Advisory · AI Strategy & Opportunity Assessment
Where AI actually belongs in your business.
AI strategy consulting from a team that builds with AI every day. We assess your processes, data and systems and return an honest answer: what to build AI-native, what to add AI to later and what to leave alone.
Why this exists
Most AI strategies start with the model. Ours starts with the process.
Every vendor now sells AI and every board wants a plan for it. The result is often a list of pilots chosen because they demo well, not because they move a number. Most never reach production.
Our AI strategy consulting starts where the value is: the process, the data and the decision AI is meant to improve. If the process is broken, AI automates the breakage. If the data is scattered across tools, no model will fix that. We check both first.
We build with AI agents daily in our own delivery, so we know where it saves weeks and where it adds risk. That goes into the recommendation, including where AI is the wrong tool.
Problems we solve
The AI questions on the desk. Answered plainly.
Pilots that never ship
Proofs of concept that impressed in a demo and stalled before production, because nobody owned the process around them.
AI features you pay for and don't use
Copilots and add-ons bundled into every SaaS renewal, with no view of which ones earn their cost.
Data that isn't ready
Customer, operational and financial data spread across tools, in formats no model can use reliably.
Build, buy or wait
Whether to build on a foundation model, buy an AI product or wait for your existing vendors to catch up.
Risk nobody has mapped
Privacy, accuracy, security and governance questions raised after the pilot instead of before it.
Deliverables
What you get. One plan, not a pilot list.
AI opportunity map
Every candidate use case scored on value, feasibility, data readiness and risk.
A call per use case
Build AI-native, add AI later or leave alone, with the reasoning.
Data readiness assessment
Where the data each priority use case needs lives, what shape it is in and what it takes to fix.
Build, buy or wait analysis
For priority use cases: foundation model, AI product or existing vendor, costed over three years.
Governance guardrails
The privacy, accuracy, human review and security controls each use case needs before launch.
Sequenced plan
The first use case to ship, what it proves and what follows.
How it runs
Diagnose. Decide. Ship the first one.
Step 1 · 1–3 weeks
Diagnose
Processes, data and current tools reviewed. Candidate use cases collected from the people closest to the work.
Step 2 · 1–2 weeks
Decide
Use cases scored and called. Data, cost and risk checked for the shortlist. One written recommendation.
Step 3 · your choice
Close or continue
Act on the plan yourself, build the first use case with us or keep us on as adviser through rollout.
Who this is for
Operators with a decision on the desk.
CEOs and boards
You need an AI position grounded in your operations, not in a vendor's roadmap.
Operators with stalled pilots
You have run experiments. You need to know which to scale, which to stop and why.
CTOs and heads of data
You need an independent view on build vs buy and on whether your data can support what is being promised.
How we compare
The same question, three ways to answer it.
Common questions
What does an AI strategy consultant do?
They help you decide where AI should be used in your business, in what order and with what safeguards. Ours focuses on use cases that change an operating number.
How long does an AI strategy engagement take?
Usually three to five weeks, depending on how many processes are in scope.
Do we need clean data before starting?
No. Assessing data readiness is part of the work. We tell you what each use case needs and what it takes to get there.
Do you recommend specific AI tools or models?
Yes, when buying is the right answer. We hold no reseller agreements, so the recommendation follows the use case.
Can you build the use cases you recommend?
Yes. AI-native builds run through our Build service, with senior engineers who work with AI agents daily.
How do you handle AI risk and governance?
Each approved use case comes with its controls: data privacy, accuracy checks, human review points and security requirements.
Related services
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- BuildBusiness Process AutomationBusiness process automation that replaces tool stitches and manual handoffs with one owned workflow tool.
- PillarAdvisory overviewSix advisory domains and how an engagement runs, from diagnosis to decision.
Need a straight answer on AI?
Book a discovery call. Bring the use cases on your list and we'll tell you which are worth a closer look.
01Book a Discovery CallAdvisory starts with a discovery call