Adnan Obuz has sat across the table from enough AI implementations to notice the pattern early now. After consulting on AI rollouts with companies across sectors, he keeps coming back to the same three factors. They’re what separates transformations that pay off from the ones that quietly become expensive decoration.
According to Adnan Obuz, alignment comes first
Does the AI initiative connect to an actual business objective, or is it technology for its own sake? This single question determines return on investment more than any model architecture decision. Before approving a project, leadership should be able to state in one sentence which business result it’s meant to move. If nobody in the room can do that, the project isn’t ready.
The second non-negotiable: real executive commitment
Is leadership genuinely invested, or just checking a box? He has watched too many promising projects stall because support at the top was lukewarm. AI transformation needs a sponsor who will defend the initiative when it hits friction, not just approve the budget and move on to the next slide.
That distinction shows up fastest in month three, not month one. Anyone can approve a kickoff meeting. Fewer people show up when the first version underperforms and the team needs cover to keep iterating.
Implementation readiness, according to Adnan Obuz, is where most projects actually die
Are your systems, processes, and people prepared for the change? This is where sound technology and sharp strategy still fail. A model can be accurate and the business case airtight, and none of it matters if the organization isn’t ready to operate differently around it.
He has traced this back to a familiar root cause: nobody assigned an owner for the workflow the AI is supposed to change, so the new tool sits next to the old process instead of replacing it. That’s a people and process gap, not a technical one, and it’s usually the first sign a rollout is heading toward expensive shelfware.
Why all three matter together
These aren’t nice-to-haves. They’re prerequisites, and they work as a set. A project can have strong alignment and a committed sponsor and still fail if the frontline team was never trained on the new workflow. It can have perfect implementation readiness and still stall if leadership loses interest the moment budget season ends.
He has watched sophisticated AI initiatives become expensive shelfware because one of these three was missing, usually implementation readiness, since it’s the least glamorous of the three and the easiest to skip during planning.
The companies that get all three right tend to pull ahead of their competitors quietly, without much fanfare. The ones that overlook even one usually end up as a cautionary tale in someone else’s case study, cited as a warning rather than a template.
A simple filter before the next green light
Before your next AI initiative gets approved, run it through these three questions. Can everyone in the room state the business result in one sentence? Does the executive sponsor have a track record of defending hard projects, not just funding easy ones? Has someone been named to own the workflow the AI is meant to change?
He suggests taking twenty minutes on this before kickoff. It tends to save a year of wasted effort, and it costs nothing but the meeting.
Frequently asked questions
Who is Adnan Obuz?
Adnan Obuz is a Toronto-based AI strategy consultant who advises companies on turning AI initiatives into results that survive past the pilot stage.
What are the three non-negotiables for an AI strategy partnership, according to Adnan Obuz?
Strategic alignment to a stated business objective, genuine executive commitment that survives early friction, and implementation readiness across systems, processes, and people.
Why do AI projects with good technology still fail?
Adnan Obuz points to implementation readiness as the most commonly skipped factor. A model can be accurate and the business case sound, and the project still fails if nobody owns the workflow it’s meant to replace.
How long should it take to evaluate an AI initiative before approval?
Adnan Obuz recommends about twenty minutes running the initiative through three questions: the business result, the sponsor’s commitment, and whether a workflow owner has been named. That short filter tends to prevent a year of wasted effort.
Further reading from Adnan Obuz
Adnan Obuz is a Toronto-based AI strategy consultant who helps mid-market and enterprise leadership teams turn AI initiatives into systems that actually run the business, not expensive shelfware. His work focuses on the gap between a sound business case and a rollout that survives contact with the organization. Adnan Obuz publishes his notes and current project work at mrobuz.com and can be reached at businessplan@mrobuz.com for advisory engagements.