrier. Anyone with access to ChatGPT or similar can now script phishing campaigns, automate exploits, or mimic executive voices, without knowing how the underlying tech works.

The lesson? Even the smartest AI is only as good as the people, context, and controls around it.

Executive Takeaways

• Lean In. AI is not optional, it’s essential. Those who wait will watch from behind as adversaries accelerate. Adopt AI thoughtfully but act with intent. Falling behind in this race means leaving an organization exposed.
• Set Guardrails. Not all AI is created equal. Choose tools carefully and demand transparency from vendors. Establish clear governance and accountability around every AI deployment, from procurement, to monitoring, to decommissioning. Trust must be earned, not assumed.
• Enable Teams. AI should empower, not replace. Equip analysts with tools that amplify judgment, not override it. Focus on augmentation, not automation alone. The best outcomes still come from human insight, guided by intelligent systems.
• Stay Vigilant. Monitor more than the network. Monitor the way AI could be used against an organization, in deepfake data breaches and deception at scale. This is a two-front war: defend your systems and your sense of reality.

The arms race is on. The winners won’t be those with the most tools, but those who use them wisely. Ask the hard questions and never stop adapting.