Preparing your company for the AI age - the first phase
We help companies become AI-first
Situation
This is more than a solution. This is a transformational project. We help entire teams become AI-first.
The program is designed for investment teams, consulting teams and other businesses whose performance depends on the strength of their people.
The ambition is to double or triple the team's productivity while raising the quality of the work:
20 people work like 40, and juniors work like seniors
The first phase builds the skills, habits and shared systems needed to pursue that ambition.
Opportunity
Giving everyone access to an AI tool leaves several questions unanswered. Who helps people use it well? What motivates them to change how they work? How do useful experiments become methods the whole team can use?
This first-phase package brings those questions together. It focuses on training your team, motivating the use of AI and setting up the infrastructure for AI use to scale across the company.
The approach draws on our hands-on work in a 2026 AI transformation project. It brings practical training, an internal AI team and a structured process for developing new initiatives into one program.
Solution
We begin with your business priorities and the work your people do. Together, we identify the common foundation your team needs and choose real tasks to use in training.
People practice on work they recognize: researching an investment opportunity, synthesizing due diligence, preparing a client analysis or reviewing a presentation. They learn to give AI relevant context, break work into clear steps and check sources and reasoning.
We help establish an internal AI team with a lead, a leadership sponsor and time set aside for the work. Employees bring forward recurring problems. The team assesses value and feasibility, assigns owners and tests selected solutions before sharing them more widely.
We turn useful methods into resources the team can reuse: project instructions, templates, quality checklists, AI skills and workflows. These capture the context and standards that make good work easier to repeat.
The learning format evolves with the team. Initial sessions establish a common foundation. Pair challenges, demonstrations and experience sharing then help people apply it. Colleagues test what they build, share useful methods and get feedback. Managers reinforce these habits in project reviews and coaching.
The first phase brings this together: practical training, internal ownership, shared working principles and resources, and a process for developing new initiatives. Clear rules for data use and human review help the team apply AI responsibly as its use grows.
Expected benefits and how to measure them
The goal is a stronger team: people take on more demanding work, spend less time on repetitive preparation and use shared methods to improve the quality of what they deliver.
Measure progress through real work. Set a baseline for selected tasks, then compare delivery time and quality. Track whether people reuse the methods and whether selected initiatives reach implementation. Use the findings to decide where to invest next.
The next phase focuses on implementing the workflows with the clearest value, with owners, review controls and measures agreed before scaling.
Common questions
Who is this AI transformation program for?
It is designed for investment teams, consulting teams and other businesses whose performance depends on the quality of their people's work. The approach stays the same; the tasks, examples and training priorities reflect your team.
How is this different from a standalone AI course?
The program connects training with internal ownership, shared methods and a process for developing AI initiatives. It begins with a common foundation, then evolves toward practical challenges and peer sharing so people can apply what they learn.
Do we need an internal AI team?
Someone needs to own the work. We help define an AI lead, a leadership sponsor and the colleagues who can test and share useful methods. The time and responsibilities should fit the size and capacity of your organization.
How do we know when to move to the next phase?
Review whether people use the methods in real work, check the results and share what works. Move selected initiatives into implementation when the workflow, owner, review controls and measures of value are clear.