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    Services / AI buying decision

    Pick the AI model your team can execute.

    SMEs and enterprise teams face different delivery constraints. We compare where each model works best and what to decide first.

    An SME often needs one fast-moving, high-impact workflow. Enterprise buyers usually need portfolio governance and staged adoption. Both can work, but the model must match your operating reality.

    If this sounds like you

    Who is this for?

    Teams deciding whether AI should begin as a focused SME-style use-case delivery or a broader enterprise-led programme.

    How fast?

    Most teams get a recommended model in 1–2 weeks.

    What will it cost?

    We recommend fixed-scope starts for first outputs, with clear phase gates for broader rollout.

    What result should I expect?

    A clear AI model that fits your team capacity, governance style, and funding cadence.

    Not a fit if you already have a locked-in procurement model and only need implementation support for pre-defined initiatives.

    The problem we hear

    Wrong AI model selection creates delivery delays, wasted spend, and ownership problems.

    Scope is too broad for available bandwidth

    Small teams often try to solve everything with one pilot and then stall when adoption is high risk.

    Governance is treated as optional

    Enterprise programmes can fail without portfolio-level ownership and risk controls.

    Cost and pace are misaligned

    A fixed-scope service can be safer for one use case, while fractional leadership may be needed for a broader programme.

    How we approach it

    01

    Segment your operating model

    Assess team size, process maturity, and internal ownership before selecting a commercial model.

    02

    Define the first decision page

    Choose one use case for SMEs, or a portfolio view for enterprise rollout.

    03

    Match model to risk

    Compare speed, governance and internal support required for each option.

    04

    Agree first step

    Set one visible first slice with explicit owner and success signal.

    What good looks like

    Clear, documented model choice for your current phase.

    Reduced over-scope in year one AI programmes.

    Ownership boundaries that prevent delivery drift.

    A faster path from discovery to first measurable outcome.

    What we assess

    Team capability fit

    Internal ownership, adoption rhythm, and training capacity.

    Governance requirements

    Decision rights and control points for high-risk use cases.

    Commercial model fit

    Fixed-scope starts, fractional leadership, or platform build selection.

    Pilot-to-runbook map

    A route from first decision to ongoing operations.

    Delivery rhythm

    Recommended cadence for your capacity and governance constraints.

    Client outcome blocks

    SME teams moving from pilot spam to one priority output

    Multiple proofs were competing for attention without ownership.

    Clear ownership and one selected use case delivered first, with a practical roadmap for expansion.

    Typical delivery duration: 3–6 weeks

    Vignettes are anonymised composites drawn from engagements and product work. No client names, logos, or performance figures are implied.

    Frequently asked questions

    Are SMEs expected to run AI differently?

    Usually yes. SME programs need sharper scope and smaller operating loops.

    Do you support mixed teams?

    Yes, we support hybrid models with smaller pilots and structured executive governance.

    Can this become a portfolio programme later?

    Yes, once outcomes, ownership, and capacity prove sustainable.

    Choose your starting model with clarity.

    We can help you decide whether to start with a fixed-scope pilot, portfolio leadership, or direct implementation.

    Book Your Free Discovery Call