Enterprise AI Pricing - The expensive lessons nobody warned me about

Just wrapped up 9 months of AI implementation hell at my current company. Third time doing this dance, and I still managed to fuck up the budget estimates by about 150%. You'd think I'd learn.

Claude's not as expensive as you think (until it is)

Started with Claude because their pricing page doesn't look like a slot machine. $20 for individual, $25/user for teams, call for enterprise. Seemed straightforward. Their features comparison looked promising and the API documentation was actually readable.

First nasty surprise: Claude's team plan actually works pretty well for small dev teams. The gotcha that nobody explains clearly is that prompt caching shit - when you paste big codebases for review, it auto-caches them and charges you extra. I had no idea this was happening in the background until our bill jumped from around $480 to $1,847 one month. Spent three hours trying to figure out where the extra charges came from before I found that buried token counting guide.

The dashboard updates slow as hell - usually 4-6 hours behind real usage, sometimes longer on weekends. So you can't tell if someone's burning through your budget until you're already fucked. Learned to manually check usage every few days because I don't trust their alerts.

SCIM setup was a complete fucking nightmare. Their docs say "plug and play" but our Azure AD integration took Sarah from IT about two weeks of back-and-forth with their support team. She was not happy about it. Still not sure we got it right - people get randomly logged out maybe once a week and nobody knows why.

OpenAI will bankrupt you if you're not careful

Been using OpenAI the longest, back when GPT-3 was the only game in town. Their individual ChatGPT Plus is fine for $20/month, but enterprise is where things get weird. The API documentation is comprehensive but dense.

Enterprise starts at something like $60/user but that's just the subscription fee - the real killer is API calls. We built a customer service bot using their Chat API and the API usage hit $2,847 our first month in production. Sales never mentioned API costs would be separate. Their usage tiers also affect pricing in ways that aren't obvious until you hit them.

Rate limiting is absolutely brutal. We had a traffic spike on a Tuesday afternoon and OpenAI just started spitting back 429 errors with no warning. Took down our main customer-facing feature for about 6 hours while I frantically tried to figure out what was happening. Their enterprise support finally responded around 10 PM that night, but by then I'd already switched that feature over to Claude. Pro tip: bookmark their status page and check it obsessively.

The usage dashboard is better than Claude's but still lags behind by a few hours. You can set spend limits but they're soft limits - basically just email warnings that you went over budget. Found this out the hard way when our bill hit $4,200 one month.

Google's "free" AI isn't free

Gemini comes "bundled" with Workspace which sounds amazing until you dig deeper and realize the useful AI features need the Enterprise Plus plans. We were already paying $18/user for regular Workspace and had to upgrade everyone to $22/user just to get the AI shit that actually works. The Gemini for Workspace docs bury this requirement about six paragraphs down.

Then there's Vertex AI costs piled on top if you want to use their API for anything real. Those costs add up stupidly fast - I think we burned through around $1,173 one month just from document processing using their Gemini API. The billing documentation is typical Google bullshit - scattered across 47 different pages with no clear navigation.

The Workspace integration is supposed to be seamless but it broke our calendar sharing twice in the first month. Some confidential legal docs somehow got auto-shared externally - still gives me nightmares. Google's support team immediately blamed our config and it took them almost three weeks to admit there was actually a bug on their end. I'm still not 100% sure what went wrong or if it could happen again.

Context limits are way higher than the others which is nice, but there's some pricing jump around 200K tokens that I never fully figured out. The billing console is classic Google - buried six clicks deep behind three different menus, and the UI changes every few months just to keep you confused.

I've blown through AI budgets three times now at three different companies. Here's the expensive shit that actually happens when you roll this stuff out that nobody warns you about.

Month 1: Everyone discovers AI exists

First month is always chaos. Everyone wants to try the new shiny thing and nobody understands how usage-based pricing works.

With Claude, Jake from the backend team was pasting entire repositories into chat for code reviews - like, literally copy-pasting 50+ files at once. Turns out that triggers their prompt caching bullshit which costs extra and nobody tells you it's happening. Bill went from around $190 to $1,640 before anyone noticed. The usage dashboard is delayed by 5-8 hours so you can't catch this kind of runaway spending until you're already fucked. Should have read that buried usage monitoring guide but who has time for that?

OpenAI was infinitely worse. Amy from marketing built some content generation script using the Chat Completions API and let it run over a weekend to "batch process blog ideas." Monday morning I walk into the office and there's a $2,847 API bill waiting for me. Apparently their spend limits are just polite suggestions, not actual hard limits that stop billing. The billing FAQ makes this clear as mud.

Gemini seemed safer at first since it's "bundled" with Workspace. Then we realized we needed to upgrade everyone to the $22/user Enterprise plan to get decent AI features. Plus Vertex AI charges for API usage on top of the subscription.

Integration hell (budget 3x whatever you think)

SCIM and SSO setup always takes 3-5x longer than anyone estimates. Ended up bringing in consultants for all three platforms because the docs are either completely wrong or skip the 47 gotchas that will break your integration.

Claude's SCIM integration with Azure AD was a complete shitshow. Their documentation cheerfully says setup takes "minutes" but Sarah from our IT team spent almost three weeks troubleshooting weird provisioning errors and group mapping issues. People still get randomly logged out maybe twice a week and nobody has any idea why. I'm pretty sure we fucked something up during setup but the Azure AD provisioning docs are about as helpful as a chocolate teapot.

OpenAI's enterprise sales process is pure torture. Eight fucking weeks of security reviews, compliance theater, and legal back-and-forth before they'll even give you real pricing. Then you finally sign the contracts and discover that the subscription cost they quoted doesn't include API usage, which is where they actually make their money. Sales conveniently forgot to mention that detail.

Google's integration actually worked pretty well at first, which should have been a red flag. Then it randomly broke our calendar permissions and somehow auto-shared some confidential legal documents externally. Still have nightmares about explaining that to the CEO. Support took almost a month to fix it and spent the whole time insisting it was our fault and our configuration was wrong.

What we actually spent vs what we budgeted

Small dev team (8 people):

• Budgeted: $200/month total
• Claude actual: ~$800/month (prompt caching kills you)
• OpenAI actual: ~$1,100/month (API usage adds up fast)
• Gemini actual: ~$600/month (if you're already on Workspace)

The lesson: whatever number you have in mind, triple it for the first six months while everyone figures out how not to burn money.

The dumb mistakes that cost real money

Left API keys in a public repo. Someone found them and racked up $400 in charges before we noticed. OpenAI was decent about refunding most of it.

Built a customer service bot that went into infinite loops. Spent maybe $600 on API calls that accomplished nothing. Rate limiting finally stopped it.

Enabled "smart" features in Workspace that auto-processed old documents through Vertex AI. Burned through $1,200 in background processing we didn't even know was happening.

Set up monitoring alerts for spending but set the thresholds too high. By the time the alerts fired, damage was done.

What I'd do differently next time

Start with individual accounts only. Let 2-3 power users figure out the platforms before rolling out to teams.

Set hard spending limits on day one, not soft alerts. Yeah, it might break stuff but it's better than surprise bills.

Don't trust the dashboards - they lag behind real usage. Check spending manually every few days.

Budget consultant time for integrations. The "plug and play" marketing is bullshit. Plan for weeks, not hours.

Keep marketing and content teams away from API access until you understand the real costs. They'll bankrupt you by accident.