AI Advisory
Make AI pay off on the P&L.
AI is everywhere now. The hard part in 2026 is proving the return. We help leadership teams pick the use cases that matter, build the governance, and measure the result with a CFO's discipline, so AI becomes a number you can point to instead of a line of spend.
The Problem
Everyone's using AI.
Almost no one has a plan.
Around two-thirds of small businesses report using AI in some capacity. But there is a wide gap between adoption and impact, and it is where most companies are stuck right now.
The gap between using ChatGPT for email drafts and building AI into core operations is where most companies stall. Experimentation feels productive, but without a defined business case and success metrics, it stays experimentation. Tools get purchased. Subscriptions renew. Nothing changes at the P&L level.
Without strategic direction, AI initiatives become scattered pilots that never scale. Individual teams try different tools for different problems. There is no shared governance, no measurement framework, and no one connecting the dots between what is being tried and what the business actually needs.
The result is predictable: budget spent on tools nobody fully uses, employees reverting to old workflows within weeks, and leadership unable to answer the board's questions about AI readiness with anything more specific than "we're exploring it."
What most leadership teams actually need is not a technology consultant who arrives with product demos. They need an operator who understands both the technology landscape and the business context, someone who can connect AI capability to specific bottlenecks, build the financial case, and make it stick.
Our Approach
Four phases. One objective:
AI that moves the needle.
Every engagement follows a structured progression from assessment to implementation. Each phase has defined deliverables, clear timelines, and measurable outcomes. We do not move forward until the current phase justifies the next one.
AI Readiness Assessment
We evaluate where you stand today: data infrastructure quality, current tool usage, team capabilities, process documentation, and existing bottlenecks. We identify quick wins that can demonstrate value in weeks, not months, and flag areas where AI is not the right answer.
- Current-state operational audit
- Data readiness evaluation
- Team capability assessment
- Quick-win opportunity map
Strategy & Prioritization
Not every process benefits from AI. We rank opportunities by expected ROI, implementation complexity, and risk profile. Each priority gets a business case with baseline metrics, projected impact, and resource requirements. The output is a roadmap your leadership team can actually execute against.
- Prioritized use-case ranking
- Business case per initiative
- Phased implementation roadmap
- Budget and resource plan
Governance & Policy
Most businesses using AI have no formal policy governing how it is used. We build one, covering data privacy, quality controls on AI-generated output, vendor evaluation criteria, acceptable use boundaries, and risk management protocols. Governance is how you scale AI without creating liability. It does more than tick a compliance box.
- AI usage and acceptable-use policy
- Data privacy framework
- Vendor evaluation criteria
- Risk management protocols
Implementation Support
We stay through execution. That means vendor selection based on your specific requirements, pilot programs with defined KPIs, change management to ensure adoption, team training that builds lasting capability, and a measurement framework so you know exactly what is working and what is not.
- Vendor selection and contracting
- Pilot program with KPI tracking
- Change management and training
- Measurement and iteration cadence
What Makes Us Different
Operator-led AI advisory.
Not a tech consultancy.
Most AI advisory firms lead with the technology. We lead with the business problem. That distinction shapes everything about how we work.
Operators first, not technologists
We have sat in the CFO seat, managed the P&L, and reported to boards. Our AI recommendations are filtered through operational reality, not theoretical capability. We understand what it takes to get a team to actually adopt new workflows, because we have been the ones responsible for making it happen.
ROI, not novelty
Every recommendation ties back to measurable business impact. We do not propose AI initiatives because the technology is interesting. We propose them because the financial case is clear: this process costs you X today, and with this approach, it will cost Y. If the math does not work, we say so.
Internal capability, not dependency
The goal is a team that can evaluate, implement, and manage AI without us. We build the governance framework, train your people, document the playbooks, and create a measurement cadence your team owns. Our success is measured by how quickly you do not need us anymore.
Governance from day one
Too many businesses treat AI governance as something to figure out later, after adoption is underway. We build it in from the start, acceptable use policies, data handling protocols, quality controls, and risk frameworks. Done right, governance lets you scale responsibly without slowing the business down.
Common Use Cases
Where AI delivers
measurable results.
These are the areas where we most frequently see clear ROI for small and mid-market businesses. Every engagement starts with identifying which of these, or others specific to your operations, represent the highest-value opportunity.
Financial reporting automation
Reduce close timelines, automate reconciliations, and generate board-ready reports with less manual effort and fewer errors.
Document processing and classification
Extract, categorize, and route information from invoices, contracts, permits, and compliance documents at scale.
Customer service optimization
Triage inquiries, surface relevant information to agents, and reduce response times without sacrificing service quality.
Demand forecasting and inventory
Improve forecast accuracy, reduce carrying costs, and align procurement with actual demand patterns using historical and market data.
Process mining and efficiency
Identify operational bottlenecks, quantify waste, and surface improvement opportunities that manual analysis would miss.
Board and investor reporting
Automate data aggregation, enhance narrative quality, and deliver more insightful reporting packages to sponsors, boards, and lenders.
Ready to move beyond
experimentation?
Most engagements start with a single conversation. Tell us where you are with AI and we will be direct about whether we can help.