AI Opportunity & Readiness Assessment
Find where AI actually pays off in your business
In four weeks, we find the AI use cases worth doing in your business, tell you honestly whether your data is ready, and map the path to production.
You pay $0
No fee, no procurement cycle
AWS funds it
Comparable engagements run $40k-$120k
You keep everything
All four documents, no strings
Funded through AWS partner programmes for qualifying businesses — see the FAQ for how it works
Where AI creates value
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Knowledge & document search
Your team asks in plain language and gets answers pulled straight from your manuals, contracts, SOPs and records.
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Forecasting & optimization
Forecast demand, inventory and asset needs from your own data instead of guesswork.
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Process & document automation
High-volume, repetitive work handled by AI: invoices, orders, claims and back-office tasks.
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Monitoring & decision support
AI flags the exceptions and patterns that matter and puts the full picture in one place, so your team decides faster.
Why start with an assessment
Most AI initiatives don't fail on the model — they fail on foundations nobody checked first.
- >80% of AI projects fail — roughly twice the failure rate of non-AI IT projects RAND Corporation, 2024
- 48% of AI projects make it out of prototype and into production Gartner, 2024
- 74% of companies struggle to achieve and scale value from AI investments BCG, 2024
What the other 20% looks like — one of ours, in production
Full case study- 61% lower cost per scan than the vendor we replaced
- 0.73s average recognition, down from roughly five seconds
- 2-3M scans processed per day in production
- 100% of the intellectual property assigned to the client
Measured in a like-for-like production comparison at live traffic volume.
Exactly what you walk away with
Not a maturity score and a slide about the future of AI. Four documents you can act on, and they are yours to keep whatever you decide to do next.
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01 / USE CASES8-12 pages
Prioritised use-case register
Three to five candidate use cases, each scored for business value and technical feasibility, including the ones we recommend you do not pursue and why.
PDF + XLSX -
02 / READINESS14-18 pages
Readiness scorecard and gap register
Your data, platform, security and operating model rated against the AWS Cloud Adoption Framework for AI, with every gap listed by severity and owner.
PDF -
03 / ARCHITECTURE10-14 pages
Target architecture and business case
A reference architecture on AWS, sized and costed, with a three-year TCO model and the AWS funding programmes you qualify for.
PDF + diagram -
04 / ROADMAP1 page + deck
Sequenced roadmap and board readout
A twelve-month delivery sequence with dependencies and decision points, plus a one-page executive summary written for a board rather than for engineers.
PDF + PPTX
Four weeks, start to readout
About six hours of your team's time in total, concentrated in the first two weeks.
Discovery and prioritization
Goal
Understand your priorities, workflows and data, and agree which candidate use cases are worth scoring.
Your time ~3 hoursWhat we do
- Map your priorities, workflows and data
- Shortlist the candidate use cases
- Score them by value and feasibility
Readiness assessment
Goal
Establish honestly what your data, platform and operating model can carry today, and what they cannot.
Your time ~2 hoursWhat we do
- Assess data, technology and AI readiness
- Flag the gaps and risks honestly
- Cover security and governance where it matters
Architecture and ROI
Goal
Design what the first use case actually runs on, and what it costs against what it returns.
Your time ~1 hourWhat we do
- Design the target AWS architecture
- Build the business case and ROI
- Identify applicable AWS funding
Roadmap and readout
Goal
Hand over a sequenced twelve-month plan and walk your leadership through it.
Your time Readout onlyWhat we do
- Sequence the path to production
- Executive readout with recommendations
- Optional 2-4 week feasibility prototype
Whether this is worth your four weeks
Roughly six hours of your team's time in total, concentrated in the first two weeks.
A good fit if
- You have executive intent for AI but no agreed plan, and competing internal opinions about where to start.
- You are running AI pilots that have not reached production, and it is not clear why.
- An AI feature is live but the unit economics or a vendor dependency has become the problem.
- You need a costed, defensible case before a board or investment committee will release budget.
Not a fit if
- You already know the use case and want it built. Skip the assessment and talk to us about delivery instead.
- You are looking for licence discounts or procurement leverage rather than an engineering opinion.
- Nobody can commit around six hours across four weeks. The assessment needs your people in the room.
Not sure yet?
Score your AI readiness in two minutes
Before you book four weeks, get a first read on where you stand — the same four dimensions we assess in the full engagement: data, platform, use case, and ownership.
- 4 questions
- about 2 minutes
- see your result instantly
Regulated sectors get the regulated version
Same four weeks, same deliverables. The difference is that every gap we find comes mapped to the frameworks your auditors already use, so the readiness work lands straight in your existing compliance process.
Financial services
4 frameworks- Model governance, explainability and the human-in-the-loop controls a regulator will ask about.
- Gap register mapped to OSFI B-13 NIST AI RMF 1.0 ISO/IEC 42001:2024 SOC 2
Healthcare
4 frameworks- PHI handling, clinical-safety review and third-party AI risk, with a board-ready risk summary.
- Gap register mapped to HIPAA Security Rule HITRUST CSF NIST AI RMF 1.0 ISO/IEC 42001
Retail and commerce
4 frameworks- Personalisation, forecasting and automated decisioning where consent and peak-season cost both bite.
- Gap register mapped to PCI DSS 4.0 GDPR Art. 22 SOC 2 ISO/IEC 42001:2024
In manufacturing, insurance, energy, or the public sector? The same mapping works for your frameworks — tell us which ones apply.
Why Dedicatted
The only Generative AI and MSP partner in Canada
Top 2% of AWS partners worldwide — the team assessing your readiness is the same one that ships AI to production.
100+
AWS certifications across the team
50+
AI use cases shipped to production
Proven results
Questions, answered
Do we need to be using AWS already?
No. The assessment is about your business and your data. You don’t need to be an AWS customer to take part.
What is the catch if AWS sponsors it?
No catch. AWS supports these assessments so organizations find real, high-value AI opportunities. You work with Dedicatted the whole way through.
What if our data is not ready?
That’s exactly what we check. You get an honest readiness picture and a roadmap that accounts for it, so nothing surprises you later.
How much of our team time does it take?
A few working sessions across the four weeks, with your business and technology people.
Do we own the deliverables?
Yes. The report, roadmap and architecture are yours, and you’re under no obligation to build with us.
What if we are multi-cloud?
That’s fine. The architecture we recommend is AWS-based, but the opportunities and roadmap are yours to run anywhere.
Can you sign an NDA?
Yes, before we look at anything sensitive.
See where AI can create value in your business
Briefly outline your challenge. Our team responds within one business day with relevant experience and a first read on the technical approach.
Thanks, we have it.
Our team replies within one business day, with relevant experience and a first read on your problem.