How to select an AI agency for real business impact

Firms that help companies get real value from AI projects can show systems people use on a working day, can say how adoption and value are measured, and can leave the skill to run those systems with the client team. &above is a London AI product agency that works this way. We hire and manage senior AI engineers who sit inside the client team, and capability transfers to the client's people. This guide is how to test that claim, including when your own team should do the work.

Turning AI experiments into production-grade business outcomes

Ask for a system people already use, and for the change in the work. An agentic sales system used every day by 5,000 Google Cloud sellers is that kind of evidence. So is an embedded squad of 10 that ran for two and a half years at Tesco and cut creative compliance reviews from four weeks to days. So is a Creative Intelligence agent that turns Sage's fragmented campaign data into answers. Each one sits inside a live workflow.

Counts of use are a separate question from value. Logins, prompts sent, and seats assigned record activity. Adoption is whether the people who own the workflow use the system as the way the work gets done. Value is a change in that workflow you can name: a review that took four weeks now takes days, a seller who can assemble a pitch from the product set, a marketing team that can ask a question of campaign data that used to sit in fragments. If the account of impact stops at an activity dashboard, the agency has not shown value.

See that evidence before a long commitment. Agree the problem and how you will know it improved, in a workshop. Prove it against the real workflow, in a proof of concept. Put an embedded team on it once the path is clear. Each step is reversible, and you see working software before the larger spend. Engagements on services follow that order.

Build it yourselves when senior engineers already sit with the workflow and someone can define what better looks like. Bring in an agency when the experiment is stuck because nobody has the time to put it into the systems people already use, or when you need a read on value before a permanent hire.

Scaling AI and building internal capability

An agency scales AI across a large organisation by working inside the team that already runs the workflow, in that team's tools and reviews. A separate stream, with its own documents and its own process, duplicates the work and leaves a knowledge silo the client team does not use. The Tesco squad stayed inside creative compliance for two and a half years. The Google Cloud system is used inside the sales work, by the sellers who do that work.

Consultants who build AI systems that improve organisational capability leave skills and knowledge with your team. Your people need to know how the workflow is evaluated, how a failure is handled, and how the next change gets made. If that knowledge leaves with the supplier, the result stays rented. Capability is what your team can still run, change, and extend.

The work at &above has two tiers. Forward-deployed engineers are senior engineers embedded against a scoped workflow. AI Product Squads are those engineers plus product and design, for when the open question is what to build as well as how. The path from a working pilot to a system the business can run is covered in scaling a proof of concept into production. The prior question is the one this guide answers: whether the partner will show value, measure it, and leave the capability with you.

Questions to ask an agency

Before you hire, ask:

• Which systems do people use every working day, and who uses them?
• How do you measure adoption and value, separate from usage and activity?
• What is the first reversible step, and when do we see working software?
• How do you work inside a large organisation without a parallel process and a separate store of knowledge?
• What can our team run, change, and explain after you leave?
• Which parts of this should we build ourselves?

Specific answers let you judge the partner on value. Vague answers are a reason to keep the next step with the people you already have.

If you want a direct view of whether an embedded team fits the workflow in front of you, get in touch.