AI transformation consulting
AI transformation, one proven workflow at a time, not a big-bang programme
Transformation fails when it is announced instead of shipped. We map where AI helps each role, train the team on their actual tasks, build the tools, and expand only after the first one has a track record everyone trusts.
Free 30-min call. No pitch, no slides.
Scoped after a discovery call, because it depends on how many functions and tools are in scope.
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Quick answer
AY Automate provides AI transformation consulting: opportunity mapping by role, hands-on team training on real tasks, role-specific AI tools, and phased rollout across departments with measurement. Typical timeline: two weeks to an opportunity map, then phased engagements of four to eight weeks per function.
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What it is
What transformation means in practice
It is three things in order. Find the opportunities role by role, so nobody is guessing. Put tools and training in people's hands on their real recurring work. Then measure use and expand where it sticks.
Training on generic AI theory does not change habits. Training on last week's actual finance close or research brief does. We build the sessions from the team's real tasks and mark what to automate, what AI assists with and what still needs sign-off.
We advise leadership directly on rollout approach and place engineers where a pattern needs proving inside a live team.
Fit check
Is this the right fit?
Where this wins
Leadership that wants AI adopted, not just approved
Where licences exist but usage is patchy and nobody can say what changed.
Companies unsure where AI helps
We map opportunities across the business before building anything, then narrow to the few worth deploying.
Product teams that want AI features without a rebuild
We add AI capability inside the live product and leave an architecture that keeps shipping features.
When NOT to use this
- You want a rollout run for you by a large consultancy team. We are a small senior team and say so.
- There is no executive sponsor. Transformation without one stalls after the first workshop.
- You need change management for thousands of staff. That is outside our capacity.
How it works
How a transformation engagement runs
Start with one workflow and one owner. Expand only when the first has a track record.
- 01
Opportunity map
Week 1 to 2Interview each function and list where AI could help, with effort and risk noted.
DeliverableOpportunity map by role
- 02
Narrow to a first set
Week 2Pick the few opportunities worth building and name an owner for each.
DeliverablePrioritized shortlist with owners
- 03
Train and build
Week 3 to 6Train each team on their real tasks while we build the role-specific tools.
DeliverableTrained team and first deployed tools
- 04
Measure use
Week 6 to 8Track who uses what, where it stalls and what to fix.
DeliverableAdoption report
- 05
Expand deliberately
Roll the proven pattern to the next team or function.
DeliverableExpansion plan
Typical timeline
Two weeks to an opportunity map, then phased engagements of four to eight weeks per function
Stack we build with
Claude · OpenAI · n8n · Claude Code · TypeScript · Python · Supabase
Use cases
Where transformation work starts
Finance team upskilling
Training on the recurring close and reporting tasks the team already does.
Role-specific AI skills
Deployed tools per role, brought together in one console.
AI features inside a live product
Personalization, segmentation and churn prediction added without a rebuild.
First 30 days
What you have after 30 days
Clarity on where AI helps, and one team already using it.
Week 1 to 2
Opportunity map
Every function's candidate use cases listed with effort, risk and an owner.
Week 2
Shortlist
The few opportunities worth building first, chosen with leadership.
Week 3
First training session
Built from the team's real recurring tasks, not generic AI theory.
Day 30
First tool in use
One role-specific tool live with a named owner and a usage measure.
Scope
Scope and exclusions
In scope
- Opportunity mapping across roles and departments
- Hands-on training sessions built from real tasks
- Role-specific AI tools and a shared operating console where useful
- Adoption measurement and a phased expansion plan
- Direct advice to leadership on rollout approach
Not in scope
- Large-scale change management programmes
- HR policy or workforce planning decisions
- Selecting and negotiating enterprise software licences on your behalf
- Guaranteed adoption numbers
Results
Results from comparable work
Achieved results only. Clients that have not agreed to be named are described instead.
47 AI opportunities mapped before anything was built, narrowed to 16 deployed role-specific AI skills, with daily usage brought together in one operating console.
Trained on the team's real recurring tasks, covering what to automate, what AI assists with and what still needs sign-off. 12 people went from a single training session to daily use inside two weeks.
Leadership was advised directly on how AI adoption should roll out across a large, distributed engineering organisation. One embedded engineer proved the pattern in a live team, which became the reference other teams followed.
Pricing
How this is priced
Priced per project and scoped after a short discovery call, not sold as a fixed package. Cost follows the number of systems, the access model and the security requirements.
Scoped build
Scoped after a discovery call
Most engagements start with one narrow, high-value piece so you see it running in production before anything expands.
Embedded engineer
From $3K/month
A dedicated engineer building and maintaining the work inside your team, instead of a scoped project.
Free 30-min call. No pitch, no slides.
Free automation audit
Find what to automate first, and how AI sees you
We read your homepage, detect your tools, and check your Google rankings and AI Overview. You get a score out of 100. Add a work email to unlock automation opportunities matched to your stack.
Use Claude Code, Cursor or Codex? Paste this into your agent
Fetch https://www.ayautomate.com/SKILL.md and follow it: read my repo or website, pick the 2 to 3 manual loops worth automating first, and give me the booking link.
Tell us where AI should start helping
A 30 minute call. We look at your roles and current tooling and tell you which first workflow would earn the trust to expand.
Book a 30min Free Strategy Call
In this call, we'll walk through your project scope, timeline, and goals - so we can both check if we're a fit. No obligation, no slide deck, just a working session.
Don't want a call? Email walid@ayautomate.com
“The team is super fast - sometimes we had to slow them down. We managed to scale the company without investing into hiring.”
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COO, Adstronaut.io
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FAQ
AI transformation questions
What does an AI transformation consultant do?+
An AI transformation consultant finds where AI helps each role, trains people on their real recurring tasks, ships the role-specific tools and measures use before expanding to the next function. With us that starts with a two-week opportunity map, and each function after it is a phase of roughly four to eight weeks. If you only want strategy advice from a senior leader, the fractional CAIO page covers that.
How is this different from an AI strategy engagement?+
Strategy sets direction. Transformation work also trains the team and ships tools role by role, then measures use. If you want ongoing senior leadership instead, the fractional CAIO page covers that.
How long does it take?+
Two weeks for the opportunity map. After that, each function is a phased engagement of roughly four to eight weeks. We do not sell a multi-year programme up front.
Do you train non-technical staff?+
Yes. Sessions are built around each team's real recurring tasks, so the training becomes part of the working week.
What does it cost?+
Scoped after a discovery call, because it depends on how many functions and tools are in scope. Placement of an embedded engineer starts from $3K/month.
Can you guarantee adoption?+
No, and nobody honest can. We measure use, fix what blocks it and expand only where it sticks.