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12/06/2026 9:57 pm
TL;DR: AI Enthusiasts represent 25% of enterprises, and Arkose Labs says they are more likely to use AI across historical analysis, forecasting, automation, 24/7 monitoring, and real-time response to counter AI-driven attacks and fraud. The governance signal is clear: security programmes now need faster detection, tighter model oversight, and vendor strategies that account for adversarial AI pressure.
NHIMG editorial — based on content published by Arkose Labs: The Intersection of AI, Digital Fraud and Cyber Defenses
By the numbers:
- AI Enthusiasts are a select group, with just 25% of enterprises fitting this category today.
- 50% of AI Enthusiasts acknowledge the shortage of talent with expertise in both cybersecurity and AI.
- 67% prefer partnering with vendors who specialize in AI-powered cybersecurity.
Questions worth separating out
Q: How should security teams use AI in fraud and identity defence without losing control?
A: Use AI to improve prioritisation, pattern detection, and response speed, but keep human ownership for high-impact decisions.
Q: Why do AI-driven attacks change identity governance requirements?
A: Because they compress attacker decision cycles and increase the volume of abuse that identity controls must evaluate.
Q: What do security teams get wrong about AI in cyber defence?
A: They often treat AI as a technology purchase rather than a governed operating model.
Practitioner guidance
- Assess identity response latency Measure how long it takes to detect, triage, and contain account takeover, MFA compromise, and suspicious session activity.
- Define governance for defensive AI use Document who approves models, who validates outputs, and who owns the rollback path when an AI control misclassifies user behaviour or blocks legitimate activity.
- Separate automation from accountability Allow AI to prioritise or enrich alerts, but preserve human decision rights for high-impact actions such as account lockout, challenge escalation, and fraud case closure.
What's in the full report
Arkose Labs' full research covers the operational detail this post intentionally leaves for the source:
- A breakdown of the three AI Enthusiast behaviours that the report uses to segment enterprises and compare maturity.
- The report’s thinking on account takeover, MFA compromise, and generative AI threats as separate operational scenarios.
- The vendor’s view on why specialist AI security sourcing can be faster than building in-house capabilities.
- The underlying survey and benchmarking context behind the 25% AI Enthusiast classification.
👉 Read Arkose Labs' research on AI, digital fraud, and cyber defences →
AI-driven fraud and cyber defenses: what practitioners need to act on?
Explore further
13/06/2026 12:24 am
AI-driven fraud creates a governance problem before it creates a tooling problem. The article shows that enterprises are being pushed to adopt AI because attacker behaviour has become more automated and more adaptive. That changes the control question from whether a security team can detect abuse to whether its governance model can keep pace with AI-assisted attack volume. For practitioners, the real test is whether identity and fraud controls are built for machine-speed escalation.
A few things that frame the scale:
- Companies are dedicating an average of 32.4% of their security budgets to secrets management and code security, with US organisations leading at 40.8%, according to The State of Secrets in AppSec.
- Only 44% of developers are reported to follow security best practices for secrets management, exposing a significant developer behaviour gap, according to The State of Secrets in AppSec.
A question worth separating out:
Q: Who is accountable when AI-driven defence blocks legitimate users or misses fraud?
A: The organisation remains accountable, not the model. Security, fraud, and identity owners need a shared governance model that defines decision rights, exception handling, and auditability. If an AI system affects access or customer trust, it needs the same accountability discipline as any other identity control.
👉 Read our full editorial: AI enthusiasts are reshaping defenses against AI-driven fraud
