Avoiding the Wild West: Bringing Order to AI Use in the Workplace

(Spoiler alert for the current season of The Morning Show, Season 4)

AI isn’t a “future trend” anymore. It’s already in your office, writing, summarizing, automating, and occasionally hallucinating its way through your workflows. Whether you signed off on it or not, your team is using AI.

Without structure, that adoption can go from exciting to chaotic fast. Think less Silicon Valley success story, more The Morning Show Season 4, when Stella’s shiny new AI platform crashed live and started replaying all her worst private comments. Ambitious idea, total system meltdown, and a very public reminder that “move fast and break things” isn’t a governance model.

The rush to publish “AI content” without proper review is a lot like Stella’s AI fiasco. You launch fast to look innovative, then watch in horror as the system starts spitting out everything you never wanted the world to hear.

Back in 2023, CNET quietly started publishing AI-written articles under human bylines. The goal? Save time and embrace innovation. The reality? They pushed out content riddled with factual errors, plagiarism, and the kind of confident nonsense only a bot could produce.

The fallout hit hard:

Dozens of corrections: Out of 77 AI-written articles, 41 had to be corrected, more than half.

Angry staff: Over 100 CNET employees unionized in direct response to the AI rollout, citing transparency issues and erosion of editorial integrity.

Layoffs: Within months, roughly 10% of the newsroom was cut, a “restructuring” that looked suspiciously like damage control.

A major dent in trust: Red Ventures sold CNET the next year for about half its prior value after deleting thousands of pages to salvage credibility.

AI didn’t ruin their reputation. Lack of oversight did.

If your team is using AI but you don’t have standards, training, or review systems in place, you’re gambling with your brand. That’s exactly why we built our AI Corporate Trainings at Imagine Social — to help businesses use AI responsibly before their next big “live demo” moment becomes a PR crisis.

1. Audit what’s already happening

Spoiler: your people are already using AI more than you think.

What to look for:

• Which tools are being used across departments

• What types of data are being uploaded into those tools

• Where AI output is showing up in public-facing channels

If you can’t see it, you can’t manage it. An audit gives you visibility and control before something breaks, or worse, starts talking back.

2. Set policies that are actually usable

“Be careful” isn’t a policy. Spell it out:

• Which tools are approved and why

• What data is off-limits and cannot be shared

• Who reviews AI-generated work before it’s published

Good guardrails don’t kill creativity; they keep you from starring in your own newsroom meltdown.

3. Get every department on the same page

AI misuse doesn’t just break processes; it fractures your brand voice. Marketing writes like a stand-up comic, operations sounds like a robot, and sales? They’re quoting ChatGPT like scripture.

Create shared standards for tone, formatting, and quality. When everyone plays by the same rules, your brand sounds unified, human, confident, and trustworthy, not like an AI that forgot its filter mid-broadcast.

4. Train like it matters (because it does)

Policies are useless if no one understands them.

Build AI education into onboarding and professional development. Teach people:

• How AI affects search rankings and social reach

• How to use approved tools correctly

• How to spot low-quality or risky output before it hits “publish”

  
  

Knowledge isn’t just power; it’s protection, the difference between a smooth broadcast and watching your AI go rogue in front of millions.

5. Assign ownership

AI governance isn’t a “whoever-has-time” project. Someone has to steer the ship before it crashes live on air. Put a cross-functional team in charge, legal, HR, IT, and operations. Clear accountability keeps you out of headline territory.

The Bottom Line

AI won’t destroy your brand. But reckless use will. With the right structure, you get innovation without the chaos. Guardrails and training turn AI from a liability into a competitive advantage that makes your company faster, smarter, and infinitely more credible.

Because at the end of the day, this isn’t the Wild West anymore. It’s the AI Frontier, and if you’re still riding without a map, it’s only a matter of time before your brand ends up like Stella’s broadcast, ambitious, impressive, and suddenly very, very public for all the wrong reasons.

Our AI Team Trainings help companies move past the Wild West stage. We show your teams how to use AI responsibly while protecting your brand’s visibility, credibility, and long-term growth.

Start the conversation: book a mini discovery call today.

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About the Author

Angie Pelkie is a Business Development Strategist at Imagine Social, where she focuses on helping brands integrate AI into their marketing and operations. She guides business owners and professionals through the shift to AI-driven systems that build visibility, credibility, and long-term growth.

At Imagine Social, we specialize in AI-powered websites, content engines, and marketing systems that generate leads and protect brand authority across Google, AI platforms, and voice search. Our team of digital marketing and AI experts is setting new standards in how businesses adapt to search, content, and automation in 2025 and beyond.

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FAQ: AI Team Trainings

1. Why do companies need AI governance?

AI governance gives structure to how your team uses tools like ChatGPT, automation platforms, and writing assistants. Without it, employees may share private data, publish unverified content, or create reputational risks. Governance helps set clear boundaries so innovation happens safely and responsibly.

2. What happens when businesses use AI without oversight?

Without oversight, AI adoption can spiral into chaos. Teams start using different tools with no review or security checks. That leads to inconsistent messaging, data leaks, and credibility loss. The CNET example showed how poor review systems can turn “innovation” into a public trust issue overnight.

3. How can a company audit AI use internally?

Start by identifying which AI tools are already in use across departments. Review what data employees are entering, where that data goes, and where AI-generated content is being published. This gives you visibility and control before a mistake becomes public.

4. What should be included in an AI policy?

A strong AI policy lists approved tools, outlines what data cannot be shared, and defines who reviews AI outputs before they go public. It should be simple, specific, and part of onboarding so everyone knows what’s allowed and what isn’t.

5. How do corporate AI trainings help?

Corporate AI trainings turn general awareness into real skill. They teach teams how to use tools correctly, recognize low-quality or risky output, and understand how AI affects search rankings and brand visibility. Training ensures your people know how to innovate without risking your reputation.

6. Who should own AI compliance inside a company?

AI oversight should be shared across departments like IT, HR, legal, and operations. No single person can handle it alone. Cross-functional ownership keeps policies consistent, data protected, and accountability clear.

7. What are the risks of unregulated AI content?

Unregulated AI content can damage credibility fast. It may include plagiarism, factual errors, or outdated information that misleads customers. Once trust is broken, recovery is slow and expensive. AI itself isn’t the problem; lack of quality control is.

8. How can AI be used safely for marketing and content creation?

Use AI as a support system, not a replacement for human review. Generate first drafts or outlines, then fact-check, edit, and personalize before publishing. Keep brand voice consistent and verify every claim. Structure and human oversight make AI your ally, not a liability.