How COOs Can Build an AI Operating Model That Actually Drives Revenue

By Maria Geokezas, Chief Working Officer at Heinz Advertising

Over the past 18 months, each income chief has felt the identical pressure: AI is not elective, however most organizations nonetheless wrestle to maneuver past pilots and prototypes. As COOs, we sit on the intersection of technique, execution, and operational scale which implies we’re those who decide whether or not AI turns into a real income driver or stays a scattered set of experiments.

The true differentiator for the subsequent era of B2B firms gained’t be who adopted AI first.  Will probably be who constructed a repeatable, scalable AI working mannequin that embeds intelligence into the day by day rhythms of selling, gross sales, and buyer success.

Under, I define how COOs can plan and operationalize AI so it turns into an engine of income effectiveness, not only a assortment of instruments.

What Is an AI Working Mannequin — and Why It Issues Now

Once we discuss an “AI working mannequin,” we’re speaking about one thing larger than instruments. It’s the mixture of folks, processes, expertise, governance, and tradition that ensures AI is utilized constantly and reliably throughout the income engine.

And the urgency is actual:

• 61% of organizations say they’re already restructuring or evolving their knowledge and analytics working mannequin due to AI’s affect.
• Ann Handley captures the spirit of the shift: “AI is a device … a robotic perched on our shoulder, not the creator on the keyboard.”

The idea of people augmented by AI inside a system designed for velocity and scale sits on the coronary heart of a contemporary income working mannequin.

Why AI Pilots Stall 

Most pilots don’t fail as a result of the expertise doesn’t work. They fail as a result of the group isn’t ready to operationalize it.

Gartner predicts that over 40% of agentic AI projects will be scrapped by 2027 because of unclear enterprise worth

Forrester highlights one thing related in RevOps organizations: Many groups deploy AI instruments however lack the mature operating model wanted to scale them throughout course of, knowledge flows, and decision-making.

In different phrases, AI instruments aren’t the bottleneck — working fashions are. That is exactly the place COOs add probably the most worth.

The Constructing Blocks of a Scalable AI Working Mannequin

1. Imaginative and prescient & Worth Definition

Begin with a transparent articulation of the enterprise outcomes AI helps:

• Quicker income cycles
• Larger high quality pipeline
• Higher forecasting
• Decrease acquisition prices
• Stronger buyer enlargement

Gartner recommends that AI strategy move beyond tool adoption towards a portfolio of AI initiatives built-in straight with enterprise working fashions.

Questions COOs ought to ask:

• Which income outcomes will AI affect?
• What is going to we measure?
• What use circumstances matter most to our enterprise mannequin?

2. Roles, Accountability & Staff Construction

AI creates new organizational wants:

• Who owns mannequin governance?
• Who interprets AI outputs into enterprise motion?
• The place does RevOps, Ops, and Information formalize cross-functional duties?

Forrester recommends introducing a “revenue process architect” to supervise interconnected GTM workflows.

COO NEXT Steps:

Outline possession earlier than scaling. Ambiguous accountability is the quickest option to kill AI adoption.

3. Course of & Workflow Design

AI shouldn’t sit on the aspect. It have to be built-in into workflows. Map out how work will get carried out after which determine the features and hand-offs by who/what performs every job (people, machine, or AI).

Inquiries to plan for:

• The place do people make selections?
• The place does AI generate perception or automate duties?
• How do workflows change when AI turns into the primary draft, not the ultimate supply?

4. Information & Know-how Infrastructure

“Rubbish in, rubbish out” turns into painfully true with AI. Gartner notes that many organizations are revamping their Data &Analytics mission and features particularly because of AI pressures.

Vital COO concerns:

• Do we’ve got unified income knowledge?
• Is our tech stack built-in sufficient for AI outputs to move into workflow instruments?
• Do we’ve got a ModelOps or governance course of?

5. Metrics, Governance & Steady Studying

You want metrics that present AI’s contribution to income outcomes — not simply exercise:

• AI-influenced alternative creation
• Cycle time discount
• Growth raise from predictive insights
• Forecast accuracy enhancements

Governance consists of:

• Bias checks
• Audit trails
• Utilization tips
• Mannequin efficiency evaluations (quarterly at minimal)

6. Tradition & Change Administration

This can be the largest one as a result of no working mannequin scales with out cultural adoption. Embedding AI into your working mannequin isn’t only a expertise rollout — it’s a folks and tradition transformation. Core values comparable to Clarity, Consistency, and Empathy underpin profitable AI integration.

• Readability — Groups should clearly perceive why the change is going on, what’s anticipated of them, and how success will probably be measured.
• Consistency — Change fatigue is actual. Leaders ought to keep up common communication and keep away from beginning contemporary each quarter. Because the weblog places it: “Don’t reboot your change efforts, as a substitute discover methods to iterate your processes.”
• Empathy — One of many greatest dangers in AI change is the notion of job displacement or lack of relevance. The weblog advises: “Know what your workforce fears … Communicate to their wants earlier than they do.”

COO motion steps:

• Construct a communication rhythm
• Normalize experimentation
• Spend money on upskilling and literacy
• Monitor adoption, not simply output

AI adoption fails in organizations the place tradition isn’t handled as a part of the working mannequin.

The Working Mannequin Mandate

In the long run, AI’s affect on B2B income groups is not going to be decided by who adopts probably the most instruments, however by who builds probably the most resilient, built-in AI working mannequin. For COOs, which means shifting the dialog from particular person use circumstances to the methods and constructions that enable AI to affect workflows, decision-making, and cross-functional alignment.

Once we deliberately design the working mannequin by redefining roles, redesigning workflows, strengthening knowledge foundations and establishing governance, AI turns into a repeatable and scalable functionality, not an remoted effort. If tradition and alter administration methods are a part of the method, AI is adopted whole-heartedly and turns into a everlasting piece of how work will get carried out.

Excited by studying extra in regards to the Heinz Advertising method to operationalizing AI for GTM groups?  We’d love to hear from you.

Picture courtesy of Freepik.