AI Transformation for Sales Teams: from theory to workflows the team uses every day
In twelve weeks we identify where AI genuinely improves sales execution, decide what to buy and what to build, implement it inside the workflow you already use and train the team until they use it on their own. Use cases in production, not a demo.
If any of these sounds familiar
Tools get tried, but not adopted
You're paying for licences and there's a Slack channel full of prompts. Three months in, almost nobody opens the tools.
There are use cases, but no priority
Everyone has an idea of where to put AI, and nobody has measured which one moves the number.
The result depends on who writes the prompt
Without shared criteria, the output is inconsistent, it can't be reviewed and so it can't be improved.
The team doesn't know where AI fits into their day
It's seen as a separate tool, not as part of preparing a call, qualifying or reviewing the pipeline.
You're asking AI to analyse a CRM that's half empty
It confidently returns conclusions about data that doesn't exist, and the team stops trusting the tool after the first meeting.
There's activity. There's just no impact yet.
An implementation, not an experiment.
We're not here to explore AI for the sake of it. In twelve weeks we work with you to identify where AI genuinely improves how the team sells, decide what to buy and what to build, and implement it inside the tools and workflows you already use: account research before every conversation, qualification filled in from the transcripts, outbound drafted from the signal, pipeline review with the at-risk opportunities already flagged. At the end you won't have a list of ideas. You'll have use cases in production and a team that uses them.
What we deliver
Who it's for, and who it isn't
How it works: three phases
- [01]
Where it adds value
We go through how the team works today and how much of their time goes on mechanical work: research, notes, drafts, reading the CRM out loud. From that come the use cases that move the number, each with a buy-or-build decision.
- Deliverable: prioritised use cases and a buy / build recommendation for each case
- Duration: first month
- [02]
Build and integrate
The highest-impact cases are built or configured inside your CRM and your calling tools, with the process redesigned so that AI improves how the work is done rather than adding one more tab.
- Deliverable: use cases in production, integrated and with an execution log
- Duration: second month
- [03]
Adopt and measure
Hands-on sessions with your real cases until the team uses it on their own, and a measurement framework to know what has changed and decide with data where to keep investing.
- Deliverable: adoption sessions, internal guide and measurement framework
- Duration: third month
What you walk away with
What it costs, up front
We fix the figure with the scope, in writing, before we start. If you've done the RevOps & GTM Diagnostic, it comes straight from it. What drives it: the number of use cases to implement, the number of people to train and their starting levels, the integrations needed with the CRM and the calling tools and how much has to be custom-built versus configured on existing tools.
Before you ask
The programme is quoted according to the number of use cases, the people to train and what has to be custom-built, and the figure is agreed with the scope, before starting and in writing (if you're coming from the Diagnostic, it comes out of it). We don't publish a "from" price here: three cases configured on existing tools and three custom agents are very different programmes.
What comes before and after
Bring AI into your team's real workflow
Tell us how your pipeline works today and we'll tell you honestly where we'd start, or whether we're the right fit.
30 minutes, no sales pressure.