AI's double-edged cyber protection role in 2026

Having already been mainstreamed at work and home, it's no surprise that AI will continue to significantly influence cyber protection in 2026. But AI's rapid adoption cuts both ways: The same technology consumers and businesses use to stop fraud faster is simultaneously being weaponized by criminals to scale their schemes.

With AI being deployed for offense and defense alike, 2026 is shaping up to be the year the technology's protective promise and perilous potential collide.

New threats operate at machine speed

For cyber insurers, maintaining a clear line of sight into emerging AI trends will require frequent analyses of emerging threats and incoming claims. Two AI-enabled traps have recently gained steam and are expected to break out in 2026.

Prompt injections. The widespread adoption of large language models (LLMs) has created a new threat. Prompt injection crimes seek to embed malicious instructions into an AI system prompt or other input, such as an uploaded document or image. The goal is to override the LLM's safe behavior rules and force the system to follow the attacker's instructions instead. Because users often connect generative AI models to both personal data sources (like email) and enterprise systems (like HR platforms), researchers warn prompt injections could easily extract sensitive information.

Presentation attacks. As nefarious AI tools are democratized, both experienced and novice criminals are expected to bypass biometric-based systems. Employing synthetic speech and digitally fabricated faces, criminals can use deepfake technology to mimic a trusted individual's identity markers — tricking humans as well as voice- or facial-recognition authentication tools. And because such biometric authenticators are increasingly used for digital banking platforms, call center technologies and consumer apps — spoofing attacks could expose financial accounts and personal data. In 2025, call centers reported an increase in cyberattacks, with more than half saying attacks increased between 51%–75%.

AI sharpens the shield against cyberattacks
In the cyber insurance community, AI is a hot topic across conferences, trade publications and broader market discussions. Yet, most of these conversations focus on the risks rather than benefits.

AI may be accelerating and scaling digital crime, but the same underlying technology is poised to advance cybersecurity intelligence and strengthen defenses. IBM and Ponemon Institute uncovered average savings of $1.9 million in breach costs among firms that extensively use AI and automation for security.

Some AI tools are designed to reinforce system integrity, while others are aimed at mitigating the fallout of data breaches and intrusions. Three interesting examples of how the technology is being deployed are as follows.

1. Intelligent logging. Businesses can't maintain data records forever. System admin logs, in particular, are far too costly to store as the data simply isn't valuable enough to justify the cost — particularly as businesses optimize their cloud storage. Yet, the lack of records could be crippling in a forensic data breach investigation.

Certain AI models may be able to tackle this problem via anomaly detection. By only preserving logs that deviate from normal patterns, companies can retain forensic details where it matters, helping them stop ongoing intrusions faster, as well as better secure vulnerabilities against future attacks.

2. Evolving defenses. The prevalence of class action lawsuits following cyber incidents is pressuring legal teams to pursue defense strategies that are more sustainable than relying on settlements. AI tools may soon help determine what customer data was actually exposed during a breach, significantly narrowing the pool of potential claimants.

Organizations could even use AI to show certain personal details were already available on the dark web prior to a breach — suggesting their incidents were not the cause of any potential harm.

3. Agentic risk analysis and underwriting. The comparative capabilities of agentic AI are expected to accelerate both the pace and depth of large dataset analyses. Working alongside human underwriters, AI agents will be able to process far greater volumes of applicant information than ever before. Just as important, agentic AI could surface subtle patterns of risk that might otherwise go unnoticed, enabling more personalized coverage.

Insurers will be keen to adopt these new, more proactive systems because they'll make it easier to expand their client bases while gaining a clear picture of risks. Combining human insight with this technology has the potential to become the standard for insurance and cyber protection offerings.

Testing the balance of risk and resilience

AI's role in cyber protection is unfolding in real time, reshaping cyber threats and the defenses used against them. Insurers must remain agile enough to anticipate and protect against cyberattacks, scams and fraud powered by fast-learning AI engines.

Insurers will likely find themselves in closer collaboration with tech vendors as AI's most effective use cases come into view. As a result, success will hinge on an insurer's ability to recognize AI not only as a threat but also a transformative ally in protecting their operations and policyholders.