AI Does Not Need Its Own Roadmap

by Ferne Eliz King | Oct 29, 2026 | taking action

Roadmaps – seperate or together?

In 2026, in a meeting room with a firm’s CEO, CTO and product owner, I looked at two roadmaps.

One was the enterprise roadmap, newly created. The other was a separate map for AI, created a few months earlier.

We brought the AI work into the enterprise roadmap. It opened up a question: in what sequence are these outcomes best to land to deliver the strategy? It highlighted what had to happen before and concurrently to the AI and growth outcomes could be achieved. In this case: capability uplift and data management decisions.

We could see the priorities, the sequence, and whether we had the capacity and capability to deliver. The decisions got sharper.

I’m sharing this because the separate map made AI feel apart from the people, process, technology and data. On one roadmap, it was simply part of getting the outcomes.

Imagine if every strategic outcome, AI included, sat on one roadmap.

“Where are we up to with AI?” is the wrong first question

Mid-tier firms, private wealth, large organisations: they all ask it. I often say that the quality of the questions you ask determines the quality of the answers you get.

The stronger question: what does our strategic pathway look like, and where are the risks, constraints and outcomes?

AI belongs inside that answer, not beside it as a separate technology roadmap. By one roadmap I mean one view of every outcome the strategy needs, the work to deliver it across people, process, data and technology, and the order it happens in. Put everything on it and you see what competes for the same money, people and attention. It shows which decisions need to be made.

Mik Kersten’s Outcome Roadmap works the same way: work sequenced against objectives. AI is part of that sequence, not alongside it. Experienced strategic portfolio managers can build this roadmap quickly.

Curiosity is a key ingredient

AI gives answers quickly. Curiosity decides which questions are worth asking. The “what else?” in that meeting room came from curiosity. It’s a skill you can build, and in a fast-moving portfolio it matters more, not less. Now more than ever, we need to avoid acting on assumptions.

What this means for your PMO, TMO or VMO

Whatever you call the office that runs your portfolio, its service has to keep improving. As strategy shifts, so does the service. It can’t wait for strategy to be settled before it acts.

Its job is to give clarity on:

the decisions to be made, and when
how success will be measured
the constraints, and how to manage them to inform priority and sequence
the most economical path to an outcome that sticks
the risks and capabilities needed

Think of the Formula One Pit Wall. When the weather turns or the safety car comes out, it re-plans while the cars are still moving. Your office keeps pace in the same way, with three lenses: where you want to be, where you are today, and what the past has taught you.

Five questions to ask your business this week

Which strategic outcome does each AI use serve? (An AI use is anywhere AI is used or planned: a chatbot, an automated report, an agent.)
Does our AI work rank against everything else on the roadmap, or is it running on its own?
Where are the real constraints? Speed up a step that isn’t the bottleneck and you only move the pile.
What are the risks, and who owns each one?
What will we stop doing to make room?

Where is your organisation on the pathway?

Nataliya Shalygina of LeadMark.AI and I have written a free AI question guide for PMO, TMO and VMO leaders, and the executives accountable for them: seven phases, from starting out to banking value, with quality questions for each. The answers help you decide what goes onto your one roadmap, and where.

Download it here: Questions to ask relating to AI from a TMO, PMO, VMO lens

Next week: the operating model of a PMO, TMO or VMO, and the capabilities to build as AI speeds up outputs. Know what informs an operating model. The start point is not your current organisational structure.

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Track first, engine later.

Ferne Eliz King helps executive teams and boards turn strategic complexity into clarity, and clarity into results. Get in touch, or subscribe to the newsletter for more.

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Reflecting on the Slow Days

by Ferne Eliz King | Oct 21, 2026 | taking action

AI Has Sped Up the Ideas. Has Your Portfolio Kept Up?

In 2018, in Melbourne, I was the portfolio delivery director on one of the largest transformations NAB had run: Right Customer, Right Banker.

We sat in front of the data models for weeks. Around mid-afternoon, late in a particularly long week, the Senior Business Lead said, “We’ve cracked it. We’ve got the ratios right.”

That was the moment we understood how to solve the problem we’d been given. Then we worked out how to show the banker and customer ratios so people could see them.

Last month I watched a similar piece of work finish before my coffee was cold. The answer was good. But nobody had to work out the problem first. Nobody had to fix and refix the assumptions, or ask why the answer didn’t feel right.

I’m sharing this because those slow days were doing something for us. That’s where the thinking happened, and where we collaborated. Now ideas, experiments and outputs reach portfolio leaders faster than we’ve ever known.

Imagine if the speed was only half the story.

What Mik Kersten says

Mik Kersten, author of Output to Outcome, eloquently describes this shift. Once AI removes output as the limiting factor, the constraint moves to how an organisation is structured and run. His warning: “Either we find a scalable way to manage AI, or it will manage us.”

He wrote the book himself, every word, with no AI for the ideas or the writing, because the process helped him slow down and think. That’s what our slow days did.

I keep coming back to Mik because he puts into words what experienced portfolio leaders do by instinct. Across 50+ projects I’ve been involved in, one habit has separated the good from the rest: look at the constraints and work with them, not around them. Start from the future and work backwards. Together they tell you how fast you can really go.

AI is an opportunity. It’s also a reason not to take our eyes off the constraints. Identify them. Decide which can be fixed. Plan around the ones that can’t. Use that to prioritise which ideas are ready to become experiments: the ones whose constraints are gone or managed.

Where energy comes in

Portfolios need energy. People who try things, speak up, are heard, and stop early when it isn’t working. AI makes trying cheaper, and sends more ideas to our desks every day, every week. Silent voices kill a portfolio’s outcomes and its speed. What are you doing to make sure voices are heard and experiments can happen? And do we celebrate the idea that works, and what we learned from the ones we stopped?

Four questions for your own practice

Is our calendar built for this pace? I favour one rhythm across the year, quarter, month and week, so teams can reprioritise without a new meeting for every idea. When things get really bumpy, go to a daily or weekly cadence for a while to deal with the crisis – then back to your regular cadence.
What did the slow work give us that we need to keep? A pause. A sketch. A conversation. Have you built thinking time into your week?
New questions. Not “what did we produce?” but “what changed because of it?”
How we run the portfolio. Do we track how long ideas wait, not only what gets done? Is your operating model, whether PMO or VMO, set up for this pace?

Our role in Portfolio Director or Portfolio Manager hasn’t changed

Prioritise. Sequence. Know the constraints and the opportunities. Tie the choices back to the outcomes in the strategy. In Formula One terms, the Pit Wall doesn’t drive faster because the car got quicker. It decides when to pit, and what the race needs. It is accountable for decisions made at speed, knowing the constraints, with the podium in sight.

Try this

This week, ask your team: if ideas arrive three times as fast, what breaks first?