Outcomes, not output

Output is easy to produce and almost always looks good: tickets summarised, documents generated, seats licensed, agents deployed. It is what pilots report. It is not what a CFO recognises.

OG judges every AI initiative on a ladder of three tiers. Output is activity. Outcome is a business number, measured against a baseline taken before you started. Impact is what survives the next budget cycle: headcount reallocated, a contract cancelled, a margin point defended in the audited accounts.

If your AI reporting stops at output, spending more will only buy you more output.

The talk always arrives years before the value. In a July 2026 study, BCG found that only 6% of large US public companies qualify as real AI adoption leaders.

The market pays a little for the story and a lot for the outcome.

• Capture the baseline before you start. No baseline, no outcome.
• Name, in advance, the outcome metric each funded initiative will move and the impact line it will touch.
• Find where value leaks: promised, piloted, in production, still running eighteen months later.
• Fund the 70% nobody wants to fund: process, decision rights, skills and change.
• Be loose on the forecast, strict on the ladder.

Across HP and DXC, OG helped run an automation estate of more than 3,000 bots. The work only counted when it showed up in the numbers: his work delivered more than $100M of business impact. That is the lens he brings to every advisory engagement. How he works.