The new AI-Native sprint series develops capabilities through real organizational cases. It begins by identifying the organization's existing capabilities and needs, then explores where AI could contribute to the work.
At the start of each sprint, we work on the organization's strategic need, the problem it wants to solve, and the human capabilities that problem requires. Before moving into off-the-shelf tool training, the team reframes the problem, tests assumptions, and develops different paths to a solution. For me, the starting point is the organization's ability to clearly articulate its own agenda. This inquiry also establishes where AI could be useful.
Why are we still unable to solve this chronic problem? Where should we invest in AI to get the best ROI? Is this innovation idea actually feasible? Which new areas of value should we pursue in the coming period? These questions can give rise to cases for the sprints. Once a real, strategic case has been selected, the team looks beyond the symptom and defines the outcome it wants to change.
As the team examines its own way of thinking and the capabilities it needs, it develops options using problem-solving and creativity methods. The human–AI working model is tested on the same case. At the end of each sprint, alongside a list of ideas, the team has a clarified problem statement, a picture of its capabilities, and a tested value hypothesis. Management can draw on these findings when deciding whether to continue the work, invest, or scale.
Ask yourself
- What is the underlying problem limiting us today?
- Which human capabilities does this problem require?
- What strategic value must the AI investment demonstrate?
