Every software vendor now trumpets AI features. “AI-powered!” “With AI!” “AI included!”

Most of these features go unused.

I’ve seen it repeatedly: businesses pay premium prices for AI features, then never touch them. Or use them once, find them underwhelming, and forget they exist.

Here’s how to cut through the noise.

The AI Feature Trap

Vendors add AI features because:

1. It justifies higher prices
2. It sounds modern
3. Competitors are doing it
4. It generates buzz

Notice what’s missing? Customer need.

Many AI features are solutions looking for problems. They exist because AI is trendy, not because customers asked for them.

Signs You’re Paying for Unused AI

The Upgrade You Forgot About

Vendor: “Our Professional tier now includes AI-powered insights!”

You: Upgrade. Never use the insights. Pay the premium anyway.

The Feature Nobody Opened

There’s an AI tab in your software. When did anyone last click it?

The Capability You Can’t Explain

If you can’t explain what the AI feature does in plain language, you probably don’t need it.

The Demo That Impressed, Then Nothing

The demo was slick. You bought. Six months later, nobody remembers the AI feature exists.

How to Evaluate AI Features

Question 1: What Specific Problem Does This Solve?

Not “improve productivity” or “enhance insights.” Specific problems.

“This analyzes customer emails to flag urgent issues before human review.”

That’s specific. You can evaluate whether it’s valuable.

“AI-powered customer intelligence.”

That’s marketing. It means nothing concrete.

Question 2: Who Will Actually Use This?

Not theoretically. Practically.

Name the person. Describe when they’d use it. Explain how it fits their workflow.

If you can’t do this, nobody will use it.

Question 3: What’s the Alternative?

Is there a simpler way to accomplish the same thing?

Sometimes the non-AI approach is faster, cheaper, and more reliable.

AI isn’t automatically better. Sometimes it’s just newer.

Question 4: What Happens Without This Feature?

If you had all the other features but not the AI one, what would you miss?

Often the answer is: nothing significant.

Question 5: Is This Core or Supplementary?

AI features that are core to the product matter. AI features tacked onto otherwise complete products often don’t.

An AI-native document processing tool is different from a document management system with “AI features” added later.

Categories of AI Features

Actually Useful

Predictive text and autocomplete. Saves typing. Low friction. Genuinely helpful.

Automatic categorization. When dealing with volume, automated sorting helps.

Anomaly detection. Finding outliers in data you couldn’t review manually.

Basic summarization. For long documents you need to skim.

Rarely Used

AI-generated reports. Usually require so much editing they’re not worth it.

“Intelligent” recommendations. Often wrong enough to be unhelpful.

Automated insights. Typically surface the obvious.

AI-powered forecasting. Garbage in, garbage out. Few have clean enough data.

Pure Marketing

“AI-enhanced” anything. Vague descriptor that often means minimal AI.

“Smart” features. Usually basic automation labeled with buzzwords.

“Cognitive” capabilities. Ten-dollar word for simple pattern matching.

The Right Approach

Start Without AI Features

Use the basic version first. Understand what you actually need.

Only then consider whether AI features would help.

Trial Specifically for AI

If AI features are the reason for an upgrade, trial them specifically:

• Use the AI features intentionally
• For your actual use cases
• With your actual data
• By your actual users

Don’t just trial the product. Trial the AI features that justify the extra cost.

Set AI Feature Goals

Before upgrading for AI: define what success looks like.

“The AI feature will save our support team 5 hours per week by auto-categorizing tickets.”

Measure after implementation. Did it deliver?

Budget Separately

Track what you’re paying for AI features specifically.

When renewal comes: ask whether you got value from that spend.

If not, downgrade.

Case Study: CRM AI Features

A client upgraded their CRM to the “AI-powered” tier. Extra cost: $50/user/month.

Features gained:

• AI lead scoring
• Predictive opportunity insights
• AI-generated email suggestions
• Smart contact enrichment

Six months later:

• Lead scoring: Used by one person, somewhat helpful
• Predictive insights: Never opened
• Email suggestions: Tried once, ignored since
• Contact enrichment: Useful, but available cheaper elsewhere

Was $50/user/month worth it? For 15 users, that’s $9,000/year.

The honest answer: no.

They downgraded. Bought a standalone contact enrichment tool for $100/month. Accepted that they didn’t need the other features.

Net savings: $7,800/year.

When AI Features Are Worth It

High Volume Operations

AI features make sense when you’re dealing with volume you can’t process manually.

1,000 support tickets/day? AI categorization matters.

10 support tickets/day? Just read them.

Pattern Recognition at Scale

Finding anomalies in massive datasets is genuinely valuable AI work.

If you have massive datasets. Most SMBs don’t.

Genuine Automation

When AI can actually replace manual work—not just assist—it’s valuable.

Auto-processing standard invoices saves real time.

AI “suggestions” that require just as much human review don’t.

Getting Honest Assessment

If you’re uncertain whether AI features justify their cost, outside perspective helps.

AI consultants Melbourne and similar specialists can assess which AI capabilities actually matter for your situation and which are marketing noise.

They’ve seen enough implementations to know what delivers value.

Vendor Negotiation

Armed with honest assessment, you can negotiate:

“We’re happy with the base tier. The AI features haven’t delivered value. Can we remove them and reduce price?”

Works more often than you’d think. Especially at renewal.

Or: “We want to trial the AI features for three months before committing to the premium tier.”

Reasonable vendors agree. Those who don’t are probably hiding something.

The Questions to Ask Vendors

When vendors pitch AI features:

1. “What specific problem does this solve for a business like ours?”
2. “Can you show usage statistics? What percentage of customers actively use this feature?”
3. “What results have similar businesses seen?”
4. “Can we trial these features specifically?”
5. “What’s the pricing without the AI features?”

Vague answers are warning signs.

My Recommendation

For most SMBs:

Start with base tiers. Get comfortable with core functionality.

Upgrade deliberately. Only when you’ve identified specific needs that AI features address.

Measure ruthlessly. Track whether AI features deliver promised value.

Downgrade willingly. If features don’t perform, stop paying for them.

Don’t chase AI features because they sound impressive. Chase solutions to actual problems.

If AI is the best solution, great. Often, it’s not.

Building AI Literacy

The better you understand AI capabilities, the better you can evaluate vendor claims.

Talk to people who’ve implemented AI. Read case studies critically. Understand what AI does well and poorly.

Team400 and similar specialists can help build this understanding. Not to sell you AI—but to help you evaluate it honestly.

The Bottom Line

AI features are often oversold and underused. That’s not a criticism of AI—it’s a criticism of marketing.

Good AI features solve specific problems at scale. Most AI features are buzzwords applied to basic functionality.

Know the difference. Pay for what you’ll use. Ignore the rest.

That’s right-sizing for the AI era.