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AI is not replacing phishing, business email compromise, malware delivery or impersonation. It is making those familiar attacks faster to produce, easier to personalize and more convincing across email, text, voice and video. The safest response is to verify identity and unusual requests through a channel you already trust, while using multifactor authentication (MFA) and layered organizational controls.
AI is an amplifier, not a wholly new kind of scam
Most AI-assisted cyberattacks still pursue the same outcomes as older schemes: stealing credentials, taking over accounts, delivering malware, obtaining sensitive information or persuading a victim to send money. The FBI describes AI as improving the presentation, speed, scale and automation of existing fraud methods rather than changing the underlying objective.
The practical difference is that an attacker can produce more credible lures with less effort. A message that once contained obvious spelling mistakes can now use polished grammar, a convincing tone and details that fit the target’s culture, job or personal circumstances. Europol’s IOCTA 2025 summary says criminals are using generative AI, including large language models, to tailor scam messages to victims’ cultural context and personal details.
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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11| Familiar attack | What AI can change | What the victim still faces |
|---|---|---|
| Phishing email | Cleaner writing, faster drafting and individualized wording | A request to click, sign in, open an attachment or disclose information |
| Smishing text | Large-scale, plausible messages adapted to the recipient | A malicious link, a request for a code or a move to another chat platform |
| Business email compromise | More persuasive executive or supplier impersonation | A fraudulent payment, account-change request or sensitive-data request |
| Voice or video impersonation | Cloned voices and synthetic video that resemble a known person | Pressure to act before independently checking the caller’s identity |
| Malware and malicious sites | Emerging possibilities such as realistic websites or AI-assisted code | Credential theft, device compromise or data loss |
None of these changes means every phishing email, malware incident or fraud case used AI. The FBI’s examples describe observed campaigns; broader technical possibilities described by NIST remain an evolving risk assessment.
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Phishing now crosses email, text, voice and video
Email: professional wording removes an old warning sign
Earlier phishing campaigns often exposed themselves through awkward language or obvious formatting errors. AI can generate a message with correct spelling, natural phrasing and an appropriate level of formality. It can also produce many versions of the same lure, allowing criminals to tailor a message to a department, supplier relationship or current event.
A polished message is not evidence that the sender is genuine. Inspect the actual sender address, reply-to address and destination of every link. A familiar display name can hide an unrelated account, and a legitimate-looking page can still be controlled by an attacker.
Text messages: smishing can become a bridge to another channel
In a May 2025 alert, the FBI described a campaign in which text messages and AI-generated voice messages impersonated senior officials. The messages built rapport and sometimes moved the target to another messaging platform containing a malicious link. This combination matters because a short text can establish trust, while a second channel makes the request feel more personal or urgent.
Do not treat a message as safe merely because it arrived on a phone rather than by email. A text asking you to continue a conversation elsewhere, open a link, provide a one-time code or discuss money deserves the same independent verification as an email.
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Voice and video: a familiar face or voice is no longer proof
The FBI says criminals can use voice and video cloning to imitate family members, co-workers and business partners. A caller may sound like a relative who needs urgent help, or appear to be an executive asking for a transfer. Audio glitches, unnatural facial movement or odd timing may occur, but the FBI warns that AI-generated content can be difficult to identify. Detection by appearance or sound alone is not a dependable control.
How attackers use AI across a familiar attack
1. Drafting and personalization
Generative tools can turn a basic script into a message that matches a victim’s language, cultural references, role and relationship with the supposed sender. The result may feel unusually relevant without containing any obvious technical flaw.
2. Speed and scale
The FBI’s San Francisco field office says AI can increase the speed, scale and automation of existing schemes. An attacker can generate numerous variants, test different appeals and send them to more targets without manually writing each message.
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3. Multichannel impersonation
Text, email, voice and video can be combined into one social-engineering sequence. For example, a message can introduce a supposed official, a voice call can establish rapport and a follow-up link can request a login or payment. The technology changes the presentation; the manipulation of trust remains familiar.
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4. Realistic websites and malicious links
NIST’s AI Cybersecurity Framework Profile, published as an initial preliminary draft in December 2025, discusses the possibility of realistic malicious websites and links, AI-assisted malware and more autonomous orchestration of attack phases. These are emerging-risk descriptions, not a universal finding that criminals already use autonomous systems in every campaign.
5. Attacking AI systems themselves
A related but distinct issue arises when an organization deploys AI. NIST AI 100-2 covers adversarial-machine-learning threats including evasion, poisoning, privacy attacks and misuse of generative AI. Those threats target an AI system or its data; they should not be confused with criminals using AI to improve ordinary phishing against people.
What the reported numbers do—and do not—show
The FBI Internet Crime Complaint Center (IC3) annual report for 2025 provides useful reported figures, but its categories depend on what complainants identified as AI-related. They are not a verified count of every AI-caused attack, and they do not establish that AI caused a particular loss.
| 2025 IC3 figure | What it represents | Important qualification |
|---|---|---|
| 22,364 complaints | Complaints that reported AI-related information | A reported category, not a census of AI-enabled crime |
| $893,346,472 | Adjusted losses shown in the report’s graphic for complaints reporting AI-related information | Reported loss; not a verified estimate of all AI-caused cybercrime |
| More than $30 million | Business losses reported for business email compromise scams involving AI | Applies to that category and the report’s attribution language |
| More than $19 million | Losses from confidence or romance scams with a likely AI nexus | “Likely AI nexus” is the report’s qualification |
| More than $5 million | Losses from distress scams with a likely AI nexus | A defined category, not a complete AI-fraud total |
These figures show why the issue matters, while leaving key questions unanswered: they do not measure an attack-success rate, prove that AI caused every reported incident or quantify how much conventional phishing has changed.
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Can you tell whether a phishing message was written by AI?
There is no universal, reliable visual or linguistic test. Perfect grammar, a professional logo, an unusual image, a slight audio artifact or an awkward sentence can each occur in genuine and fraudulent communications. The FBI specifically cautions that AI-generated content may be difficult to identify.
Use observable clues as prompts to verify, not as proof. Check whether the request is unexpected, urgent, secretive or financially unusual. Compare the sender’s actual address or number with records you already trust. Hover over a link on a computer, or press and hold it on a phone, to inspect the destination without opening it. Do not rely on a display name or a caller-ID label.
What to do with a suspicious email, text or voice message
- Pause. Do not click, reply, download an attachment, transfer money or disclose a password while the request is unresolved.
- Inspect the source. Check the full email address, phone number, account name and link destination. Look for a mismatch between the visible label and the underlying address.
- Use a previously trusted channel. Call the person using a number already stored in your contacts or an official directory. Do not use a number or link supplied by the suspicious message.
- Ask for context. Confirm what was requested, why it is urgent and which account or transaction is involved. A genuine person can answer through the independent channel.
- Refuse authentication-code requests. Never give an MFA code to a caller, texter or chat participant. Enter codes only into the service you intentionally opened.
- Report and preserve evidence. Use your email or messaging service’s reporting function and, in a workplace, notify the security or help-desk team. Keep the original message, headers, number and time if an investigation may be needed.
- If you already acted, contain the damage. Change the affected password from a known-clean device, revoke active sessions where the service allows it, contact the bank or payment provider immediately and tell your organization if a work account or data may be exposed.
How to verify a payment request from a boss, supplier or family member
Payment fraud succeeds when urgency replaces normal approval. Apply a separate verification step before sending money, changing bank details or buying gift cards.
- For a workplace request, follow the organization’s existing approval and callback process. Confirm new bank details using a supplier record or phone number that predates the request.
- For a family emergency, call the relative on a known number. If the voice sounds convincing but the situation is unusual, ask a personal question or use a family secret word or phrase agreed in advance; the FBI suggests this precaution.
- For either case, require a second person to review an unusual transfer. Do not allow a message’s urgency to cancel separation of duties.
- Stop if the person insists on secrecy, refuses an independent call or asks you to bypass normal controls.
Does multifactor authentication stop phishing?
MFA can reduce the damage from a stolen password, but it is not a guarantee. Attackers may attempt to persuade a victim to read an authentication code aloud, approve an unexpected prompt or sign in through a malicious page that captures the session. Never disclose a code or approve a request you did not initiate.
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| Control | Attack path it helps address | Limitation to plan for |
|---|---|---|
| MFA on email, financial and administrator accounts | Some credential-theft and account-takeover attempts | Does not stop a victim from approving or revealing a fraudulent authentication request |
| Hardware security key | Can add a physical verification step for compatible accounts | Compatibility varies; the reviewed official guidance does not establish a particular model |
| Email filtering and authentication controls | Reduce exposure to malicious messages and spoofed domains | Determined attackers may use legitimate services or new infrastructure |
| Independent callback procedures | Payment fraud, executive impersonation and supplier-account changes | Works only when staff use a trusted number or directory, not the message’s contact details |
Choose controls by the attack path you need to reduce—credential theft, account takeover, payment fraud or malicious links—and by whether the control fits your accounts and workflow.
How organizations should adapt
Organizations need overlapping measures because no single clue reliably identifies AI-generated content. Combine technical controls with recurring education and a process that makes unusual requests harder to approve.
Reduce delivery and exposure
- Use email authentication, filtering, attachment and link analysis, and protections for mobile messaging where available.
- Protect administrator, finance and executive accounts with MFA and least-privilege access.
- Monitor for suspicious sign-ins, impossible travel, unusual payment behavior and newly registered or look-alike domains.
Train for realistic scenarios
Training should include polished email, smishing, voice-clone calls, fake video meetings and requests that move conversations to another platform. Teach employees to verify through known contact routes, protect MFA codes and report near misses without delay. NIST’s December 2025 preliminary draft calls for updated personnel training and integrated automated email and authentication defenses.
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Require two-person approval for unusual transfers, independent confirmation of changed payment details and a documented callback path. Make the secure action the convenient action by publishing the correct directory and escalation contact. A rule that exists only in a policy document will not help when a convincing voice demands immediate action.
What remains uncertain
Official sources establish that AI is being used to improve familiar social-engineering methods and that criminals are experimenting with voice and video impersonation. They do not establish a quantified, universal increase in phishing success rates or a dependable detector for AI-generated content.
CISA’s January 2024 material addresses election-related risks and says generative AI may amplify existing threats; it should not be read as a general crime-rate measurement. NIST’s December 2025 document is an initial preliminary draft, so its discussion of AI-assisted malware and autonomous attack orchestration should be treated as an evolving assessment rather than a measured trend.
The practical decision rule
Whenever a message asks for credentials, an MFA code, money, sensitive information or a link click, treat the request as unverified until you confirm it through a channel you already know is genuine. A familiar voice, polished prose and convincing video can support an impersonation; independent verification is what establishes identity.
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