The AI value framework

What the framework is for

Most organizations arriving at AI have a long list of ideas and no way to compare them. The three paths give a common language for sorting that list, so a leadership team can see the shape of its own portfolio instead of arguing case by case.

We use it as the opening instrument in discovery work, and as the organizing structure in inspiration sessions and enablement programs.

The three paths

1. 1
   Boost productivity

   Perform tasks and workflows faster, at larger scale, higher quality, and lower cost. This is where most organizations start, because the workflows are already understood and the results are measurable within weeks. Typical work: marketing and content production, customer support, software development, operations, research and analysis, human resources.

2. 2
   Create value

   Build innovative solutions to accelerate time to value for your stakeholders. This path changes what customers receive, through AI embedded in products, services and experiences. It takes longer, it needs product ownership rather than functional ownership, and it is where competitive difference accumulates.

3. 3
   Disrupt models

   Challenge value chains, business models and modes of operation. This path asks what becomes possible, or indefensible, when intelligence is cheap. It carries the longest horizon and the highest variance, and it is the path organizations most often skip.

The portfolio point

The framework pays off in the mix. Organizations that stop at path one get real savings and no strategic position. Organizations that jump to path three without path one have no internal capability to execute with.

We look for a deliberate spread: near-term productivity work that funds and builds capability, measured bets on new value for stakeholders, and at least one structured exploration of how the model itself could change. The right proportions depend on your sector, your risk tolerance, and your culture. The wrong proportion is all of one.

Where each path is owned

Two questions before any of it

Two questions come before the framework, and they are the ones we ask first in discovery.

1. 1
   What are you trying to change?

   If there is no answer beyond doing something with AI, the portfolio conversation is premature.

2. 2
   Should this process exist in its current form at all?

   Delegating work to AI requires the process to be defined. Organizations that try find out how much of their complexity is accidental. Simplification is often the larger prize, and it does not require any AI to collect.

How we use it in engagements

1. 1
   Inspiration sessions

   The framework anchors the session, and participants place their own priorities against it before any tool is demonstrated.

2. 2
   Discovery and direction

   Each candidate use case is placed on a path, then scored, then compared within its path instead of against everything at once. The output is a prioritized portfolio with explicit criteria for what did not make the cut.

3. 3
   Implementation and adoption

   The path determines the delivery shape. Path one runs as enablement plus workflow redesign. Path two runs as product work. Path three runs as structured exploration with scenarios.