A shortlist worth funding
The few opportunities where AI would move a number that matters in your business, ranked by value against the effort to get there.
365 Cloud Advisors
AI Strategy & Readiness
Find the AI opportunities worth pursuing.
We help small and mid-sized businesses identify where AI can create measurable value, what foundations must change first, and which ideas should be left on the bunny hill.
This is for leaders who are being asked what their AI plan is, and who want an answer grounded in their own operations rather than a vendor roadmap.
Most AI projects fail on the foundations, not the idea.
The idea is rarely the problem. Somebody can always name a process that looks ripe for automation. What sinks the project is everything underneath it: data nobody trusts, systems that cannot be reached cleanly, a process that only works because one person remembers the exceptions.
So the work starts with your operations rather than a product demo. Which decisions are slow? Which questions take three systems and an afternoon to answer? Where does the same investigation happen every week? Those are the places AI pays, and they are specific to you.
The output is a short list you can act on, in priority order, with the honest cost of each item attached — including the ones we would tell you not to do yet.
AI opportunity discovery and prioritization
AI readiness and maturity assessment
Business process analysis
Technology and vendor selection
ROI, feasibility and risk analysis
Executive AI roadmap
What you get
Deliverables, not a deck of slides.
A prioritised opportunity list
Every candidate use case scored on business value, feasibility and what it depends on — so the sequence is defensible, not just a wish list.
An honest readiness picture
Where your data, systems, processes and skills actually stand today, including the gaps that would sink a project if nobody named them.
The cost of each option
What each opportunity needs in licensing, engineering and ongoing running cost, so the business case survives contact with finance.
A phased roadmap
What to do in the next quarter, the next year, and what to deliberately defer — with the trigger that would move something forward.
A do-not-do list
The ideas that sound good and are not worth it yet, and the specific reason why. This is usually the most valuable page.
Something you can present
A short executive summary written to be shown to a board or an owner, not to be translated by you first.
How it works
Where this sits in the route.
Step 1
Assess
Understand your business, systems, processes and AI readiness.
Step 2
Modernize
Strengthen ERP platforms, integrations and data foundations.
Step 3
Automate
Deploy AI agents where they deliver measurable value.
Step 4
Govern
Implement responsible AI with security, permissions and human oversight.
Common questions
The things people actually ask.
Do we need a data platform before we can do anything with AI?
Usually not. Plenty of worthwhile first projects run on the systems you already have. A data platform becomes necessary when the questions you want answered span several systems at once — and that is a conclusion the assessment should reach on evidence, not an assumption at the start.
What if the honest answer is that we are not ready?
Then that is the answer, and it is worth knowing before you spend a budget rather than after. Readiness gaps are usually specific and fixable, and knowing which three matter is more useful than a roadmap that assumes they do not exist.
How is this different from a vendor’s AI assessment?
A vendor assessment ends in a recommendation to buy that vendor’s product. This one can end in the recommendation to buy nothing yet, and frequently does.
Related reading
Written on this, at length.
AI + Business Central
How to Use AI to Get More Value From Microsoft Dynamics 365 Business Central
Business Central already logs every turn you made. The interesting question is what it takes to make it tell you why you keep catching an edge in the same spot.
AI Strategy
Microsoft Copilot vs. Custom AI: Which Is Right for Your Business Central Environment?
The answer is usually both — for different runs. The mistake is buying one pair of skis and expecting them to handle the whole mountain.
Data Architecture
Fabric, OneLake, Lakehouses and Data Lakes: What Do They Actually Have to Do With AI?
Everyone nods when somebody says “we should put all our data in the lake.” Almost nobody asks which lake, or what is already floating in it.
Start here
Not sure this is the right run for you?
The Trailhead Assessment is a short set of questions about your systems, data and processes. It ends with a practical map of what to modernize, what to automate, and what to leave alone.