LinkedIn Live Recap: AI, Plagiarism, Trust and Content Marketing

    LinkedIn Live Recap: AI, Plagiarism, Trust and Content Marketing
    7:12

    Both Annie Zelm and I have been plagiarized.

    In Annie’s case, she went looking for one of her Kuno blog posts to promote in an email, and the search turned up a near-identical article from another marketing agency. She reached out, and they took it down. And that was that: no C&D, no consequences beyond a page that now 404s.

    That story opened our recent LinkedIn Live, where Annie and I took on a topic that isn’t necessarily sexy, but necessary to address in this era. We both came up through journalism, where plagiarism ends careers. It’s something we take seriously, and with good reason. In marketing, the stakes can feel lower: after all, no content marketer is getting served papers.

    Generative AI makes it easier than ever to re/produce content at scale. The real cost of getting this wrong? Well, there is potential civil exposure, but the truer bill comes due in audience trust. For B2B brands, especially those with an Inbound mindset, trust turns content into demand and demand into pipeline.

    It Happens at Every Level

    Annie's experience isn't unusual. At MAICON 26, she spoke with Amanda Todorovich, who until recently led Cleveland Clinic's content operation. Competitors routinely repurpose their best-performing articles, the cease-and-desist letters keep going out, as does the printer toner.

    The data points the same direction. PlagiarismSearch, an academic plagiarism-detection service, reviewed roughly 70 million submissions between 2018 and 2024. In that timeframe, it flagged 15 to 19 percent as potential plagiarism, with notable bumps during the pandemic and again as gen AI took off in 2022.

    Let’s be fair in saying that these submissions are almost entirely academic work, not marketing collateral. Admittedly, it's not a perfect comparison, but it's a strong signal that the problem is growing, not shrinking.

    Detection tools won't save us, either. Plagiarism checkers and AI detectors are useful, but their limitations show more clearly as models get more sophisticated and begin consuming more and more AI-generated content. Nobody is going to win the AI content arms race, and there's still no substitute for the human eye and sound editorial judgment.

    Three Scenarios, Three Gray Areas

    We put three situations we’ve encountered over the years to our audience:

    1. Asking AI to rewrite a competitor's blog in your brand voice

    Roughly two-thirds of the audience called this plagiarism. We agree: Annie compared it to putting a fresh coat of paint on wood that's already peeling. You might get away with it, but you've skipped the most important question: what's your take?

    To me, the request itself is the tell. Plagiarism is a matter of intent as much as action. One also has to separate plagiarism from infringement. Plagiarism is an ethical failure; infringement is a legal one. (Neither of us is a lawyer, and this isn't legal advice.) You can plagiarize without breaking the law, but it's still wrong. It starts in the heart, not on a screen.

    2. Reviewing five articles, then AI helps to develop an outline

    Most viewers said this isn't plagiarism. We agree, that's research. You're taking a 30,000-foot view and surveying the landscape, seeing what competitors say, and finding what's missing.

    AI is great at getting you past the blinking cursor. Annie's preferred approach is to ask AI to interview her: What surprised you, What did you learn, What's the story here? Questions any journalist worth her salt would ask to establish context and create new lines of inquiry.

    3. AI produces language that closely matches something already published

    The audience split on this one, and that's fair. It really depends.

    A general statement, like ‘sales and marketing don't always get along,’ isn't going to land you in trouble. Generally accepted knowledge cannot be plagiarized. A specific story that isn't yours, or a summarized statistic without its original source, will. The fix is knowing where every piece of information comes from. Use AI's research features to get started, then check every link: it should be live, real, and point to the original study.

    Trust, but verify. One filter I rely on after nearly a decade of checking work is tonal shift. When the language suddenly doesn't flow the way the rest of the piece does, that's where I start digging. Annie's red flags: details that are suspiciously vague, or suspiciously specific with no context anywhere else.

    Original Content Is a Revenue Issue

    It's justifiable to treat plagiarism as purely an ethics problem, but ethics problems inevitably become business problems.

    SEO pressure pushes teams to mirror the results leading a SERP. Cover the basics. But content that never demonstrates original thinking or a clear point of view dilutes your brand and erodes audience trust. In B2B especially, buyers are already tuning out content that feels like recycled AI output. It's reasonable to expect search engines and AI crawlers to follow their lead, and Google already works to demote low-quality content and has for some time.

    Shortcuts usually show up where strategy is missing. When content is treated as a chore list instead of an extension of strategy, the ends start justifying the means. The fix isn't more tools and gadgets, but process and relationships: an editor who works alongside writers to make them better, and stakeholders who are aligned on what the content is supposed to accomplish.

    Some takeaways from our conversation:

    • Start with the point nobody else can make. Your own data, customer stories and explicit opinions act as both your best differentiator and best protection. Generic content is easy to copy, real case studies and real research and analysis aren’t.
    • Use AI for research and brainstorming, not substitution. Let it fill the blank page and put your core premise through the paces. The thinking stays yours, AI just acts as a spark plug to get the engine going.
    • Verify every source. Every stat should trace to a live link and an original study from a credible source, including the ones your SEO tools suggest. Where appropriate, obtain permission to restate any data from elsewhere.
    • Loop in stakeholders and your editor early. Second and third sets of eyes tend to catch what tools miss. This also helps inform strategy and sustains buy-in.
    • Check it before it ships. If it sounds like something else, it probably is. Better to catch it yourself than to get nailed with a C&D.

    Great work takes time. AI saves hours on tasks, but writing something worth someone’s time reading isn't where shortcuts pay off. Readers aren’t dumb; they can tell when there's a heartbeat behind the copy, and crafted content always wins out over the merely curated.

    Watch the Full Conversation

    This recap covers the highlights, but the full LinkedIn Live goes further. You'll hear how Annie discovered her work had been copied, our candid take on plagiarism-detection tools and get a look at the Plaig-o-Matic detection meter.

    Brent Sirvio
    the author

    Brent Sirvio

    Brent brings a marketing strategist's perspective and an incisive eye for language to ensure all content deliverables are compelling and accurate, adhering to brand and style guidelines and best practices. A member of ACES, Brent holds a BA from the University of Wisconsin-Stevens Point and a MA from Bethel University (MN). Sisu.
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