AI Advisory & Team Enablement
Make AI useful for your business
— not just interesting.
I help leadership teams turn AI curiosity into confident team adoption and measurable operational results: the right use cases, an educated workforce, and pilots that hold up in daily work.
The problem
Plenty of interest.
Very little traction.
In most established businesses I speak with, AI is not a technology problem yet. It is a clarity problem. These are the patterns I see most often.
- 01Leadership knows AI matters but has no shared view of where it fits in this business.
- 02Employees are experimenting on their own, with no guidance on what is safe or useful.
- 03Vendors are pitching tools before anyone has defined the problem worth solving.
- 04Early experiments produced interesting demos and very little operational change.
- 05Nobody owns the questions around data privacy, accuracy and acceptable use.
Services
Five ways I help, depending on where you are.
Executive AI Strategy
Plain-language sessions for owners and leadership teams: what current AI can and cannot do, where it matters for your business model, and what decisions need to be made first.
AI Opportunity Assessment
I look at how work actually moves through your teams, identify where AI could save time or improve quality, and rank the opportunities by value, effort and risk.
Employee Workshops & Training
Hands-on sessions built around your team's real tasks, not generic demos. People leave knowing how to use the tools well, and where not to rely on them.
Pilot Implementation & Adoption
A focused pilot on one or two priority use cases, with clear owners, success measures and the process changes needed for people to actually keep using it.
Ongoing Advisory
A regular check-in as adoption grows: reviewing results, adjusting priorities, evaluating new tools and keeping governance in step with usage.
Clear lines
Strategy, training and implementation are different jobs.
You may need one, two or all three. Being clear about which is which keeps the scope honest and the budget sensible.
- Strategy
- Deciding where AI belongs in the business, and where it does not. The output is a prioritized roadmap leadership can act on.
- Training
- Building practical confidence across the team so that adoption does not depend on one or two enthusiasts.
- Implementation
- Putting a specific use case into daily work, measuring it, and adjusting. Where specialist technical build is required, I help you scope it and work alongside the right people.
How an engagement works
A phased approach, tailored to your business.
- Phase 1
Discovery call
A conversation about your business, your goals and where AI questions are coming up. We decide together whether there is something worth pursuing.
- Phase 2
Assessment & prioritized roadmap
Interviews and working sessions with key people, followed by a short list of use cases ranked by business value, effort and risk.
- Phase 3
Hands-on team enablement
Workshops for leaders and employees, plus simple usage guidelines so people know what is encouraged, what is off-limits and why.
- Phase 4
30–90 day pilot & measurement
One or two priority use cases put into real work, with baseline measures agreed up front and an honest review at the end.
Not every business needs every phase. Some start with a single executive session; others go straight to a team workshop. We agree the scope after the discovery call.
Where AI tends to help
Practical goals,
not promises.
These are typical areas we might explore. Whether any of them make sense for you, and what a realistic target looks like, is exactly what the assessment is for.
- Operations
- Goal: Reduce time spent on routine reporting, documentation and handoffs between teams.
- Knowledge retrieval
- Goal: Help employees find answers in policies, procedures and past work without hunting through folders or asking the same three people.
- Marketing
- Goal: Speed up first drafts, research and content adaptation while keeping the brand voice and human approval intact.
- Customer service
- Goal: Shorten response times with drafted replies and better access to account history, reviewed by staff before anything goes out.
- Employee productivity
- Goal: Give people practical help with email, meeting notes, summaries and analysis so more time goes to work that needs judgment.
Responsible AI
Useful only counts if it is also safe.
Privacy
We start by clarifying what data can and cannot go into which tools, and choose options that respect your client and employee confidentiality obligations.
Governance
Simple, written guidelines on acceptable use, approved tools and accountability — sized for a mid-market business, not a bank.
Human review
AI drafts, people decide. Anything customer-facing or consequential keeps a person responsible for the final call.
Change management
Most AI efforts stall on habits, not technology. I pay as much attention to how people work as to which tool they use.
In person or virtual
Wherever the work happens best.
Leadership sessions and team workshops often work best in the room, and I meet clients in person across Toronto and the GTA. Assessments, follow-ups and ongoing advisory work well virtually, including for businesses elsewhere in Canada.
What happens in a discovery call
Around 30 minutes. No preparation needed, and no obligation.
- A short overview of your business, team and current priorities.
- Where AI is already being used, formally or informally.
- The questions or concerns your leadership team keeps returning to.
- Whether an assessment, a workshop or something else makes sense as a first step.
- An honest view on fit. If I am not the right person, I will say so.
Questions
Frequently asked.
Who is this for?
Established Canadian businesses, typically in the $5M–$50M revenue range, where leadership wants a clear, practical view of AI and a team that can use it responsibly.
Do we need a technical team or an AI budget already in place?
No. Most clients start with off-the-shelf tools they may already be paying for. Part of the work is deciding what, if anything, is worth spending more on.
Do you sell or resell any software?
No. My recommendations are tool-neutral. I am paid for advice and enablement, not for which product you choose.
Do you build custom AI systems?
My focus is strategy, training and adoption. When a use case needs custom technical work, I help scope it and work alongside your IT team or a specialist partner.
How long does an engagement take?
It depends on the business. An assessment can take a few weeks; a pilot usually runs 30 to 90 days. Everything is tailored after the discovery call.
Do you work in person?
Yes. I work in person across Toronto and the GTA, and virtually with businesses elsewhere in Canada. Many engagements combine both.
Can you guarantee specific results?
No, and you should be cautious of anyone who does. What I commit to is clear goals, agreed measures and an honest review of what worked and what did not.
Ready to find out where AI actually fits?
Send me a few lines about your business and what you are hoping AI could help with. I will reply personally to arrange a discovery call.