7 Social Selling + AI Commerce Myths: Where Influence Meets Intelligence

If you’re an electrical manufacturer or distributor, you’ve probably been told some version of this: “If we just do better social media — influencers, reels, viral demos — the sales will follow.” That used to be mostly true. But something fundamental has changed.

Today, buying decisions in the trades are increasingly shaped by AI-driven answers, not just social proof. Electricians still discover products on social media — but they validate and decide using AI-powered search, recommendations, and comparisons.

Understanding the difference between social selling and AI commerce is now a competitive advantage. But understanding how they can work together is where your real money will be made.

This article breaks down the biggest myths we see in the trades — and what actually works if you want your products, tools, or brand to show up where decisions are being made.

Social selling and AI commerce are not the same thing

While both are increasingly powerful tools for sellers, they aren’t the exact same thing. They can however be strategically leveraged together, when you understand how social platforms and AI chatbots work. Let’s define terms clearly. Social selling influences people. It builds awareness, trust, and familiarity through platforms like Instagram, TikTok, Facebook, and LinkedIn.

AI commerce influences decisions in AI chatbots like ChatGPT. It answers questions like:

• “What’s the best option for this job?”
• “What do electricians actually use?”
• “What works — and what fails — in the field?”

As of January 2026, most AI chatbots don’t browse feeds (yet). They don’t watch reels. They don’t care about follower counts. AI summarizes documented experience. That gap is where most brands lose visibility.

That’s one of the reasons Trade Hounds is building our AI commerce platform right inside of America’s largest social media app for tradespeople. We’re combining the power of social selling and AI commerce in one app. But manufacturers and distributors can’t live off Trade Hounds alone. In 2026, an omnichannel approach is even more crucial. Even Trade Hounds has an account on Instagram, Facebook, YouTube, LinkedIn and TikTok. That’s because SEO, which used to mean search engine optimization, now means search everywhere optimization.

The goal is to be everywhere your buyers are. That can seem like an unsurmountable task. That’s why we’re here to save you time and help you make the most of your social presence so you’re more discoverable on AI answer engines. Let’s start by debunking myths about how social media and AI answer engines work together.

Myth #1: “If it goes viral, AI will pick it up”

Viral content feels powerful — and for human awareness, it is. But virality is:

• Short-lived
• Platform-contained
• Optimized for emotion, not explanation

AI systems don’t track views, likes, or shares. They rely on durable, crawlable explanations that appear consistently across public sources.

Why this matters in the trades: A viral reel might show a breaker installing faster — but AI needs to understand:

• Why it installs faster
• Who benefits (retrofit vs new construction)
• When it’s the wrong choice
• What it replaces or competes with

Without that written context, the product effectively disappears from AI-driven answers.

Actionable takeaway: Every viral post should trigger a follow-up asset — ideally a 700- to 1,500-word article, FAQ, or use-case page that explains what the video shows on a public website.

Myth #2: “Influencers with big followings matter more to AI”

AI cannot yet see:

• Follower counts
• Likes
• Engagement metrics
• “Verified” badges

What AI can see:

• Job roles
• Credentials
• Field experience
• Step-by-step explanations
• Repetition across sources

A licensed electrician with 2,000 followers who explains why they use a product in specific scenarios is far more valuable to AI than a lifestyle influencer with 200,000 followers saying “this is my favorite.”

What actually builds AI authority

AI recognizes expertise when:

• A real person is named
• Their role is clearly stated (electrician, contractor, inspector, engineer)
• They are quoted or referenced across multiple public pages
• They explain decisions, not just outcomes

Actionable takeaway: Choose creators who can produce 300 to 1,000 words of explanation, not just short-form promotion. Or even better, opt for a short reel for Instagram and a longform video on YouTube. That way, real followers can watch the short reel and AI answer engines can pull in-depth information from YouTube transcripts, headlines, descriptions and tags. This also helps with your SEO to boost your brand in traditional search engine results like Google.

Myth #3: “AI shops the way people shop”

People browse:

• Videos
• Images
• Catalogs
• Prices

AI answer engines prefer to answer questions by summarizing:

• Comparisons
• Pros and cons
• Use cases
• Failure modes
• Consensus from documented experience

If your product doesn’t have:

• Comparison pages
• “Best for / not for” explanations
• Use-case-specific guidance

AI will either ignore it — or let competitors define it for you.

Actionable takeaway: If you haven’t written comparisons, AI will compare you anyway. While marketing and ecommerce teams may have been focusing on clean product data for a while now, it is worth repeating that the foundation is data that AI can easily read. Making sure your website’s product data is as enriched and up to date as possible is now even more important because AI answer engines rely on it.

Myth #4: “Our Instagram explains how the product works”

Social media videos are excellent at showing what happened. This is fantastic for humans.

AI needs to understand:

• Why it works
• How it behaves in different conditions
• When it fails
• What installers need to watch out for

A 30-second demo cannot communicate:

• Code nuance
• Inspection concerns
• Environmental constraints
• Edge cases in the field

Actionable takeaway: Every demo should become:

• A written install sequence (300–500 words)
• A “common mistakes” section
• A “when not to use this” explanation

Myth #5: “AI will figure out our product on its own”

AI is only as accurate as the information it’s given. When key details are missing, AI:

• Assumes
• Generalizes
• Or excludes the product entirely

This is especially risky for:

• Innovative products
• Hybrid solutions
• New categories

If you don’t clearly define:

• What category you’re in
• What you replace
• What you don’t replace

AI will guess — and guesses are rarely favorable.

Actionable takeaway: Every product needs a clear, written answer to: “Who is this for — and who is it not for?”

Myth #6: “Social selling is AI commerce”

Social selling and AI commerce operate at different stages of the buying journey.

Social selling:

• Creates awareness
• Builds trust
• Starts conversations

AI commerce:

• Reduces uncertainty
• Confirms decisions
• Validates choices before purchase

In the trades, this often looks like:

• Discover product on social
• Ask AI or search to verify
• Confirm with distributor or peer
• Buy

If AI can’t verify what social promised, the deal stalls.

Actionable takeaway: Social content must feed decision-ready documentation.

Myth #7: “AI replaces relationships”

AI doesn’t replace trust — it replaces confusion.

Relationships still matter for:

• Negotiation
• Exceptions
• Long-term loyalty
• Advocacy

What AI removes is:

• Repetitive questions
• Basic uncertainty
• Inconsistent explanations

Used correctly, AI-powered content makes your sales team, reps, and distributors more credible, not less relevant.

The practical rule every manufacturer should remember: if a human can watch it but an AI can’t read it, it doesn’t count. Instagram creates belief. Websites create memory. AI only remembers what’s written.

At Trade Hounds, we see this every day: electricians and contractors discover products socially — but they make decisions based on clarity, proof, and documented experience.

The manufacturers who win the next decade won’t just be the loudest on social. They’ll be the clearest when AI is asked: “What actually works in the field?”

If you want help turning real-world trade expertise into AI-visible authority, that’s exactly the problem we’re here to solve.