AI Enablement
AI Enablement for Enterprise Teams
After an AI mandate, buying the tools is the easy part. The harder part is the period that follows: months of unstructured trial and error as teams who have never written a system prompt are asked to be productive with one. Asta works alongside your existing teams during that period and installs the practices that turn AI from a line on the invoice into a reliable part of how work gets done.
What we see after the AI tools are switched on
After eighteen months of helping enterprises after their initial AI rollout, the same handful of issues come up across every engagement. Teams default to the most expensive model for every task because nobody told them they had a choice. Prompts get copied between colleagues with no record of which version actually works. Outputs get re-edited by hand because nobody knew the model could be told to write in the right format on the first try. Spend climbs, output quality stops getting better, and at some point a board meeting comes up where someone asks what the company is getting for the money, and the answer is harder to give than it ought to be.
What a trained team looks like
A team that knows what it is doing picks the right model for each task and reaches for an expensive reasoning model only when the task actually calls for one. They write prompts that are specific, testable, and version-controlled. They keep small evaluation sets so a change to a prompt produces a measurable result rather than an opinion in a Slack thread. They use tool calls and structured outputs to keep AI work auditable. The result is lower spend, faster cycle times on AI-assisted work, and output that an executive will sign off on without rework.
How we work
Engagements run four to eight weeks against a single function rather than the whole company. We start with two days of audit: which models are in use, what prompts are circulating, where rework is happening, what the actual cost per useful output looks like. From there we build a curriculum tailored to the function we are working with, because the examples and patterns that make sense for legal operations are not the same ones that make sense for software engineering or customer support. We run the team through workshops grounded in their own work and their own data. We close with a measurement phase: thirty days of telemetry against a pre-engagement baseline, so leadership can see what changed and where the gains came from.
Who this is for
Most useful when an organisation has already deployed AI tools, has a leader accountable for the return on that investment, and a team that needs to be productive with the tools faster than self-study allows. We work with functions rather than whole companies. The functions we have most experience with are finance and FP&A, customer operations, legal operations, software engineering, and marketing. We work onsite or remotely, in English, in any time zone.
What you take away
Three artifacts stay with your team after the engagement. A function-specific prompt library built around your actual work, with the evaluation cases that prove each prompt does what it claims. A starter evaluation harness your team can extend as the work evolves. A written reference set, the Asta Prompting Guides, covering foundations, OpenAI, and Claude. The guides serve as the textbook for everything we have installed during the engagement, and your team keeps them indefinitely with no subscription or licence renewal.
Request the foundations volume.
Leave your details and we will send the foundations volume of the Asta Prompting Guides to your inbox.
Briefing
Tell us what your team is using AI for and where it is falling short. We will respond with whether an enablement engagement is a fit and, if it is, what the engagement would cover and how long it would take.