Keeping Customer Data More Secure with AI

By Phillip Britt  
Text below includes excerpts from an article originally published by DestinationCRM. For the full story, click here.  

Customer data theft and cyberattacks are escalating rapidly, with data breaches increasing by up to 40 percent globally this year, according to the latest statistics from SentinelOne, a cybersecurity solutions provider. This surge represents a 70 percent increase in weekly cyberattack volume since 2023 and an 18 percent increase in just the past few months alone. 

In many of these incidents, attackers are increasingly using automated, agentic artificial intelligence to conduct reconnaissance and exploit vulnerabilities at machine speeds. 

To try to stay ahead of fraudsters and guard against these data breaches, companies also need to turn to AI. 

“AI is becoming one of the strongest tools we have to keep customer data secure,” says Sean Hauver, chief information officer of Alorica, a customer service experience outsourcing services provider. “Modern organizations generate an enormous volume of signals that no human team could realistically monitor. AI fills that gap by recognizing patterns, detecting anomalies, and surfacing threats in real time, well before they become breaches.” 

Hauver adds that AI can help with the governance of customer data and other sensitive material through automated content and policy moderation: “Models can detect exposed [personally identifiable information], risky uploads, harmful documents, or malicious messages in seconds. I’ve seen these systems work in industries like banking, travel, and tech to prevent fake loan applications, block bot-driven scams, filter fraudulent listings, and stop toxic profiles before they cause harm. The impact is faster detection, fewer mistakes, and dramatically lower exposure to human error.” 

Hauver also maintains that AI can protect data with robust behavioral analysis. Modern threat patterns rarely appear as obvious violations; they show up as subtle anomalies, such as unusual access patterns, abnormal typing cadence, suspicious login behavior, or coordinated account activity, he says, noting that AI models can learn what’s normal across millions of interactions and flag deviations instantly. 

Alorica uses AI to catch identity theft attempts, fraudulent transactions, impersonation, and multi-account abuse before it impacts customers, according to Hauver.

AI can also assist in adaptive identity verification, Hauver continues. Instead of relying solely on passwords or static questions, AI can layer voice biometrics, behavioral signals, device intelligence, and contextual location data to authenticate users with far greater accuracy, reducing account takeovers without increasing friction for legitimate customers, he says. 

The most overlooked best practice in protecting customer data is keeping humans in command, Hauver maintains. “The strongest systems pair AI’s pattern recognition with human oversight, audit trails, and escalation paths. AI raises the flag; humans make the final call. When you get the balance right, AI builds trust, reduces risk, and strengthens the entire customer experience.”