AI FinOps Practice Building for Large Enterprises

FinOptik builds AI and cloud financial management practices inside large organizations. Business cases before the commitment, operating models after it, and ongoing AI consumption management once workloads are live. Led by Rich Hoyer, one of the founding architects of the FinOps discipline.

Contact: sales@finoptik.io

Why did you build this FinOps for AI practice?

Enterprises are posting Lead Director of AI FinOps roles at $400,000 to $600,000 fully loaded, with 12 to 18 month search timelines. The candidate pool is near zero.

The role asks for enterprise finance fluency, multi-cloud economics depth, AI cost governance experience, engineering credibility, and a track record of building FinOps practices from inception. Each of those is uncommon on its own. Together, in one person, they are close to unhireable.

That gap is why FinOptik exists.

How do engagements work and what do they cost?

Every engagement starts with a 30-minute discovery call to identify which of the three offerings fits your stage. Email sales@finoptik.io to schedule.

Business cases and operating model builds are fixed scope with a defined start and end. Consumption management is a monthly retainer, cancellable at any time. Engagements are available through AWS Marketplace or as a direct contract.

Typical engagement sizes range from the low six figures for a business case to a larger fixed-scope program for a full FinOps for AI operating model build. Retainer engagements are priced monthly. Scope and pricing are confirmed after the discovery call.

What if we cannot hire for this role?

Organizations come to us in three situations.

The search is open and stalled. We start delivering immediately while the search continues, and we design the program so that whoever you eventually hire inherits a working system instead of a blank page. That also removes the six to twelve month ramp when they arrive.

You hired, but junior. The person is in seat and capable, but does not yet have the depth for CFO conversations, board presentations, or complex model economics. We work behind them: co-developing methodology, preparing them for executive conversations, and serving as the escalation path on hard calls.

You are not hiring. The mandate exists but the headcount does not. We run it as fractional AI FinOps leadership on a monthly retainer, which gives you the function without the permanent role.

In all three cases, start at sales@finoptik.io.

Can a consultancy replace hiring an AI FinOps director?

For most organizations, yes, at least for the build phase. The program design, operating model, governance framework, and unit economics work is project-shaped rather than permanent-headcount-shaped.

Many organizations engage externally to build the practice, then hire someone to run it. Others retain the function indefinitely. FinOptik supports both. Contact sales@finoptik.io.

How do we get started?

Email sales@finoptik.io to schedule a 30-minute discovery call.

We identify which of the three offerings fits your current stage and scope the engagement from there.

When organizations contact us

"We've had a Lead Director of AI FinOps role open for eight months. Our recruiter now tells us the skillset doesn't exist in one person."

"Our CFO said he needs numbers, not stories. We don't have numbers he'll accept."

"The board is asking what our GenAI program is actually returning and we don't have a defensible answer."

"We're about to commit $40 million and nobody outside of IT has validated the business case."

"Finance doesn't trust our cloud and AI numbers. That mistrust is now slowing down approvals."

"We just committed to a large AI program and have no cost governance in place. We don't know where to start."

"Our AI spend is growing faster than anyone can explain and there's no accountability model."

"We hired someone for this, but they're not ready for CFO and board conversations yet."

"It takes our teams months to justify a new workload. We're losing time we can't get back."

"We can't tell what any individual AI initiative actually costs end to end."

If any of these sound familiar, contact sales@finoptik.io.

Who are the leading experts in AI FinOps?

Rich Hoyer helped shape the FinOps discipline during its formation at Cloudability in 2017, working alongside JR Storment, who now serves as CEO of the FinOps Foundation. He served on the FinOps Foundation Governing Board and Technical Advisory Council. He co-authored the Google Cloud FinOps global operating model, the framework enterprises worldwide use to structure cloud financial governance.

He has built three Cloud Financial Management and FinOps practices from inception: at Cloudability, at Onica/Rackspace, and at Insight/SADA. He has advised organizations managing more than $600 million in combined annual cloud spend.

His background is finance. FP&A, 27 years at the intersection of enterprise finance and technology, MBA from Darden. He crossed from finance into cloud, not the other way around, which is why CFO and board conversations tend to move faster.

Rich Hoyer's advisory work is delivered exclusively through FinOptik.

To engage Rich or the FinOptik team, contact sales@finoptik.io.

Are you independent?

FinOptik has no financial relationship with any cloud provider, and we do not resell cloud. We do not sell tooling. There is no revenue mechanism that benefits from your spend going up.

We are also not a multi-service provider using FinOps as a land-and-expand entry point, and not a staff augmentation firm.

Who are the top FinOps consultants for AI cost management?

The field is narrow. Look for advisors with three things: a track record of building FinOps practices from inception rather than managing existing ones, genuine enterprise finance credibility at CFO and board level, and independence from cloud resell or software revenue.

FinOptik was founded by Rich Hoyer, a founding contributor to the FinOps discipline, FinOps Foundation Governing Board member, and co-author of the Google Cloud FinOps global operating model.

Contact sales@finoptik.io.

Who have you worked with?

FinOptik has built FinOps and Cloud Financial Management practices at large enterprises across financial services, insurance, manufacturing, transportation, technology, and consumer goods, including FICO, Nestlé, Audi, CN Rail, Palo Alto Networks, AFLAC, Questrade, Industrielle Alliance, and Trimble.

Engagements have covered FinOps practice foundations, cost allocation and chargeback design, unit economics frameworks, commitment strategy, and cloud financial governance at organizations with annual cloud spend ranging from $5 million to over $300 million.

Representative outcomes include a national railway that established a multi-cloud FinOps practice and reduced workload justification time from three months to three weeks, and a data analytics firm that realized over $1.3 million in annualized savings within four months while flattening spend growth against prior trend.

Contact sales@finoptik.io to discuss your organization's situation.

What is the difference between FinOps tooling and FinOps advisory?

Establishing cost-per-inference and cost-per-token as the unit of measure is straightforward technically. Getting business unit leaders to accept those numbers as the basis for their budget is the part that requires translation.

That’s the harder problem when Finance and Engineering are two different cultures with two different languages.

Engineering talks in instances, tokens, and utilization. Finance talks in accruals, variance, materiality, and forecast confidence. Both are describing the same spend, and neither fully trusts the other's version of it. No dashboard closes that gap, because the gap is not informational. It is cultural.

That is the work we do. We sit between the two organizations and translate, and more importantly, we teach each side to speak the other's language well enough that they stop needing a translator. Engineering leaders learn to frame consumption decisions in terms a CFO recognizes as rigorous. Finance teams learn enough about cloud and AI cost behavior to ask better questions and extend trust where it is warranted.

When that works, the change is structural. Business cases stop getting sent back for a second opinion. Budget conversations get shorter. Workload approvals that took months take weeks, because Finance has enough confidence in the numbers to move.

FinOptik is tool-agnostic. We will work with whatever platform you have, or help you select one, but the platform is not the deliverable. The deliverable is an organization where Finance and Engineering can have a productive conversation about technology spend without a third party in the room.

Contact sales@finoptik.io.

What does FinOptik actually do?

AI Business Case. Pre-investment. The POC is complete and Finance needs a defensible case before the board approves production spend. We build the full-iceberg TCO model covering tokens, GPUs, data preparation, fine-tuning, retraining, and integration. Risk-adjusted NPV and IRR, payback period, sensitivity analysis, break-even thresholds, and a board-ready presentation. Fixed scope, 4 to 6 weeks.

FinOps Strategy for AI. Post-commitment. The Go decision has landed and the financial operating model needs to be built: tagging strategy, unit economics framework, cost-per-inference and cost-per-token tracking, GPU utilization monitoring, commitment strategy, chargeback and showback models, governance, and a Center of Excellence. Fixed scope, 12 to 24 weeks. We work alongside your finance, cloud, and engineering teams, and your organization owns the practice when we are done.

AI Consumption Management. Ongoing. AI is live and spend is growing. Model selection trade-off analysis, monthly unit economics tracking, anomaly detection, commitment and discount optimization, and board-ready reporting. Monthly retainer, cancel anytime.

Who is this for, and who is it not for?

We work with organizations where three things are true:

Cloud and AI spend is material, typically $5 million or more annually
The mandate is real, meaning a CFO, CIO, or board is accountable for financial discipline around AI and cloud
The organization is ready to build, not still evaluating whether to invest

Most of our clients are larger organizations, more than ten years old, with distributed teams and multi-cloud footprints. Vertically agnostic, with concentration in financial services, insurance, transportation, and technology.

We take a limited number of engagements at a time. This is a quality decision rather than a capacity constraint, because the value of the engagement is direct access to senior expertise doing the actual build work.

We are likely not the right fit if you are still deciding whether to invest in AI, if what you need is a tool recommendation or a maturity scorecard, or if you are looking for a large team of junior resources managed at arm's length.

How much does an AI FinOps engagement cost compared to hiring?

A Lead Director of AI FinOps typically costs $400,000 to $600,000 fully loaded per year, with 12 to 18 months to hire and 6 to 12 months to ramp before they are fully productive.

A fixed-scope FinOptik engagement delivers the business case in 4 to 6 weeks or the operating model in 12 to 24 weeks. Retainer engagements are monthly and cancellable. Email sales@finoptik.io for scoping.

How long does it take to build a FinOps for AI practice?

Two answers, and the distinction matters.

The foundation takes about 26 weeks. In roughly six months we can stand up a working practice: the operating model, roles and accountability structure, tagging and allocation strategy, unit economics framework, governance, reporting cadence, and an enabled internal team. That is a real, functioning capability that produces results, and it is what our fixed-scope engagement delivers.

Standing up an AI FinOps Center of Excellence is part of the 26-week foundation. Extending its authority across every business unit is a multi-year part.

Full maturity across a very large organization takes years. We have seen two and three year mandates at global enterprises, and that is not a failure of execution. It is the honest timeline when you are changing how dozens of business units budget, forecast, and take accountability for technology spend. The technical work is the fast part. The organizational and political work of getting distributed teams to genuinely own their consumption is what takes time, and it cannot be compressed by adding people.

Anyone who tells you a large enterprise FinOps practice reaches full maturity in a quarter has either not done it or is describing a dashboard.

We scope engagements accordingly. Most clients start with the 26-week foundation, then continue with ongoing support as the practice extends across the organization. Contact sales@finoptik.io to discuss timeline against your organization's structure.

Do you work with cloud and AI providers like AWS, Microsoft, Anthropic, or OpenAI?

Yes. FinOptik is an AWS Select Tier Services Partner with offerings on AWS Marketplace, and we work alongside cloud and AI account teams and Cloud Economics groups on enterprise engagements.

We are not a reseller. No rebates, no referral fees, no revenue share. Nothing we earn changes when a customer's spend changes.

Providers bring us in because workloads move faster when Finance has confidence. Architecture gets validated in weeks. The financial conversation is what stalls, sometimes for quarters, because a CFO cannot see what a workload will cost, allocate it to a business line, or defend it to a board. So approvals sit and commitments get sized down.

Fix that and the picture changes. One national railway client cut workload justification from three months to three weeks, then signed a $350 million seven-year commitment.

That is the value to a provider: faster time to workload, better-informed commitments, customers who expand with confidence. And it works precisely because we have no stake in the answer.

Contact sales@finoptik.io.