75% of companies are already using generative AI, up from 55% the year before. Most AI pilots that fail do so because operations, data, security, or team readiness wasn't evaluated up front. The problem is almost always preparation, not technology. IDC / Microsoft, 2024 Business Opportunity of AI

What we evaluate

Operations and workflows.Mapping your processes to identify where AI delivers measurable time and cost savings. Document-heavy workflows, repetitive classification tasks, multi-step approvals. The hours your team spends today get quantified so the ROI projection is based on real numbers.
Data readiness.Auditing your data sources for structure, accessibility, quality, and duplication. Identifying whether your documents and databases are in formats AI can work with or whether cleanup is needed first. Flagging data silos that would block results.
Technology infrastructure.Evaluating your current stack to determine what integrates with modern AI tooling and where gaps exist. Cloud providers, identity systems, API capabilities, and whether your environment supports private model deployments if needed.
Team capability.Assessing AI fluency across leadership, management, and frontline staff. Identifying where training gaps would slow adoption and where existing expertise can be built on.
Security and compliance posture.Looking for shadow AI usage, unsanctioned data flowing to public LLMs, and gaps in your data loss prevention controls. Mapping where your existing compliance controls touch AI usage.
Competitive position.Researching how your competitors and industry peers are deploying AI. Identifying where you can move faster and where the market has already set expectations your customers will bring to you.

What you get

Prioritized opportunity map.Every AI use case ranked by business impact, technical feasibility, and time to value. Which projects to fund first, which to defer, and why.
Quick-win identification.Any quick-win opportunities we find using existing data and current tools.
Risk assessment.Security, compliance, and organizational risks tied to your planned AI use. Each risk rated by likelihood and impact with a recommended path to address it.
Next-steps roadmap.A phased plan with budget ranges, resource requirements, and realistic timelines. Distinguishes between what you can handle internally and where you need outside help.

52% of organizations cite lack of skilled workers as the top barrier to scaling AI. A readiness assessment tells you exactly where that gap sits in your business. IDC / Microsoft, 2023 Business Opportunity of AI

How it works

Discovery call.An opening conversation to better understand your business, your goals, and your current stack. This sets the direction for the assessment so the rest of the work measures against the right targets.
Working session.A session with stakeholders across operations, IT, finance, and leadership. Walking through current workflows, data systems, security posture, and team structure. This is where the raw material for every deliverable gets collected.
Analysis and report.Synthesizing the findings, building the opportunity map, and developing the prioritized roadmap. Every recommendation gets pressure-tested against your stated budget and timeline.
Deliverable presentation.Presenting findings, the opportunity map, risk assessment, and roadmap in a working session with your leadership. This is a conversation, not a document drop. Priorities get refined on the spot so you leave with a plan you can act on.

Who this is for

Leaders who want clarity before committing budget. Companies with stalled or failed AI pilots. Businesses that want AI baked into the foundation, not bolted on later.

AI readiness assessment.

What we evaluate

What you get

How it works

Who this is for

Start with clarity, not guesswork