AI Automation
9 min read

What Are Deepfakes? (And Why Your Business Needs to Pay Attention)

Published on
July 27, 2025
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Your head of marketing just Slacked: “Is this video of our CEO saying we’re merging with a competitor real?”

It takes you a second to respond because... it kinda looks real. Same voice. Same mannerisms. Same background as last week’s webinar. But nope—it’s bogus. Totally fabricated. And you’re now 30 seconds into a full-body sweat about how the hell you’re supposed to stay ahead of this kind of thing.

Welcome to the wonderful and chaotic world of deepfakes.

If you’re running a small business, managing a marketing team, or helping clients wrangle their systems—this isn’t just a weird corner of the internet anymore. Deepfakes are crawling out of Reddit threads and into real-world operations, marketing campaigns, and yes, the occasional PR disaster.

Let’s break down what they are, how they work, where the real threat (and opportunity) lies—and what scrappy teams like yours can actually do about it.

What Are Deepfakes?

Short version? A deepfake is a synthetic piece of media—usually video, audio, or images—made using AI to look and sound real. You’ve probably seen the TikToks of a fake Tom Cruise or the Morgan Freeman that isn’t. Weirdly entertaining, slightly unsettling, and freakishly convincing.

The term itself blends "deep learning" (a type of machine learning) with “fake.” Catchy, right? What’s behind it is a little juicier—and way more important if you deal with digital content in any capacity (which, let’s be real, you do).

How Deepfakes Actually Work (No, It’s Not Just Fancy Photoshop)

Deepfakes use something called GANs—or Generative Adversarial Networks. Think of it like this:

  • The Generator is the smooth-talking artist cranking out fake content
  • The Discriminator is the suspicious friend trying to catch them in a lie

They go back and forth, over and over, until the fakes are really good—and borderline indistinguishable from the real stuff.

To pull off a believable deepfake, here’s what a typical setup looks like:

  1. Data Collection: You need tons of data. Images, videos, audio of the person you're mimicking. The more angles, expressions, lighting setups—the better.
  2. Training: You feed that data to an AI, which learns the micro-details of how that person looks, speaks, and moves. Facial tics, voice cadence, subtle eye movements—it gets creepy fast.
  3. Generation: The AI builds a new video or audio clip, reconstructing your target in a totally new context—like saying something they never actually said.
  4. Refinement: The result gets polished and iterated until it’s ultra-realistic. And sometimes only detectable by (you guessed it) more AI.

And no, this isn’t science fiction. These tools are available right now—some even free. That’s a blessing and a curse, depending on which end you’re on.

Why This Matters for SMBs, SaaS Teams, and Scrappy Marketers

Okay, so you’re not Netflix. You don’t need to worry about someone impersonating your CEO in a blockbuster. Still—you absolutely need to know what deepfakes could mean for your work.

Here’s the good, the bad, and the strategic.

The Opportunity Side (Yes, There Is One)

Despite their reputation, deepfakes aren’t just for scams. Used ethically—and creatively—they can unlock serious value:

  • Personalized Marketing Videos: Imagine auto-generating customer-specific videos where a virtual brand rep calls them by name and tailors the message. Feels intimate, but done at scale.
  • Content Localization: Record once, then translate and deepfake different language versions with accurate mouth and voice sync.
  • Training + Simulation: Deepfakes let you build realistic training scenarios that feel real—and stick better—without flying people across the country or casting actors.
  • Virtual Product Walkthroughs: Use a deepfake spokesperson to demo evolving product updates without reshooting footage every sprint.

More than 60% of marketers say they plan to use synthetic media (like deepfakes) by 2025. That’s not a fluke—it’s strategic. Done right, this tech can drastically cut production costs, boost engagement, and stretch creative capacity.

The Dark Side (Let’s Not Pretend It Doesn’t Exist)

Here’s where the “dystopian” headlines enter: deepfakes are already being used for fraud, manipulation, and misinformation. You’ve got scams where AI replicates the CEO’s voice to request funds. Fabricated political videos. Or PR landmines where a competitor fakes a scandalous endorsement “from your team.”

It’s hit the point where detection tech is now a booming industry, with $300M+ expected in investment by 2025.

The real risk isn’t just that someone might impersonate you. It’s that your customers, employees, or clients might lose trust in what they see or hear—and that’s way harder to rebuild than a social media post.

Misconceptions We Need to Clear Up

  • “It’s just goofy TikToks.” Nope. Those are face swap filters—entry-level stuff. Real deepfakes use trained AI models that can mimic voices and mannerisms to the point of fooling most humans (and some AI too).
  • “It's only about video.” Try again. Audio deepfakes are gaining ground—and may be harder to detect. Someone can fake a phone call from your CFO asking for an urgent wire transfer. Yikes.
  • “Only bad actors use this.” Honestly? That’s like saying only hackers use VPNs. Tools are tools. Brands, museums, Hollywood, training orgs—they’re already using deepfakes in some form.

How to Stay Ahead (Without Becoming a Paranoid Cyborg)

No need to overhaul your department overnight. But savvy teams are starting to take a few smart steps:

  • Start tracking use cases for your team: Where do you use video, personalized outreach, or training simulations? Chances are, at least one of those could be upgraded with synthetic media.
  • Get educated on the tools: Some teams are already experimenting with face mapping software, AI voice cloning, and localized avatars. Good news: there are plug-and-play options for all of it.
  • Double down on authenticity: Ironically, the rise of deepfakes makes realness more valuable. Emphasize your brand voice, POV, transparency—because that’s harder to fake consistently.
  • Have an internal playbook for media validation: If a rogue video pops up, your team should know what to do. (No, pinging the intern to “check the comments” is not a strategy.)

Bonus tip: Teams who are already using AI for content repurposing and lead follow-up? You’re ahead of the curve. The same mindset applies—replace what’s manual, keep what’s meaningful.

Okay, So What Can You Actually Do Next?

Look—this isn’t about doomscrolling. It’s about designing your business to use these tools on purpose. If you know where your time and energy is leaking, and you're already stretching a marketing team thinner than your agency budget—this tech can be a force multiplier.

At Timebender, we build custom and semi-custom AI systems that handle the “grunt work” in your sales, marketing, and onboarding flows. And yes, that includes helping you safely and smartly fold in tools like synthetic video, AI-powered voice, and automated content delivery.

The point isn’t “look at this futuristic thing.” It’s: how can your team stop duct-taping systems together and start using AI as a real productivity engine?

Book a free Workflow Optimization Session and let’s map what would actually save you time, keep your content smart, and put guardrails in place—so your team doesn’t have to panic the next time a fake CEO video shows up in Slack.

Sources

River Braun
Timebender-in-Chief

River Braun, founder of Timebender, is an AI consultant and systems strategist with over a decade of experience helping service-based businesses streamline operations, automate marketing, and scale sustainably. With a background in business law and digital marketing, River blends strategic insight with practical tools—empowering small teams and solopreneurs to reclaim their time and grow without burnout.

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