Find Out Which Department Is Costing You the Most — Before You Spend a Dollar on AI
Every department in your business is either a money maker or a money eater. Most AI spending goes to the wrong one because nobody checked first. In one 20-minute call, we’ll tell you which department has the most to gain, what it’s worth to your margin, and where to start.
- You’re being told to "adopt AI" without a clear reason why
- You don’t know which department is a money maker and which is a money eater
- Every vendor pitches a use case — none of them show you the impact on margin
No sales pitch. No obligation. Just a straight answer.
Trusted by 300+ companies, including
You Don’t Need to Understand AI. You Need to Know Where It Pays Off.
Some departments are money makers. Some are money eaters. Every department generates a different amount of revenue per person — the fastest way to know where AI is worth the investment is to find the one making, or losing, the most per head, and start there. That’s the whole game: increase revenue, reduce cost, grow margin.
Three Steps. One Call. A Clear Answer.
20-minute call
We ask about your departments, headcount, and where things slow down or cost more than they should. No technical questions.
We do the math
We rank your departments by revenue and cost per employee, and identify where AI has the clearest, fastest payoff.
You get the answer
A short written breakdown: which department to start with, what it’s costing you now, and what a fix is worth. No obligation to work with us.
This Is What "Which Department First" Actually Looks Like
Every one of these engagements started the same way this assessment does: find the department losing the most money, then fix that one first.
$214K a Year Recovered From One Scheduling Problem
The operations leader at a 25-store, $400M-revenue retailer knew something was off — the store-level schedule was eating $300K–$500K a year in avoidable meal- and rest-break violations, invisible until the audit caught it. Once the compliance engine was in place, violations dropped 85% in 90 days, recovering $214K/year in avoided premium pay, paid back in under 90 days. Weekend conversion moved too — up to 0.7 points, just from better peak-hour coverage. One department, found first, fixed first.
Read the Staffing Optimization Case Study →€1.24M penalty defused
"We used to find out about a schedule slip in the monthly steering call, three weeks after the window to act had already started closing," the portfolio manager said. Now the model flags it the day the data changes — €4.8M in exposure tracked continuously across a five-country portfolio.
Read the case study →$1.2M/year in IT costs cut
The content team at a global apparel retailer was stuck filing an IT ticket for every website update — slow, error-prone, and expensive. In three months, the fix saved $1.2M a year in IT costs and cut manual errors on the live site.
Read the case study →25% more sales efficiency
A private equity-backed lender’s operations lead was tracking the deal pipeline by hand, losing submissions and slowing underwriting down. The rebuild lifted sales efficiency 25% and cut average contract offer time 40% — margin recovered from a department nobody thought to check.
Read the case study →The Reasons Business Owners Hesitate — Answered
“I don’t have time to learn about AI right now.”
You don’t have to. This isn’t a training session — it’s a 20-minute conversation about your business, not our technology. We do the translating.
“Every vendor says AI will help. How is this different?”
We don’t start with a use case — we start with your numbers. If the math doesn’t support a clear payoff in a specific department, we’ll tell you that too, not just the departments where we think we can sell something. That’s the same discipline behind engagements like the $214K/year recovered for a 25-store retailer — the department, and the number, came first.
“This is probably just a sales call in disguise.”
You get the written breakdown either way — which department to prioritize and what it’s worth — whether or not you ever hire us. No contract, no pressure.
“My team already rolled out Copilot / ChatGPT. Isn’t that enough?”
Licensing a tool isn’t the same as knowing where it pays off. Most "AI adoption" stops at a login screen. This assessment tells you which department the investment should actually target.
21 Years of Delivery Before We Ever Said “AI”
Sphere has been building software, data, and engineering solutions since long before "AI" was a category — this isn’t a pivot.
Across financial services, healthcare, insurance, legal, retail, and government — we’ve seen where AI pays off and where it doesn’t.
32 verified Clutch reviews. Clients consistently cite communication, delivery, and technical depth — not just AI hype.
Stop Guessing Which Department Needs AI First
20 minutes. No jargon. A straight answer about which department is a money maker, which is a money eater, and what that’s worth to your margin.
Get My Free Assessment →Quick Answers
What is an AI readiness assessment?
A short, structured review of where your business currently loses the most money and time to manual or inefficient work — and whether AI can realistically close that gap. It is not a technology audit. It is a business diagnostic that happens to involve AI.
How long does the assessment take?
The initial call is about 20 minutes. We ask about your departments, headcount, and where money and time currently leak — not about your tech stack. You get a written breakdown within a few business days.
Do I need to understand AI to do this?
No. This assessment is built for business owners and operators, not technical teams. You won’t be asked about models, infrastructure, or architecture — only about your business.
What do I get at the end?
A ranked list of which departments in your business have the most to gain from AI, an estimate of the cost or revenue impact per department, and a recommended starting point — with no obligation to move forward with Sphere.