LinkedIn Bots: How 80M+ Fake Accounts Threaten Your Brand

LinkedIn bots are automated or AI-generated accounts that fake professional identities, inflate engagement, and run mass outreach. LinkedIn removed 80.6 million fake accounts at registration in the second half of 2024 alone, and its automated defences now catch more than 97% before any member reports them (LinkedIn Community Report). The scale is real, the brand and hiring risks are real, and most leaders aren't measuring either.

If you run marketing, sales, or hiring through LinkedIn, you're operating on a network where a large share of accounts, engagement, and inbound messages aren't human. That changes what your metrics mean and where your risk sits. This isn't a rant about spam in your inbox. It's about what happens to brand trust, lead quality, and fraud exposure when the platform underneath your pipeline is partly synthetic.

How big is the LinkedIn bot problem?

Big enough that LinkedIn publishes the numbers itself. In the second half of 2024, LinkedIn identified and removed 80.6 million fake accounts at the point of registration, up from 70.1 million in the prior six months (Rest of World, citing LinkedIn's transparency report). In the first half of 2025 it removed roughly 83.4 million.

The detection side tells you how aggressive the problem has become.

Metric (LinkedIn Community Report)	Figure
Fake accounts removed at registration, H2 2024	80.6 million
Fake accounts removed at registration, H1 2024	70.1 million
Fake accounts removed, H1 2025	~83.4 million
Caught by automated defences before any report (H1 2025)	97%+
Stopped proactively, before a member report	99.7%

Source: LinkedIn Community Report and Rest of World.

Two things follow. First, the accounts LinkedIn catches are the ones you never see, which is good. Second, these are the ones that got through the door before being stopped, which means the volume attempting to enter is enormous. The bots in your feed and your inbox are the survivors of that filter.

Are LinkedIn profiles using AI-generated faces?

Yes, and this isn't new. Back in 2022, researchers Renee DiResta and Josh Goldstein at the Stanford Internet Observatory found more than 1,000 LinkedIn profiles using faces generated by AI, specifically generative adversarial networks (NPR). Most weren't running disinformation. They were sales and lead-generation fronts: connect with the fake persona, and a real salesperson eventually takes over (Silicon Republic).

That was four years ago, with the clumsy first generation of face generators. The eyes sat dead-centre, the backgrounds blurred into nothing, the ears didn't match. Today's image models leave none of those tells. The fake profile that messages your sales team this quarter is far harder to spot than the ones Stanford flagged.

Why should marketing and brand leaders care about bot engagement?

Because your engagement data is now partly fiction, and you may be paying real money to chase it.

Three risks stack up here.

Your reach and engagement numbers get inflated by accounts that will never buy. If a post's likes and comments come partly from automated engagement pods or bot accounts, the "virality" you're reporting upward isn't demand. It's noise dressed as signal.

Your lead quality degrades. When mass-outreach tools scrape and message at scale, your SDRs spend time qualifying ghosts. The cost per genuine conversation rises even if your cost per "connection" looks flat.

Your brand sits next to the dark patterns. The AEO industry is already getting penalised for manipulation. The same logic applies on social: a brand that buys followers, runs engagement pods, or automates fake comments is one screenshot away from a credibility problem. Smart buyers and journalists can read an inflated account now, and they're starting to look.

We've written before about the broader collapse of trust when automation floods a channel. LinkedIn is that collapse happening on the one platform most B2B brands treat as safe.

What is the hiring and fraud risk from fake profiles?

This is the part most boards underestimate. Fake profiles aren't only a marketing nuisance. They're an emerging fraud vector in hiring.

Gartner predicts that by 2028, one in four candidate profiles globally will be fake (HR Dive, citing Gartner). In a Gartner survey of 3,000 candidates in Q2 2025, 6% admitted to some form of interview fraud, either posing as someone else or having someone else pose as them (Gartner).

The downstream risk is what should worry a CISO. Once an impostor is hired, especially into a remote role, they can install malware, exfiltrate customer data, or steal funds. Google and Cisco have reportedly reinstated in-person interviews specifically to counter the flood of AI-assisted impostors (CNBC). When two of the most sophisticated tech companies on earth walk back remote interviewing, that's a signal about identity assurance, not about office culture.

What should leaders actually do about it?

Stop treating LinkedIn bot activity as an inbox problem and start treating it as a data-integrity and identity problem. Here's the practical sequence.

Action	Why it matters
Discount inflated engagement	Report genuine replies and qualified conversations, not likes and connection counts
Audit your own tactics	If your agency runs engagement pods or auto-comments, kill it before it becomes a brand liability
Verify identity in hiring	Add liveness checks or a short live video step for remote roles; reinstate at least one in-person or live stage
Train SDRs to spot synthetic profiles	New account, no real activity history, generic headshot, instant pitch on connect
Govern the AI you deploy	Set a written policy on how your own teams use automation, so you don't become the problem you're complaining about

The last one matters most, and it's where a Responsible AI lens earns its keep. The instinct under pressure is to fight automation with more automation: more scraping, more auto-DMs, more AI-written posts. That's the race to the bottom. The defensible position is the opposite. Run your AI-era outreach and content with guardrails, verify who you're actually talking to, and make authenticity a visible part of how your brand operates. In a feed full of synthetic professionals, being provably human is a competitive edge, not a handicap.

Frequently asked questions

How many fake accounts does LinkedIn remove?

LinkedIn removed 80.6 million fake accounts at the point of registration in the second half of 2024, and roughly 83.4 million in the first half of 2025. Its automated defences catch more than 97% before any member reports them, and 99.7% are stopped proactively (LinkedIn Community Report).

Can you tell if a LinkedIn profile is AI-generated?

It's getting harder. Early AI faces had clear tells: eyes locked dead-centre, blurred or warped backgrounds, mismatched accessories. Modern image models have removed most of those. Better signals now are behavioural: a recent creation date, no genuine post or comment history, a generic job title, and an immediate sales pitch the moment you connect. Our executive guide to LinkedIn bot detection walks through the checks.

Is using LinkedIn automation against the rules?

Yes. Automated scraping and bulk messaging violate LinkedIn's terms of service, and the platform actively detects and restricts accounts that do it. Beyond the account risk, it's a brand and legal exposure. We cover the specifics in LinkedIn automation and terms-of-service violations at scale.

Why are fake LinkedIn profiles a hiring risk?

Because synthetic identities are moving from sales fronts into recruitment. Gartner expects one in four candidate profiles to be fake by 2028, and impostors hired into remote roles can plant malware or steal data. That's why some major tech firms have brought back in-person interview stages.

The bottom line

LinkedIn isn't dying, and the "bots talking to bots" framing overstates it. Here's the honest read: the platform is doing more than most people realise to remove fake accounts, and it's still being overwhelmed at the entry point. That gap is your problem to manage, not LinkedIn's to solve for you.

My view, plainly: every brand running marketing, sales, or hiring through LinkedIn should treat its engagement numbers as partly synthetic until proven otherwise, and should put identity verification into hiring now rather than after an incident. The companies that win the next few years won't be the ones with the biggest automated reach. They'll be the ones whose audience can trust that there's a real person and a real standard behind the account. In a network filling up with fakes, that trust is the whole game.

VerityAI advises boards and leadership teams on exactly this: governing AI use, protecting brand integrity, and building the verification practices that keep a business credible while everyone else automates themselves into a corner.

If you want support with this, VerityAI offers responsible AI governance.