Balancing the paradox of defending one of many world’s main journey, software program and companies companies in opposition to the accelerating threats of AI illustrates why CISOs should be steps forward of the newest adversarial AI tradecraft and assault methods.
As a number one world B2B journey platform, American Specific World Enterprise Journey (Amex GBT) and its safety crew are doing simply that, proactively confronting this problem with a twin deal with cybersecurity innovation and governance. With deep roots in a financial institution holding firm, Amex GBT upholds the very best information privateness requirements, safety compliance and threat administration. This makes safe, scalable AI adoption a mission-critical precedence.
Amex GBT Chief Data Safety Officer David Levin is main this effort. He’s constructing a cross-functional AI governance framework, embedding safety into each part of AI deployment and managing the rise of shadow AI with out stifling innovation. His strategy gives a blueprint for organizations navigating the high-stakes intersection of AI development and cyber protection.
The next are excerpts from Levin’s interview with VentureBeat:
VentureBeat: How is Amex GBT utilizing AI to modernize menace detection and SOC operations?
David Levin: We’re integrating AI throughout our menace detection and response workflows. On the detection facet, we use machine studying (ML) fashions in our SIEM and EDR instruments to identify malicious habits sooner and with fewer false positives. That alone accelerates how we examine alerts. Within the SOC, AI-powered automation enriches alerts with contextual information the second they seem. Analysts open a ticket and already see vital particulars; there’s now not a must pivot between a number of instruments for fundamental data.
AI additionally helps prioritize which alerts are seemingly pressing. Our analysts then spend their time on the highest-risk points moderately than sifting by noise. It’s a large enhance in effectivity. We will reply at machine pace the place it is smart, and let our expert safety engineers deal with complicated incidents. In the end, AI helps us detect threats extra precisely and reply sooner.
VentureBeat: You additionally work with managed safety companions like CrowdStrike OverWatch. How does AI function a power multiplier for each in-house and exterior SOC groups?Levin: AI amplifies our capabilities in two methods. First, CrowdStrike OverWatch provides us 24/7 menace searching augmented by superior machine studying. They continuously scan the environment for delicate indicators of an assault, together with issues we would miss if we relied on guide inspection alone. Which means we now have a top-tier menace intelligence crew on name, utilizing AI to filter out low-risk occasions and spotlight actual threats.
Second, AI boosts the effectivity of our inner SOC analysts. We used to manually triage much more alerts. Now, an AI engine handles that preliminary filtering. It might probably rapidly distinguish suspicious from benign, so analysts solely see the occasions that want human judgment. It appears like including a sensible digital teammate. Our workers can deal with extra incidents, deal with menace searching, and choose up superior investigations. That synergy—human experience plus AI help—drives higher outcomes than both alone
VentureBeat: You’re heading up an AI governance framework at GBT, primarily based on NIST rules. What does that seem like, and the way do you implement it cross-functionally?
Levin: We leaned on the NIST AI Danger Administration Framework, which helps us systematically assess and mitigate AI-related dangers round safety, privateness, bias and extra. We shaped a cross-functional governance committee with representatives from safety, authorized, privateness, compliance, HR and IT. That crew coordinates AI insurance policies and ensures new initiatives meet our requirements earlier than going reside.
Our framework covers all the AI lifecycle. Early on, every use case is mapped in opposition to potential dangers—like mannequin drift or information publicity—and we outline controls to handle them. We measure efficiency by testing and adversarial simulations to make sure the AI isn’t simply fooled. We additionally insist on at the least some stage of explainability. If an AI flags an incident, we need to know why. Then, as soon as programs are in manufacturing, we monitor them to verify they nonetheless meet our safety and compliance necessities. By integrating these steps into our broader threat program, AI turns into a part of our general governance moderately than an afterthought.
VentureBeat: How do you deal with shadow AI and guarantee staff observe these insurance policies?
Levin: Shadow AI emerged the second public generative AI instruments took off. Our strategy begins with clear insurance policies: Workers should not feed confidential or delicate information into exterior AI companies with out approval. We define acceptable use, potential dangers, and the method for vetting new instruments.
On the technical facet, we block unapproved AI platforms at our community edge and use information loss prevention (DLP) instruments to stop delicate content material from being uploaded. If somebody tries utilizing an unauthorized AI web site, they get alerted and directed to an accepted various. We additionally rely closely on coaching. We share real-world cautionary tales—like feeding a proprietary doc right into a random chatbot. That tends to stay with individuals. By combining consumer training, coverage readability and automatic checks, we will curb most rogue AI utilization whereas nonetheless encouraging reputable innovation.
VentureBeat: In deploying AI for safety, what technical challenges do you encounter, for instance, information safety, mannequin drift, or adversarial testing?
Levin: Information safety is a main concern. Our AI typically wants system logs and consumer information to identify threats, so we encrypt these feeds and limit who can entry them. We additionally be certain that no private or delicate data is used until it’s strictly needed.
Mannequin drift is one other problem. Assault patterns evolve continuously. If we depend on a mannequin educated on final yr’s information, we threat lacking new threats. We have now a schedule to retrain fashions when detection charges drop or false positives spike.
We additionally do adversarial testing, primarily red-teaming the AI to see if attackers may trick or bypass it. That may imply feeding the mannequin artificial information that masks actual intrusions, or attempting to govern logs. If we discover a vulnerability, we retrain the mannequin or add further checks. We’re additionally massive on explainability: if AI recommends isolating a machine, we need to know which habits triggered that call. That transparency fosters belief within the AI’s output and helps analysts validate it.
VentureBeat: Is AI altering the function of the CISO, making you extra of a strategic enterprise enabler than purely a compliance gatekeeper?
Levin: Completely. AI is a chief instance of how safety leaders can information innovation moderately than block it. As an alternative of simply saying, “No, that’s too risky,” we’re shaping how we undertake AI from the bottom up by defining acceptable use, coaching information requirements, and monitoring for abuse. As CISO, I’m working intently with executives and product groups so we will deploy AI options that really profit the enterprise, whether or not by bettering the shopper expertise or detecting fraud sooner, whereas nonetheless assembly laws and defending information.
We even have a seat on the desk for giant selections. If a division desires to roll out a brand new AI chatbot for journey reserving, they contain safety early to deal with threat and compliance. So we’re transferring past the compliance gatekeeper picture, getting into a job that drives accountable innovation.
VentureBeat: How is AI adoption structured globally throughout GBT, and the way do you embed safety into that course of?
Levin: We took a worldwide heart of excellence strategy. There’s a core AI technique crew that units overarching requirements and pointers, then regional leads drive initiatives tailor-made to their markets. As a result of we function worldwide, we coordinate on greatest practices: if the Europe crew develops a strong course of for AI information masking to adjust to GDPR, we share that with the U.S. or Asia groups.
Safety is embedded from day one by “secure by design.” Any AI mission, wherever it’s initiated, faces the identical threat assessments and compliance checks earlier than launch. We do menace modeling to see how the AI may fail or be misused. We implement the identical encryption and entry controls globally, but in addition adapt to native privateness guidelines. This ensures that irrespective of the place an AI system is constructed, it meets constant safety and belief requirements.
VentureBeat: You’ve been piloting instruments like CrowdStrike’s Charlotte AI for alert triage. How are AI co-pilots serving to with incident response and analyst coaching?
Levin: With Charlotte AI we’re offloading quite a lot of alert triage. The system immediately analyzes new detections, estimates severity and suggests subsequent steps. That alone saves our tier-1 analysts hours each week. They open a ticket and see a concise abstract as a substitute of uncooked logs.
We will additionally work together with Charlotte, asking follow-up questions, together with, “Is this IP address linked to prior threats?” This “conversational AI” side is a serious assist to junior analysts, who be taught from the AI’s reasoning. It’s not a black field; it shares context on why it’s flagging one thing as malicious. The web result’s sooner incident response and a built-in mentorship layer for our crew. We do keep human oversight, particularly for high-impact actions, however these co-pilots allow us to reply at machine pace whereas preserving analyst judgment.
VentureBeat: What do advances in AI imply for cybersecurity distributors and managed safety service suppliers (MSSPs)?
Levin: AI is elevating the bar for safety options. We count on MDR suppliers to automate extra of their front-end triage so human analysts can deal with the hardest issues. If a vendor can’t present significant AI-driven detection or real-time response, they’ll wrestle to face out. Many are embedding AI assistants like Charlotte straight into their platforms, accelerating how rapidly they spot and comprise threats.
That stated, AI’s ubiquity additionally means we have to see previous the buzzwords. We take a look at and validate a vendor’s AI claims—“Show us how your model learned from our data,” or “Prove it can handle these advanced threats.” The arms race between attackers and defenders will solely intensify, and safety distributors that grasp AI will thrive. I absolutely count on new companies—like AI-based coverage enforcement or deeper forensics—rising from this pattern.
VentureBeat: Lastly, what recommendation would you give CISOs beginning their AI journey, balancing compliance wants with enterprise innovation?
Levin: First, construct a governance framework early, with clear insurance policies and threat evaluation standards. AI is simply too highly effective to deploy haphazardly. When you outline what accountable AI is in your group from the outset, you’ll keep away from chasing compliance retroactively.
Second, accomplice with authorized and compliance groups upfront. AI can cross boundaries in information privateness, mental property, and extra. Having them onboard early prevents nasty surprises later.
Third, begin small however present ROI. Choose a high-volume safety ache level (like alert triage) the place AI can shine. That fast win builds credibility and confidence to develop AI efforts. In the meantime, put money into information hygiene—clear information is every little thing to AI efficiency.
Fourth, prepare your individuals. Present analysts how AI helps them, moderately than replaces them. Clarify the way it works, the place it’s dependable and the place human oversight remains to be required. A well-informed workers is extra prone to embrace these instruments.
Lastly, embrace a continuous-improvement mindset. Threats evolve; so should your AI. Retrain fashions, run adversarial exams, collect suggestions from analysts. The know-how is dynamic, and also you’ll must adapt. When you do all this—clear governance, sturdy partnerships, ongoing measurement—AI will be an unlimited enabler for safety, letting you progress sooner and extra confidently in a menace panorama that grows by the day.
VentureBeat: The place do you see AI in cybersecurity going over the following few years, each for GBT and the broader trade?
Levin: We’re heading towards autonomous SOC workflows, the place AI handles extra of the alert triage and preliminary response. People oversee complicated incidents, however routine duties get absolutely automated. We’ll additionally see predictive safety—AI fashions that forecast which programs are most in danger, so groups can patch or section them upfront.
On a broader scale, CISOs will oversee digital belief, guaranteeing AI is clear, compliant with rising legal guidelines and never simply manipulated. Distributors will refine AI to deal with every little thing from superior forensics to coverage tuning. Attackers, in the meantime, will weaponize AI to craft stealthier phishing campaigns or develop polymorphic malware. That arms race makes sturdy governance and steady enchancment vital.
At GBT, I count on AI to permeate past the SOC into areas like fraud prevention in journey bookings, consumer habits analytics and even customized safety coaching. In the end, safety leaders who leverage AI thoughtfully will achieve a aggressive edge—defending their enterprises at scale whereas liberating expertise to deal with essentially the most complicated challenges. It’s a serious paradigm shift, however one which guarantees stronger defenses and sooner innovation if we handle it responsibly.
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