Questions,
answered.

It's a 45-minute conversation — no slides, no pitch. We'll ask about your business, your processes, your biggest frustrations, and your goals. By the end, you'll have a clear sense of whether AI is likely to help and what the right starting point would be. There's no obligation to proceed.

No. Each tier — Discover, Evaluate, and Implement — is available independently. Many clients start with Discover and then decide what to do next based on the findings. We'll always recommend the approach that makes most sense for your situation, even if that means doing less with us.

Discover typically takes 2–3 weeks. Evaluate takes 3–4 weeks. Implementation varies depending on the complexity of the work — we'll estimate this clearly before anything begins. End-to-end, a full engagement across all three tiers usually runs 10–20 weeks.

Yes. Aifficiency is deliberately structured so that Alex leads every engagement. If a project benefits from specialist input — sector expertise, technical knowledge — relevant people from the wider network may be involved, but Alex is always the primary point of contact and accountability.

Access to the right people and a willingness to be open about how your business really works. The quality of the output depends on the quality of the input. We typically need 2–4 hours of your team's time per week during Discover, less during Evaluate, and more during Implementation.

After the scoping call, we'll provide a fixed price before any work begins. The price reflects the size and complexity of your business — a 20-person firm is a different engagement to a 150-person one. The figures on our pricing page are starting points; your quote will be specific to your situation.

Implementation involves working alongside your team and vendors in a live environment. The pace and scope can shift based on what's discovered during delivery. Time and materials gives you flexibility — we agree an estimated range upfront, you receive weekly timesheets, and you can pause or adjust as needed.

We handle scope changes transparently. For fixed-price work, any significant change to scope is discussed and re-agreed before we proceed. We don't quietly expand scope and invoice for it later.

Not currently. We structure engagements around specific, defined outcomes — we think that's a better model for both sides. If you need ongoing advisory support after an engagement, we can discuss what that looks like on a case-by-case basis.

Mostly practical, applied AI — not research-grade technology. This includes process automation, machine learning for forecasting and categorisation, AI-assisted document processing, intelligent scheduling, natural language tools for customer service, and data analysis. We focus on what's proven, available, and right for your scale.

In most SME contexts, no. The more realistic outcome is that AI handles repetitive, low-value tasks — freeing your people to focus on the work that actually needs them. In a growing business, that often means you don't need to hire as quickly, rather than needing to let people go.

That's a legitimate outcome, and we'll say so clearly if it is. The Discover process might reveal that the biggest opportunity is actually a simpler process change, not AI at all. We'd rather tell you that early than build a case for something you don't need.

AI is moving fast — but the tools available now are already capable of delivering real, measurable value for most SMEs. Waiting for "better" means losing ground every month to competitors who are already moving. The right approach is to start with problems that have clear solutions today, not wait for a perfect future state.

Almost certainly yes. The businesses getting the most value from AI right now aren't tech companies — they're logistics firms automating their reporting, retailers improving their forecasting, and professional services firms cutting admin time. If you have repeating processes, you have AI opportunities.

Not necessarily. Many of the tools we evaluate and recommend are designed for non-technical users and don't require internal IT resources to run. Where technical implementation is needed, we factor that into the plan — either by working alongside your existing team or by identifying appropriate external support.

Typically businesses with between 20 and 250 staff. Smaller than that, and the scope for AI investment is usually limited. Larger, and the complexity often warrants a different kind of engagement. That said, we assess each situation individually — size isn't the only factor.

Both, depending on what's needed. In many cases, we're configuring and deploying existing tools rather than building from scratch — which is usually faster and more cost-effective. Where custom development is required, we can work alongside your chosen development partner or help you find one.

Implementation includes 30 days of post-launch monitoring and optimisation as standard. After that, most clients are in a position to manage the tools themselves. If you want ongoing support beyond that, we can discuss what's appropriate.

Problems during implementation are normal — the question is how you handle them. We stay in the room and work through issues as they arise. Our role is to make the project succeed, not to hand over a document and disappear.