Six-month plan

For small and mid-sized businessesAI that changes how the business actually runs

A hands-on six-month plan to choose the right work, put first initiatives in motion, and leave your team able to continue. Not a slide deck. Not a science project.

Most AI work stalls before it changes the business

Small and mid-sized teams do not need another tool demo. They need a short list, someone to help ship the first work, and a way for people already on staff to keep going.

  • Too many ideas, no order

    Chatbots, copilots, automation, new software—everything sounds useful. Without a ranked shortlist, the team stays in discussion.

  • No one has time to own it

    Owners and operators are already running the business. AI becomes evenings, side projects, and half-finished pilots.

  • Pilots never become operations

    A promising trial sits with one person. There is no workflow, no quality check, and no plan for the rest of the team.

A six-month plan, scoped to your business

We work with you to pick a short list, implement the first initiatives, and measure what changed. Pricing is discussed for your situation—not published as a one-size fee.

Duration
6 months
Built for
SMBs
Approach
Strategy and delivery

The six months cover strategy and roadmap, workflow design, governance, use-case prioritization, team enablement, first initiatives, and a plan for what comes next.

The aim is simple: visible change in how the business runs, and a team that can continue without starting over.

Talk through the six months

What the six months are for

Clear work, defined up front—so you know what will exist at the end of the plan.

  1. 01

    Strategy and roadmap

    Where AI should help this business, where it should not, and the sequence of work for the next year.

  2. 02

    Workflow design

    Concrete ways of working for operations, finance, sales, or delivery—designed around how your team already spends its time.

  3. 03

    Governance

    Practical rules for data, quality, and decision rights so AI does not become an unmanaged side project.

  4. 04

    Use-case prioritization

    A short ranked list chosen for value and feasibility—not a catalogue of every possible idea.

  5. 05

    Team enablement

    Hands-on support for the people who will live with the work: how to brief it, review it, and keep quality high.

  6. 06

    First initiatives

    Real work in motion—not only a plan. Early initiatives that create visible value and teach the company how to operate.

  7. 07

    Next-step plan

    What to keep, what to stop, and what the next six to twelve months should look like once the first work is in place.

Use cases

Where the six-month plan shows up

Examples of AI work we structure and help ship—always with people accountable for the outcome.

  • Marketing

    Competitive research that marketers can act on

    Marketing teams often research competitors by hand—campaigns, landing pages, positioning, personas, trends—under tight time and budget. Coverage is uneven, so decisions lean on incomplete evidence.

    Approach

    • An agentic research system with sub-agents that map competitor messaging, tone, value props, and CTAs
    • Surface creative patterns; compare against the live campaign
    • Propose alternate positioning for A/B tests
    • Flag messaging gaps and opportunities—with sources for review

    Outcome

    • Less time on ad-hoc research
    • Deeper, more consistent competitive briefs
    • Sharper segment messaging
    • Faster experiment cycles
    • Decisions backed by evidence marketers can check

    Oversight

    AI supports judgment—it does not replace it. Marketers validate sources, approve recommendations, and own compliance with brand, platform rules, privacy, and local advertising requirements before anything publishes.

  • Sales

    Next-best action across a wide product portfolio

    When the catalogue is large, sales default to a handful of familiar SKUs. Cross-sell suffers, research burns quota time, and marketing cannot see which products or incentives are under-worked.

    Approach

    • A looping agentic system (chat + back office) that reads leads, product data, comparisons, commissions, and engagement history
    • Recommends providers/products; drafts pitch language and discovery questions
    • Flags promotions; suggests cross-sell/upsell
    • Prepares outreach and meeting talking points; points to the next best action—while humans validate scraped and social signals

    Outcome

    • Broader catalogue coverage in live deals
    • Clearer pitches
    • Less time digging for product facts
    • Marketing visibility into demand vs. advisor attention
    • Campaigns aimed at real gaps

    Oversight

    Sales and marketing approve outbound content and recommendations. Commission and promo logic stays human-confirmed. No automated sends without review.

  • Manufacturing

    Shop-floor and ops decisions with clearer signal

    Mid-size manufacturers juggle production schedules, quality exceptions, maintenance, and inventory across systems that do not talk cleanly. Supervisors spend the day chasing status instead of deciding; AI “pilots” stall because no one owns the workflow or the data.

    Approach

    • Over six months we pick one high-friction loop (e.g. exception triage, demand vs. capacity, or maintenance work orders)
    • Map the sources of truth; put a constrained agentic layer on top for summarization and recommended next steps
    • Wire it into how planners and floor leads already work—not a parallel dashboard nobody opens

    Outcome

    • Faster exception handling
    • Fewer blind handoffs between planning, quality, and maintenance
    • A documented operating rhythm the team can keep after the engagement
    • A path to add a second loop once the first is trusted

    Oversight

    Operators and planners stay accountable for schedule changes, quality disposition, and safety-critical calls. Models recommend; people approve. We do not invent uptime or scrap-rate guarantees.

How the six months unfold

A simple sequence: choose the work, launch the first initiatives, then tighten what works and plan the next step.

  1. Months 1–2

    Choose

    Understand how the business runs today. Set strategy, roadmap, and a shortlist you can actually staff.

    • Clear AI and transformation priorities
    • Governance light enough to use
    • Ranked use-case shortlist
  2. Months 3–4

    Launch

    Turn the plan into workflows and first initiatives. The team starts working with the new way, not only reading about it.

    • First initiatives in motion
    • Workflows the team can follow
    • A working cadence with the people involved
  3. Months 5–6

    Anchor

    Deepen enablement, keep what works, drop what does not, and leave a next-step plan the business can act on.

    • Team able to run the core workflows
    • Measured results against the original goals
    • A concrete plan for what comes next

How we measure success

The point is not activity. It is a business that works differently, and a team that can continue.

  • Priorities are written down and in use—not a backlog of every AI idea.
  • First initiatives have moved from discussion into day-to-day work.
  • Workflows and light governance exist so quality and data stay under control.
  • The people who do the work have been accompanied, not left with a deck.
  • You have a next-step plan based on what actually worked.
See if a six-month plan fits

Funding the initiatives

AI and business transformation work can often be supported by Canadian programs. We can help you see what may apply—then you decide whether to pursue it.

  • SR&ED

    Federal SR&ED tax credits when an initiative involves genuine technological uncertainty—not every AI project, only the ones that qualify.

  • Federal grants and credits

    National programs that can support AI adoption, innovation, and workforce or process transformation.

  • Provincial programs

    Province-specific grants and credits that can help fund pilots, training, and first initiatives.

The SR&ED tax credit and other federal and provincial grants can reduce the net cost of first initiatives when the work qualifies. This is optional, and separate from the six-month plan.

Questions companies usually ask

A six-month plan is a working engagement, not a workshop series.

Who is this for?
Small and mid-sized businesses that want AI and transformation to show up in operations—not only in a strategy document. If you have a team that is busy running the company, this is built for you.
Do we need a data science team?
No. The plan is designed for companies that do not have a dedicated AI department. We work with the people you already have.
How is this priced?
The scope is discussed for your situation. We do not publish a single public fee, because the work depends on the size of the team, the starting point, and the first initiatives.
What happens after six months?
You keep what works. That may mean continuing with us, handing the work to someone internal, or pausing. The next-step plan is written so that decision is concrete.
How is this different from a workshop?
Workshops end with slides. This plan is meant to leave workflows, first initiatives, and people who have already been accompanied. The test is whether the business started to run differently.
Can funding help pay for the work?
Sometimes. Canadian grants and SR&ED tax credits can apply to qualifying initiatives. We can walk through what may be relevant. Contact us to learn more.

If a six-month plan sounds useful, let’s talk

Tell us how the business runs today and where you want it to be in six months. We will tell you whether this is the right fit.