Most AI training creates awareness, not change. Teams are shown what AI Productivity tools can do. Sessions feel useful, energy is high and feedback is positive. Then they return to work.

Their tasks are different to the examples they were shown and often more complex. What felt clear in the room becomes difficult to apply in real life. Confidence drops, habits remain and very little actually changes.

This happens when training focuses on tools instead of the task level work teams are responsible for delivering.

Our work is not training in the traditional sense. It is upskilling.

That means deliberately changing how teams approach their real tasks using AI, so improvements remain after the sessions end and learners are back at their desks.

For teams and departments, this gap compounds. Inconsistent usage, uneven confidence and fragmented practices quietly undermine productivity and quality.

How Our Team Upskilling Approach Works

Our approach is deliberately designed to change how teams work, not just what they know.

We focus at the task level because this is where AI productivity tools either create value or fail completely. If training does not connect directly to the work teams are responsible for delivering, improvement will not hold.

We start by identifying the real tasks teams are accountable for. This is done through structured pre-engagement and validation, not assumptions.

Those tasks are then rebuilt as hands-on, AI-supported workflows. Teams learn how to complete their work using AI, rather than learning tools and being left to translate that learning back into their jobs.

This is the structure that makes the difference.

We Identify The Tasks That Matter

Before training begins, we engage with learners to identify the daily and weekly tasks that slow teams down, create bottlenecks or consume disproportionate time.

These tasks are validated through engagement, not assumption, creating a clear picture of where AI can genuinely help. The workflow becomes the unit of learning, not the tool.

Tasks Rebuilt As Workflows

Learner tasks we have identified are assessed for suitability and then rebuilt as clear workflows in AI tools like Microsoft Copilot, OpenAI ChatGPT and Google Gemini. We focus on how learners complete tasks using AI, rather than how to use tools in isolation.

This is how learning turns into habit, not intention.

Experience Through Learning

Teams learn using their own tasks during training.

This means confidence is built in the room, not expected later. People return to work already knowing how to apply what they have learned.

Training Courses

Koshima's training courses create fast, focused change by improving how specific tasks and activities are performed. We focus at the task level, this is where tools add value and where we work.

This approach provides a strong injection of new ways of working by teaching teams how to complete their tasks using AI.