Consulting / AI readiness assessment
Find out if you are ready for AI, before you spend on it.
A scoped assessment of where AI would pay off in your business and what has to be true first: the data, the systems, the people and the controls. You get a written report, including "not yet" when that is the honest answer. Want a quick read first? Take the free 4-minute check.
Astra Short on time? Ask about this page in plain words.
Sound familiar? Four problems we are usually called in to fix.
You do not know where AI fits
Use cases are opinions, not ranked options.
- Use cases ranked
- Autonomy per task
- A first step
Data and systems are an unknown
Nobody has checked what the AI would actually work with.
- Data review
- Systems review
- Gaps named
People and process will make or break it
Tools get bought; teams do not change how they work.
- People and process review
- Governance and risk
- Who owns what
Leadership wants a number
Without cost and effort, nothing gets approved.
- Cost and effort estimate
- Build versus buy
- Written report and roadmap
One week to a clear first step.
Let’s talkWhat the assessment looks at. What decides whether an AI project ships.
Use cases
Where AI would save time or money, ranked by value, effort and risk.
Data
Whether the data each use case needs exists, can be reached and is good enough.
Systems
How AI would connect to the tools you already run, and what that integration takes.
People and process
Who would use it, who would review its output, and what changes in their day.
Governance and risk
Approval checkpoints, audit trails and the decisions that must stay with people.
Build versus buy
Where an existing tool is enough, and where custom work earns its cost.
Autonomy per task
Which tasks suit a fixed workflow, which need a person to review, and which suit an agent.
Cost and effort
A realistic view of build and running costs, including model usage.
First step
The one use case to start with, and how to prove it works quickly.
Match the autonomy to the task. Part of every assessment: not every task needs an agent.
- L1WorkflowA fixed, auditable path.
- L2AssistantAI drafts. A person reviews.
- L3Supervised agentAI acts and flags exceptions.
- L4AutonomousRoutine, low-risk, monitored.
- Human-ledPeople decideAI supports the analysis.
Routine data entry and mapping
A fixed, auditable workflow is usually enough.
L1 WorkflowDrafting documents and replies
AI drafts. A person reviews and sends.
L2 AssistantEvidence-heavy review
Agents check every item and flag exceptions for people.
L3 Supervised agentJudgement and approvals
Stay with people. AI supports the analysis.
Human-led
Delivered work behind our advice. Our recommendations draw on systems we have built. These are delivery engagements, not consulting projects.
AI agent platform
Agents retrieve, reason and act across systems, with human approval before high-stakes actions.
~40% less manual effort AI · Document intelligenceAI document intelligence
Extraction and classification that sends only the exceptions to people.
>80% less manual review AI · InsuranceFull-stack AI platform for insurance
Fragmented policy, claims and correspondence data connected into one structured workflow.
~2.5x faster processingNot sure where AI will pay off in your business?
How the assessment runs. Four steps, ending in a report you can act on.
-
Intake
Understand the business, the goals and the work people want AI to help with.
Intake notes
- Business goals
- Candidate workflows
- Who needs to sign off
-
Discovery
Workflows, data and systems reviewed with the people who run them.
Discovery
- Workflows walked through
- Data sources checked
- Systems mapped
-
Analysis
Use cases ranked, gaps found and the first step chosen.
Analysis
- Use cases ranked
- Gaps identified
- Risks and controls
-
Report
A written assessment with a roadmap, or a direct move into a pilot.
Report
- Readiness by area
- First use case
- Roadmap and cost view
Why teams use us for an AI readiness assessment. Advice from people who ship AI.
Honest, not sales-driven
We will say "do not build this yet" when that is the accurate read.
Same team, start to finish
The team that assesses readiness is the team that would build it.
Grounded in delivered work
Advice informed by AI and Web3 systems we have shipped, not theory.
Regulation-aware
Compliance considerations are part of the advice, not a separate afterthought.
AI and Web3 under one roof
One team that can compare both, rather than favouring the one it sells.
Clear written output
Every engagement ends with a recommendation you can act on or hand over.
Engagement models. Pick the shape that fits where you are.
A written report
The assessment and roadmap, with no build obligation.
Same team throughout
The first use case moves straight into a proof of concept.
Recurring input
Regular review as you roll out more AI across the business.
What our clients say.
AI platform for an insurance broker
“Avinya Labs built our full-stack AI solution … Their expertise accelerated our launch and significantly reduced execution risk.”
Guides on this topic. Plain answers to the questions buyers ask first.
Enterprise AI Deployment: Why Projects Stall in Pilot
The eight causes we see most, and a roadmap that gets AI live.
Read the guide → GuideOperational AI Systems: A 2026 Guide for Enterprises
How AI moves from pilots into the daily operations of a business.
Read the guide → GuideAI Agent Development Cost: What Drives the Price (2026)
What drives the price of an AI agent: scope, complexity, iterations and retainer.
Read the guide →AI readiness assessment FAQs.
What is an AI readiness assessment?
A structured review of whether a business is ready to use AI well: which use cases are worth it, whether the data and systems can support them, who will use and review the output, and what controls are needed.
What do we get at the end?
A written report: readiness by area, use cases ranked by value and effort, the gaps to close, the first use case to start with, and a rough cost and effort view.
What if we are not ready?
Then the report says so, with the reasons and what to fix first. That is often the most useful outcome.
Do we have to build with you afterwards?
No. The report is yours to take to your own team or another partner.
How long does an assessment take?
It depends on how many workflows and systems are in scope. We agree the scope and timeline before we start.
What does an AI readiness assessment measure?
Data quality, the processes AI would change, team skills and governance. An AI readiness assessment ends with a ranked plan, and governance is scored against the NIST AI Risk Management Framework.