Strategies to Combat AI-Generated Fraud in Workplaces

If you're involved in the development lifecycle of your companies products - read this. Teams across the product lifecycle have spent years building systems that depend on predictable customer behaviour and reliable evidence when resolving disputes. The introduction of accessible image-manipulation tools has removed the stability that many refund and quality-assurance processes rely on. The example circulating today is a manipulated burger photo that turns a cooked patty into what appears to be raw meat. Tools of this type can now produce convincing alterations in seconds. This shift affects several functions simultaneously. Customer service loses the ability to trust photo evidence. Fraud teams face a new attack vector that blends digital forgery with legitimate order data. Product managers responsible for returns, refunds, and satisfaction guarantees now operate in an environment where the traditional verification method no longer provides assurance. Teams need to respond with structured, cross functional measures: 1. Re evaluate evidence standards Photo based confirmation should not be treated as a single source of truth. Introduce multi factor validation for high risk claims. This can include structured metadata checks, behavioral risk scoring, and pattern recognition across claims. 2. Introduce tamper detection capabilities Modern image forensic models can detect common manipulation signatures. They do not eliminate the threat, but they raise the barrier and create cost for attackers. 3. Harden refund policy logic Policies relying on unconditional visual proof should transition to controlled rulesets that include order history, claim frequency, and anomaly signals. This reduces reliance on a single point of failure. 4. Educate frontline teams Operators handling disputes must understand that AI manipulation is a routine threat. Provide clear escalation paths and ensure frontline actions are consistent with enterprise risk appetite. Close the loop with product design and supply chain. Some categories can integrate unique identifiers or packaging elements that are difficult to forge. Small design choices can materially raise the cost of manipulation. AI acceleration creates opportunity, but it also creates instability in trust based systems. Product teams that absorb this early will prevent losses and maintain customer trust without compromising operational agility. This is now a core component of modern product lifecycle security, not a peripheral concern.

AI can generate information that sounds accurate but is completely wrong. AI hallucinations can undermine trust in reporting, introduce compliance exposure, and create financial or operational losses. They can also surface sensitive data or misinform decisions that affect capital allocation, investor communication, and audit readiness. AI hallucinations are not a signal to slow down innovation. They are a signal to strengthen your governance and controls. With a thoughtful risk management approach, leaders can understand uncertainty and build a more confident, resilient AI strategy. Considerations for leaders to reduce AI hallucination risk: 1. Create a validation and review process for AI generated financial outputs. Leaders must ensure that any AI generated forecasts, variance analyses, reconciliations, or narrative summaries have structured validation for source accuracy and logic. 2. Strengthen compliance and regulatory controls within AI workflows. AI hallucinations can create errors that lead to noncompliance and regulatory exposure. Leaders can embed compliance checkpoints into AI driven processes to avoid misstatements, inaccurate filings, or unintended disclosure. 3. Prioritize data governance using high quality, company specific data to reduce the risk of fabricated or inaccurate outputs. This is critical for forecasting, scenario modeling, and automated reporting. 4. Use retrieval augmented generation and automated reasoning for workflows. Pairing these methods anchors AI generated analysis in verified data sources rather than probability-based guesses. 5. Enable filtering and moderation tools to block misleading or irrelevant results. Teams cannot work from flawed or unverified outputs. Filters help prevent misleading content from entering critical workflows or influencing decisions. AI is gaining traction. Now is the time to formalize your AI risk mitigation approach. Start the discussion within your leadership team today. Identify where AI is already influencing decision-making, assess your current controls, and define the safeguards you need next. #RiskManagement #AI #Leaders

Your employees can no longer tell real from fake. AI just erased every red flag they were trained to spot. Perfect grammar. Personalized context. Executive voice clones. Legitimate sender domains. The old tells are gone. Microsoft’s 2025 Digital Defense Report shows: AI phishing now hits 30–50% click rates — 4× higher than traditional. Let that sink in: Up to half your employees now click AI-generated phishing. After 25 years in the Intelligence Community, I’ve watched adversaries evolve social-engineering tactics continuously. But AI changed everything. Here’s what AI eliminates: ✗ Grammar mistakes — LLMs write flawlessly ✗ Generic greetings — AI personalizes instantly ✗ Timing inconsistencies — AI knows when you’re vulnerable ✗ Context errors — AI mirrors communication patterns ✗ Voice detection — Deepfakes clone executives in seconds Traditional security awareness training is obsolete. Three AI attack vectors live now: 1. Executive voice impersonation 3 seconds of audio is enough to clone a CEO’s voice. Finance teams get wire requests that sound exactly like their boss — because it IS their boss’s voice. 2. Contextual spear phishing AI scrapes LinkedIn and social media to reference real projects and deadlines. “Spray and pray” is over. 3. Real-time conversation hijacking AI joins legitimate email threads mid-conversation. The domain’s real. The thread’s real. Only the final request is malicious. What works instead: → Process-based verification — verify all financial or credential requests separately. → Decision frameworks — when it looks 100% real, verify anyway. → Institutional skepticism — verify by default, not trust by default. The IC has operated this way for decades: even trusted sources get verified. -- Channels get compromised. -- Credentials get stolen. -- Trust gets weaponized. AI gives every cybercriminal nation-state-level capability. Your defense can’t be “spot the AI.” It must be “verify everything that matters.” Build verification into daily workflow — not as friction, but as rhythm. Because the strongest defense isn’t better detection. It’s human judgment paired with institutional process and coupled with effective technology. Security leaders: What verification protocols are you building now that AI erased traditional red flags? Drop your approach #CyberSecurity #AI #BehavioralDefense #Phishing #CISO #SocialEngineering #ZeroTrust

Candidate fraud is becoming a real challenge in today’s hiring landscape. We’re moving far beyond simple résumé embellishments. Talent teams (like mine) are now confronting falsified identities, AI‑generated résumés, coached answers, and even full proxy interview setups. Fraud is particularly prevalent in remote and high‑volume hiring, where identity is harder to verify consistently. Real World Examples: • Fake résumés and identities blocked at scale Amazon reported blocking more than 1,800 job applications from suspected North Korean operatives posing as legitimate candidates to infiltrate remote tech roles. • Deepfake job candidates passing video interviews Fraudsters are now using AI‑generated videos and audio to impersonate real people, enabling them to “attend” interviews undetected. This has become one of the top emerging fraud threats for employers in 2026. • Proxy interview schemes Some candidates hire stand‑ins to complete technical or behavioral interviews on their behalf (THIS BLOWS MY MIND 👿 ) — a trend that has sharply increased between 2023 and 2026. What happened to the simple value called integrity? • Mass‑produced AI‑generated applications Automated tools can now generate polished, fabricated career histories and “perfect” responses, enabling candidates to apply at scale while blending fake profiles with real identities. So how do we stay ahead? Verify identity earlier — catching fraud early prevents wasted time and reduces exposure. Use AI for detection — behavioral analytics, voice/face matching, and credential verification tools can flag inconsistencies. Adopt structured interviews & skills‑based tests — harder for fraudsters to fake and easier to validate. Add layered verification checkpoints — a “defense‑in‑depth” model catches fraud at multiple stages without overwhelming candidates. Fraud is evolving fast — but so are our tools and strategies. With the right structure and vigilance, we can protect our hiring processes, our teams, and the trust that sits at the center of every great hire.

Candidate fraud is becoming its own full-time job to manage. It feels like every recruiter I know has a wild story from the last six months. Fake resumes. People using AI to answer interview questions in real time. Full-blown imposters taking technical interviews or, even worse, showing up on day one after getting hired. One recent study reported a 92 percent increase in fraudulent candidates since 2022, and projections show that with AI adoption, this could climb another 30 to 50 percent. Fraud in recruiting isn’t new, but the scale and sophistication definitely are. Here are some things that my network and I have incorporated into our processes that actually work at catching bad actors early: • 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝗯𝗲𝘁𝘁𝗲𝗿 𝘁𝗼𝗼𝗹𝘀: Many ATS platforms now offer fraud detection as an add-on feature, and new tools like tofu help flag suspicious profiles upfront. Huge time saver. • 𝗥𝗲𝗱𝘂𝗰𝗲 𝗮𝘂𝘁𝗼-𝗮𝗽𝗽𝗹𝘆 𝘀𝗽𝗮𝗺: AI auto-apply tools are flooding pipelines. Work with your ATS and IT teams to block domains that are clearly mass-application bots. • 𝗔𝗱𝗱 𝗮 𝗽𝗿𝗲-𝘀𝗰𝗿𝗲𝗲𝗻 𝘀𝘁𝗲𝗽 𝗯𝗲𝗳𝗼𝗿𝗲 𝗮𝗻𝘆 𝗹𝗶𝘃𝗲 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀: A simple video intro request weeds out a shocking number of questionable candidates. Most bad actors never submit anything, and the ones who do tend to be easy to flag. • 𝗨𝘀𝗲 𝗭𝗼𝗼𝗺 𝗮𝘀 𝘁𝗵𝗲 𝗱𝗲𝗳𝗮𝘂𝗹𝘁 𝗳𝗼𝗿 𝗵𝗶𝗴𝗵-𝗿𝗶𝘀𝗸 𝗿𝗼𝗹𝗲𝘀: This allows IT/security to verify IP addresses and confirm basic location info. • 𝗔𝘀𝗸 𝗵𝘆𝗽𝗲𝗿-𝗹𝗼𝗰𝗮𝗹, 𝗿𝗲𝗮𝗹-𝗹𝗶𝗳𝗲 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀: If someone claims they lived in NY for ten years, they’re going to know the code of their preferred airport without hesitation. Same with local sports teams or college mascot. Real candidates answer instantly. Fraudsters need time to stall and panic google the answer. • 𝗔𝗱𝗱 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗿𝗲𝗰𝗼𝗿𝗱𝗶𝗻𝗴: Tools like BrightHire, Metaview, and ATS-native recording features in Ashby or Kula help add another layer of protection as cheating in interviews has become extremely common. • 𝗦𝘁𝗿𝗲𝗻𝗴𝘁𝗵𝗲𝗻 𝗽𝗿𝗲-𝗯𝗼𝗮𝗿𝗱𝗶𝗻𝗴 𝘃𝗲𝗿𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗽𝗿𝗼𝘁𝗼𝗰𝗮𝗹𝘀: Double down on ID checks, verification steps and flags for anyone who asks to send equipment somewhere that doesn’t match their application details. These inconsistencies are usually early indicators of a bigger problem. The fraud problem isn’t going away, but neither is the TA community’s ability to adapt. If you have other tactics, tools or red flags you’ve seen, drop them in the comments.

Fraud is no longer fake invoices or forged signatures. It’s synthetic voices, cloned executives, and AI-generated documents (smart enough to bypass traditional controls). AI deepfakes are coming for your audit trails. We’ve reached a tipping point. 92% of companies have suffered financial loss due to a deepfake incident. In 2024, a deepfaked live video of senior executives tricked employees into transferring millions. 71% of business leaders now view fake documents as a major threat. We CFOs must step into a new role and be aware of emerging threats... Here are some strategic priorities that every finance leader should act on now: • Assess your vulnerabilities. • Embrace AI-detection technology. • Review company policy on large monetary and data transfers. • Embed healthy skepticism into your culture through training. • Invest in identity, document, and transaction-validation tools built for generative-AI threat vectors. • Lead the cross-functional response with a unified deepfake risk task-force. Tomorrow's threat won’t be a missing invoice... It'll be a voice-cloned CEO ordering a wire transfer. How are you keeping up with AI advancements?

🧾 Employees using AI to create fraudulent expense receipts 🤖 Fake or otherwise malicious “candidates” using Deepfake to hide their true identity on remote interviews until they get far enough in the process to hack your data 🎣 AI-powered phishing scams that are more sophisticated than ever Over the past few months, I’ve had to come to terms with the fact that this is our new reality. AI is here, and it is more powerful than ever. And HR professionals who continue to bury their head in the sand or stand by while “enabling” others without actually educating themselves are going to unleash serious risks and oversights across their company. Which means that HR professionals looking to stay on top of the increased risk introduced by AI need to lean into curiosity, education, and intentionality. For the record: I’m not anti-AI. AI has and will continue to help increase output, optimize efficiencies, and free up employees’ time to work on creative and energizing work instead of getting bogged down and burnt out by mind numbing, repetitive, and energy draining work. But it’s not without its risks. AI-powered fraud is real, and as HR professionals, it’s our jobs to educate ourselves — and our employees — on the risks involved and how to mitigate it. Not sure where to start? Consider the following: 📚 Educate yourself on the basics of what AI can do and partner with your broader HR, Legal, and #Compliance teams to create a plan to knowledge share and stay aware of new risks and AI-related cases of fraud, cyber hacking, etc (could be as simple as starting a Slack channel, signing up for a newsletter, subscribing to an AI-focused podcast — you get the point) 📑 Re-evaluate, update, and create new policies as necessary to make sure you’re addressing these new risks and policies around proper and improper AI usage at work (I’ll link our AI policy template below) 🧑💻 Re-evaluate, update, and roll out new trainings as necessary. Your hiring managers need to be aware of the increase in AI-powered candidate fraud we’re seeing across recruitment, how to spot it, and who to inform. Your employees need to know about the increased sophistication of #phishing scams and how to identify and report them For anyone looking for resources to get you started, here are a few I recommend: AI policy template: https://lnkd.in/e-F_A9hW AI training sample: https://lnkd.in/e8txAWjC AI phishing simulators: https://lnkd.in/eiux4QkN What big new scary #AI risks have you been seeing?

AI PR Nightmares Part 2: When AI Clones Voices, Faces, and Authority. What Happened: Last week, a sophisticated AI-driven impersonation targeted White House Chief of Staff Susie Wiles. An unknown actor, using advanced AI-generated voice cloning, began contacting high-profile Republicans and business leaders, posing as Wiles. The impersonator requested sensitive information, including lists of potential presidential pardon candidates and even cash transfers. The messages were convincing enough that some recipients engaged before realizing the deception. Wiles’ personal cellphone contacts were reportedly compromised, giving the impersonator access to a network of influential individuals. This incident underscores a huge growing threat: AI-generated deepfakes are becoming increasingly realistic and accessible, enabling malicious actors to impersonate individuals with frightening accuracy. From cloned voices to authentic looking fabricated videos, the potential for misuse spans politics, finance, and way beyond. And it needs your attention now. 🔍 The Implications for PR and Issues Management: As AI-generated impersonations become more prevalent, organizations must proactively address the associated risks as part of their ongoing crisis planning. Here are key considerations: 1. Implement New Verification Protocols: Establish multi-factor authentication for communications, especially those involving sensitive requests. Encourage stakeholders to verify unusual requests through secondary channels. 2. Educate Constituents: Conduct training sessions to raise awareness about deepfake technologies and the signs of AI-generated impersonations. An informed network is a critical defense. 3. Develop a Deepfakes Crisis Plan: Prepare for potential deepfake incidents with a clear action plan, including communication strategies to address stakeholders and the public promptly. 4. Monitor Digital Channels: Utilize your monitoring tools to detect unauthorized use of your organization’s or executives’ likenesses online. Early detection and action can mitigate damage. 5. Collaborate with Authorities: In the event of an impersonation, work closely with law enforcement and cybersecurity experts to investigate and respond effectively. ———————————————————— The rise of AI-driven impersonations is not a distant threat, it’s a current reality and only going to get worse as the tech becomes more sophisticated. If you want to think and talk more about how to prepare for this and other AI related PR and issues management topics, follow along here with my series or DM if I can help your organization prepare or respond.

Fraud no longer hides in the shadows. It might show up disguised as someone you know. Like when the CEO calls and her voice on the phone sounds exactly right. Her urgency feels real, and the wire transfer request to a new bank account seems legitimate, so accounting releases the funds. And just like that, the company loses $20k to a fraudster who weaponized AI. This isn't science fiction. It's happening right now to individuals and organizations alike. Fraudsters are creating disturbingly real AI deepfakes that can fool even the most cautious people. And companies need strategies to combat them. Because those audio and visual cues we've relied on for decades are no longer reliable indicators of authenticity when it comes to AI deepfakes. Organizations can fight back with these defense strategies: ✔ Stay cautious and be wary of anyone requesting money or personal information, even if they look or sound like someone you trust. ✔ Don’t send money or share sensitive data in response to a single phone or video call. Phone numbers can be spoofed, so always verify a person’s identity by contacting them separately at a number you trust. ✔ Use small action requests, like asking a person to turn their head, blink repeatedly, or hum a song while on a video or phone call. If they decline, freeze up, or go silent, it could be a fraudster. ✔ Establish a safe word that only your inner circle knows to confirm the identity of someone claiming to be a colleague, family member, or friend.   ✔ Use strong passwords. Enable multifactor authentication (MFA) on all company devices and accounts whenever possible. And don’t forget to report AI deepfakes to law enforcement and any relevant social media channels, websites, and other platforms where the encounter took place. All of these tips ALSO work for individuals too because hackers like causing havoc with anyone they can. The question isn't whether AI deepfakes will target your organization. It's whether your organization will be ready when it does.   Food for thought as we kick off Cybersecurity Awareness Month.   ♻ Share our infographic to help companies combat AI deepfakes. 

The fraud isn't hidden in noise. It's designed to pass through it. One carefully crafted email reaches your finance team - vendor invoice, account update, credential request. Professional formatting. Vendor Email Compromise. Your filters let it through because it's good enough. Here's what matters: Email filters stop obvious spam. But one targeted message? That gets through. Then it arrives at a fatigued decision-maker at 4:55pm on Friday, or quarter-end when backlogs are crushing, or post-acquisition when processes are chaotic. That's when verification gets skipped. This is how AI-assisted social engineering works in 2026. Not by overwhelming your inbox with thousands of messages. By crafting individual attacks that survive your defenses and land at moments when shortcuts are taken. What changes? Never verify critical transactions through the channels where the attack arrived. Don't call the number in the email. Don't reply to the message. Instead, find the person's number independently - through your directory, through a known contact - and verify through that completely separate channel. Out-of-band verification isn't optional anymore. It's the only verification that works. #Cybersecurity #AI #FraudPrevention #AgenticAdversaries #DigitalTrust