Why Revenue Operations is The Key to Delivering ROI from AI
I sit in board meetings every week. Lately the conversation is always the same.
The CEO looks at the slide deck. The board members lean forward. Someone asks the inevitable question.
“What is our AI strategy?”
The room gets quiet. The CRO starts talking about a new tool that writes emails. The CMO talks about generating blog posts. The CTO talks about vector databases.
They are all missing the point.
They are treating AI like a magic wand. They think they can sprinkle it over their business and money will fall out. They buy the licenses. They roll out the tools. They wait for the efficiency gains.
Six months later I look at the P&L. Nothing has changed. The sales cycle is the same length. The conversion rates are flat. The customer acquisition cost is actually higher because of the software fees.
Why does this happen?
It happens because AI is not a strategy. AI is an engine. And an engine cannot run without a chassis. It cannot steer without a wheel. It cannot move without a transmission.
Revenue Operations is that transmission.
I started as an engineer. I know that code is literal. I started as a banker. I know that investment requires return. Now I build companies. I know that you cannot simply plug a Ferrari engine into a go-kart and expect to win the race. You will just tear the go-kart apart.
RevOps is the discipline of building the vehicle. It is the only way to harness the raw power of AI and translate it into actual business value. If you do not have a strong RevOps foundation you will not get ROI from AI. You will just get chaos at the speed of light.
Here is why.
The Problem: Garbage at Light Speed
There is an old saying in data engineering. Garbage in, garbage out.
If you put bad data into a system you get bad results out of it.
In the old days this was manageable. If a sales rep looked at a bad data field in Salesforce they would ignore it. They would use their human judgment. They would see that the “Company Size” field said “1” but the website looked like a Fortune 500 company. They would adapt.
AI does not have judgment. AI has confidence.
If you feed an AI model dirty data it will confidently execute the wrong action. It will write a personalized email to a CEO referencing the wrong industry. It will forecast a deal to close next month based on a stale activity log. It will route a enterprise lead to an SMB rep because the territory field was blank.
Without RevOps your data is messy. You have duplicates. You have missing fields. You have unstructured notes.
If you apply AI to this mess you do not get efficiency. You get automated embarrassment. You scale your mistakes. Instead of sending one bad email you send ten thousand.
RevOps is the custodian of the data. The RevOps leader builds the data dictionary. They enforce the validation rules. They ensure the “Single Source of Truth” is actually true.
Before you buy an AI writing assistant you need a RevOps architect to clean the database it reads from. The ROI comes from the accuracy of the output. The accuracy of the output depends entirely on the cleanliness of the input.
Only RevOps can guarantee that input.
Reason 1: Context is the Currency of AI
Generative AI is a prediction machine. It predicts the next word in a sentence based on the context you give it.
The keyword is context.
Most companies have their context trapped in silos.
The marketing context is in HubSpot. The sales context is in email threads and Zoom calls. The product context is in Jira tickets. The finance context is in NetSuite.
If you ask an AI to “Draft a renewal email for this client” and it only has access to the CRM it will write a generic email. It will sound like a robot. The client will delete it. ROI = zero. Maybe negative.
But imagine a different scenario.
Imagine a RevOps team has built a unified data layer. They have connected the systems.
Now you ask the AI to draft that email.
The AI sees that the client just logged a support ticket in Zendesk yesterday about a critical bug. It sees that usage dropped by 10 percent last month. It sees that the champion just left the company and a new contact was added to the account.
The AI writes: “I noticed you’re dealing with that bug on the login screen. I’ve escalated it to our engineering lead. Also I saw usage dipped slightly. Can we discuss how the new team structure is affecting your workflow?”
That email gets a response. That email saves a customer. That is ROI.
You cannot buy this context off the shelf. You have to build the pipes that carry it.
RevOps builds the pipes.
The RevOps leader is the one who integrates the tech stack. They ensure the support ticket data flows into the Opportunity object. They ensure the LinkedIn scraper feeds the contact record.
AI is the brain. But RevOps is the nervous system that feeds the brain information.
Without the nervous system the brain is hallucinating in the dark.
Reason 2: Process Standardization Before Automation
I have a rule for my portfolio companies. Never automate a process you have not done manually five times perfectly.
AI is the ultimate automation tool. But it acts as a multiplier.
If you multiply zero by a million you still get zero.
If you have a bad sales process and you add AI you just have a bad process happening faster.
Most sales teams do not have a standard process. They have “tribal knowledge.” Rep A does it one way. Rep B does it another way.
If you train an AI on your historical data it will learn this confusion. It will learn that sometimes we offer a discount on the first call and sometimes we wait. It will be inconsistent.
RevOps is the discipline of process design.
Before you deploy AI you must map the journey. You must define the “Happy Path.”
What are the exact entry criteria for the Negotiation stage? What is the specific playbook for a competitive loss? What is the precise messaging for a C-level intro?
The RevOps leader acts as the process engineer. They strip away the waste. They define the standard.
Once the standard is defined AI can enforce it.
AI can score calls against the standard methodology. AI can check if the rep asked the budget question. AI can suggest the next step based on the playbook.
But the playbook must exist first.
Companies that skip this step fail. They buy a “Sales Coaching AI.” They turn it on. The AI gives random advice because it does not know what “good” looks like for that specific company. The reps ignore it. The CFO cancels the contract.
ROI requires a standard. RevOps sets the standard.
Reason 3: The Human-in-the-Loop Feedback Architecture
AI is not set-and-forget.
Current AI models are impressive but they hallucinate. They make up facts. They get tone wrong.
If you let AI loose on your customers without supervision you are taking a massive reputational risk.
You need a “Human-in-the-Loop” workflow. Right now. Here’s how.