Bring the work. We will work on it with you.
Most AI training happens outside the work.
Someone demonstrates a tool. Participants practice a technique. Everybody learns a few useful ideas.
Then Tuesday happens.
The inbox fills up. The customer needs something. The deadline moves closer. The employee returns to the workflow they already know. We take a different approach.
AI Work Labs build AI capability inside the work itself. Your people bring real work they are responsible for completing, and we work on it together. We use current AI capabilities to improve the output, rethink the process, and help employees develop the judgment required to direct AI well.
That is our approach to AI training for teams.
We Work Together
Bring us the work.
It might be a campaign brief, a customer analysis, a competitive report, an account plan, a presentation, a research project, a recurring task nobody likes, or a process everyone knows takes too long.
We help employees work through it with AI while the context, constraints, expertise, and consequences are real.
That matters because using AI well is not primarily about remembering prompts. It is about making decisions.
What should I delegate? How should I direct it? What context does it need? Is this output good enough? What is missing? When should I intervene? Where does my expertise still matter?
And if AI makes this dramatically easier, what should change about the work around it? Those decisions are learned by making them.
We Bring the Frontier Into the Room
Every new AI release does not deserve your team’s attention. Some do.
A model becomes capable of handling work that failed six months earlier. Agents become reliable enough to manage a longer sequence. Research capabilities improve. Multimodal tools make a previously manual process practical.
The important thing is not simply knowing that the capability exists. It is recognizing that something your team does may now need to change.
We stay close to those developments and bring the relevant ones into the Lab. Then we test them against your work.
What You Leave With
Depending on the engagement, your work lab can include:
- Applying AI to real responsibilities
- Better judgment about delegation
- Repeatable workflows
- Clearer human/AI boundaries
- Ability to recognize when task gains should trigger workflow redesign
Different Teams. Different Work.
The model stays the same, but the work changes by function.
Marketing teams might work on campaign planning, message exploration, competitive monitoring, analytics, AI search visibility, or content development. The goal is not simply producing more content. It is increasing what marketers can accomplish without losing the judgment, voice, and differentiation that make the work valuable.
Sales teams might work on account research, territory planning, prospect prioritization, personalized outreach, call preparation, follow-up, proposal development, or role-play. The opportunity is often to reduce the work surrounding customer engagement so salespeople can spend more time in it.
Market research teams might use Labs for research design, literature review, screeners, discussion guides, qualitative coding, quantitative analysis, synthesis, and reporting. The goal is to move faster while keeping researchers responsible for interpretation, validation, probing, and final judgment.
Operations teams might focus on SOPs, recurring reporting, vendor evaluation, information synthesis, documentation, workflow automation, or administrative processes. The opportunity often starts with a repetitive task and ends with redesigning what happens around it.
Finance teams might work on budgeting, forecasting, financial reporting, expense analysis, scenario planning, or preparing information for business decisions. The goal is to spend less time gathering and organizing information and more time understanding what the numbers mean and helping the business decide what to do next.
Learning and development teams might work on course design, exercises, assessments, feedback, content adaptation, facilitation preparation, and course administration. The goal is to create more capacity for teaching, coaching, discussion, and meaningful feedback.
Other functions face the same underlying question:
What can AI now do, and what should that change about the work?
We build Labs around that question.
What Makes Us Different
Research-Led Work Redesign
Our work is backed by several years of research into understanding how real world organizations adopt AI in meaningful ways. We understand not just the tech behind Ai, but how real organizations actually adopt it, resist it, and scale the use of AI.
What This Means for You:
You get a plan grounded in evidence, not guesswork or hype.
Built for B2B
We focus exclusively on B2B organizations, where buying cycles are complex, workflows are cross-functional, and the stakes are high. We understand the realities of coordinating across product, marketing, IT, ops, sales, and finance. Agentic AI in B2B contexts requires particular care. Autonomous systems operating across sales, finance, and operations carry risks that consumer-facing deployments simply don’t.
What This Means for You:
Your plan for AI is tailored to B2B realities, not repurposed from consumer or generic playbooks.
Integrated with Training, Change Management, and Market Insight
We do more than set forth a plan. We connect your AI vision to practical enablement: team training, change management, and ongoing market insight as to what’s possible with AI. You don’t need one firm for research, another for training, and another for transformation when you are trying to figure out what’s “next” with AI for your org. That includes preparing your teams not just for the AI tools they’re using today, but for the agentic systems that are increasingly entering the enterprise.
What This Means for You:
You get a unified approach from insight to execution, so initiatives reinforce each other instead of fragmenting.
Guided by Fluid Intelligence®
Our proprietary Fluid Intelligence® model is a human-centered approach to AI direction. It was built for exactly this moment, when AI is no longer just responding to humans but acting on their behalf. Fluid Intelligence® ensures that human judgment stays at the center of agentic AI deployments, not as an afterthought but as a design principle.
What This Means for You:
Your people stay in control. AI becomes a capability you direct, not a force that dictates how you work.
