When Your AI Goes Rogue: Why Not Training Your Custom AI Could Cost Your Business Big Time - Explore Gwinnett's Best in Business, AI & Tech News 2025

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IDo you have a custom AI? As a business owner, you may be tempted to let someone else build your AI for you—or simply plug in a generic AI solution and move on. But skipping the training step? That can lead to a disaster. Look no further than the recent mess over Truth Social’s AI tool to see why this matters. The Independent+2The Daily Beast+2

Here’s what happened, why it matters for your business, and how you can avoid the same pitfalls—all explained in plain English.

What went wrong — and why it matters

On his platform Truth Social (owned by Donald Trump), an AI-powered search/chat tool built in partnership with Perplexity began giving answers that contradicted the platform’s founder. For example:

It stated that his tariffs cost Americans money (contrary to his statements). Yahoo+1
It correctly indicated that courts and official investigations found no evidence the 2020 election was “rigged”. The Independent+1
It highlighted that the tool was sourcing a narrow set of media outlets (mainly conservative) thus showing bias. The Verge

In short: the AI tool was deployed without sufficient alignment to the owner’s messaging, and it ended up undermining rather than supporting the platform’s stated purpose.

The business lessons for you

If you skip or skimp on training your AI, here’s what can happen to your business:

Mismatched messaging and brand risk. The AI can say things off-brand, embarrassing your business or undermining your credibility.
Hidden bias or narrow sourcing. If the training data only reflects one viewpoint or is unbalanced, your AI may reinforce or exaggerate that bias. For a business trying to serve broad customers, that’s a major risk.
Loss of trust and customer confusion. If your customers get inconsistent or wrong answers from your AI, they’ll lose trust—and trust is harder to win back.
Legal and ethical exposure. Incorrect claims or misleading outputs generated by your AI can expose you to reputational damage or regulatory scrutiny.
Missed value. Without proper training your AI will under-deliver. You’ll pay for a tool that doesn’t boost productivity, doesn’t enhance customer service, and might even hurt your brand.

How to do it right: Your 5-step AI training checklist

Define your business voice and role for the AI. What is the AI meant to do? What values should it reflect? What tone should it use?
Curate high-quality, representative data. Make sure the training data reflects your brand, your audience, and the range of scenarios your business handles.
Test for bias and alignment. Check whether the AI is favoring one viewpoint or source unduly. The Truth Social case shows what happens when you don’t.
Provide guardrails and context. Give the AI boundaries: e.g., “If you don’t know the answer, say ‘I’m unsure’,” or “Only pull info from approved sources.”
Monitor, learn, and iterate. After deployment, track how the AI behaves. Are customers getting bad experiences? Are there unforeseen risks? Tweak regularly.

Why your business can’t afford to ignore this

As small or medium-sized business owners (which you are), many AI vendors will pitch “plug-and-play” solutions. But unless you do the training work, you’re essentially renting a tool you don’t own, don’t understand, and don’t control.

Consider this: you’re building your brand, you’re building trust, you’re building a reputation. One mis-step caused by an untrained AI can undo months—even years—of progress.

When the AI starts contradicting your message—or behaving in a way you didn’t expect—it becomes a liability, not an asset.

Realistic example for your coaching or content business

Imagine you run a business-coaching firm (much like your own experience). You deploy an AI chatbot for clients to ask business-growth questions. If that chatbot hasn’t been trained:

It may provide generic or even wrong advice (e.g., outdated tactics)
It may use tone or language inconsistent with your brand (which you’ve built carefully)
It may pull from sketchy or biased sources, giving clients wrong info
It may underperform so clients stop using it—and your investment goes to waste

But if you train it: you give it your voice, your frameworks (like your A.I.M.P.A.C.T.™ framework), your values, approved sources—and you monitor how it performs. Then you have a tool that supports your brand, frees you up, and scales your expertise.

Why the Truth Social example is a cautionary one

Because it shows how even a high-profile platform can mis-align when AI is deployed without careful control. The tool ended up exposing internal contradictions and sourcing bias. That’s the opposite of what you want your AI to do for your business.

When your AI mis-aligns, your brand credibility takes the hit—not the AI vendor.

Final takeaway

If you treat AI as a black box you plug in and forget—you’re asking for risk. For a growing business focused on brand, trust, expertise and scalability, you must treat AI like a partner you train, not a toy you launch.

By investing in training, alignment, monitoring and iteration, you turn AI into an extension of your business—and you avoid the kind of public mis-step we saw in the Truth Social rollout.

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