tgroenwals shared this post · 15h ago

Rob Llewellyn

19h ago · archived 15h ago

Most AI programmes never reach transformation.
They stop at Level 1.

Everyone wants AI to deliver business value.

But many organisations are measuring success
by faster tasks and lower costs.
They stay at Level 1.

That’s not transformation.
It’s improvement.

AI creates value at three different levels.

Level 1 improves tasks.
People work faster and costs fall.
But the business stays largely the same.

There’s nothing wrong with Level 1.
It's useful, and every organisation
should look for quick wins.

The problem is believing that’s enough.
Believing it’s transformation.

Paul Souhuwat Many organizations mistake efficiency for transformation. Efficiency helps organizations do the same work better.
Transformation changes what the organization is capable of becoming.

The missing layer is often decision architecture. Before AI reshapes the business model, it must first reshape how the enterprise senses, decides, and coordinates. That's where enduring advantage begins.

Tim Hughes Rob Llewellyn Strong perspective, thank you. I'd go one step further: transformation isn't created by AI itself—it's created by the better decisions AI enables. The organisations that outperform will redesign how decisions are made for customers, colleagues and the business, not just how work gets done.

tgroenwals shared this post · 3d ago

Rob Llewellyn

4d ago · archived 3d ago

Your project closed green.
So why does nothing feel different?

Most leaders have lived this.

The milestones hit. The budget held.
The steering committee applauded.
Yet nothing fundamental changed in the business.

Here's the uncomfortable truth.
You delivered exactly what
you were asked to deliver.

Projects deliver outputs.
Outcomes and benefits only arrive
when the business changes how it works.

That's not my definition.
PRINCE2 and the PMBOK both say it.

And there's a deeper pattern.
Most projects, not all, are focused on optimisation.
They make the existing business more efficient.

Rob Turner, MBA This is the pattern I see repeatedly in ServiceNow implementations. The platform goes live on time and on budget, the project closes green, and within six months the CMDB data is rotting because nobody built a permanent governance structure to maintain it. Every process that depends on that data — incident, problem, change, impact analysis — is now operating on assumptions instead of facts. The project delivered the output. Nobody owned the ongoing capability. Your point about permanent transformation structures is the answer, but in my experience the resistance isn't intellectual — leaders agree with it in the room. The resistance is budgetary. Permanent structures require permanent headcount, and most organizations won't fund a transformation function the way they fund IT or finance. So the work gets re-packaged as the next project, the next program, and the cycle restarts.

Rob Llewellyn Author That’s the challenge Rob. Without permanent ownership, the cycle simply repeats.

tgroenwals shared this post · Jun 25

Rob Llewellyn

Jun 25 · archived Jun 25

Two firms have access to the same AI.
By 2030, their positions will have diverged.

Same AI. Two different futures.

Most firms point AI at the present.
They apply it to what already exists
then call it transformation.

But the truth is, it's optimisation.
Valuable, yes.
But it's not transformation.

Productivity. Efficiency. Automation.
All real. All worth having. All challenging.

But optimisation has a ceiling.
It makes the current model better, not different.
The game stays the same.

And it follows a familiar curve.
Refine. Plateau. Diminishing returns.

Rizwan Tufail A company funding only optimization may show better dashboards for a period. The harder cost shows later through weaker capability, slower learning, and reduced strategic range.

Khubaib Rasheed Rob Llewellyn Optimisation has a ceiling. It makes the current model better, not different. The trap is that on a dashboard it looks like progress, so the budget commits to defending a model AI is already replacing. The companies that win run both curves deliberately: fund today's model while building tomorrow's capability.
Which curve is your board actually funding?

tgroenwals shared this post · Jun 6

Rob Llewellyn

Jun 4 · archived Jun 4

Two firms have access to the same AI.
By 2030, only one still exists.

Most firms point AI at the present.
They bolt it onto what already exists.
Then they call that transformation.

It isn't transformation.
It's optimisation wearing a fancier label.
Useful, but anchored to the past.

Productivity. Efficiency. Automation.
All real. All worth having.

But none of it changes the game.
It's not a genuine transformation of the business.

Optimisation follows a familiar curve.
Refine. Plateau. Irrelevance.
Small gains, then diminishing returns.

1 / 4

Tejas Sompura Strong distinction.
The companies that win with AI probably won't be the ones that automate the most work.
They'll be the ones who use automation to buy time, capital, and attention to build new value creation models. Jun 4

Jimmy Sandy Optimizing what exists and building what comes next are two different jobs. The ones who only do the first are funding a model they're not replacing. Jun 4

tgroenwals shared this post · May 11

Rob Llewellyn

May 11 · archived May 11

Govern transformation like a project.
You’ll get project outputs.

A CEO said this to me recently.
“Rob, we’re spending millions each month,
but margin hasn’t moved in two years.”

The room full of senior leaders went still.
The CFO looked up at the on-screen dashboard.
Every status box was green.

She turned to the project sponsor and said:
"...and so how has this changed our numbers?"

Projects were completing on schedule.
Teams were celebrating milestones.
The business had little to show for it.

That comment stayed with me.
Because it’s a common pattern
in medium and large organisations.

1 / 4

Arron Rouse Obviously am biased but there are two things that seem to be missing from your story. First is something I see most people Change/Transformation miss: there's no mention of what's going on outside the organisation. The main point of doing a transformation has to be enabling the organisation to do new things in its markets. Or at least do the old things cheaper/better.

Second, an outcome-focussed pattern like STORM should make sure you are delivering on the objectives of the transformation. If the intent is to capture 10% more of a market, it's superb to be delivering projects/programmes on time, on spec and on budget... but do they lead to the desired effect in the market?

With apologies if these kinds of things were in your previous posts, haven't had much time to read over the last few weeks. May 11

Govert Doedijns Rob Llewellyn, you consistently puts the finger on one of the biggest transformation traps in larger organisations: confusing delivery activity with enterprise change.
I see this especially in AI and transformation programmes today. Dashboards remain green, milestones are achieved, budgets are consumed, yet the operating model underneath barely changes.
Because projects optimise for completion.Transformation optimises for new organisational capability.
That is a fundamentally different governance challenge.
The important shift in your post is the move from governing tasks and timelines toward governing learning, adaptation, capability, and measurable business outcomes.
“Scaffolding isn’t the building” is a particularly strong way to frame it. May 11

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