From disconnected projects to stalled AI pilots, Dr. Brian Massey examines the choices behind innovation. But his reflections raise a wider question for Ireland: are we investing in the capabilities that make the rest of our investment work? This article forms part of No Shortcuts, IMI’s limited content series exploring the capabilities organisations depend on most—and why they cannot be developed overnight.
Dr. Brian Massey has a straightforward test for organisations that believe their strategy and innovation are aligned.
“Pull out a list of strategic priorities on one side and pull out the project register on the other,” he says. Then ask: “Do these two line up?”
Massey notes that some divergence is natural, but “if those two pieces are not communicating to one another in any meaningful way, then you know you’ve got a big problem.”
For Massey, Programme Director for IMI’s Professional Diploma in Strategy and Innovation, this comparison exposes the distance between the direction an organisation endorses versus the commitments it actually makes.
Firstly, for example, a leadership team can agree on its priorities while continuing to authorise projects that pull it elsewhere. Secondly, even when the projects support the stated strategy, has the organisation invested in what they need to succeed?
This question runs through Massey’s conversation for IMI’s No Shortcuts series—and extends well beyond an individual business or organisation.
Your project register may reveal more than your strategy deck
“Probably the biggest misconception people have about strategy is that it’s a plan,” says Massey.
Of course, a plan matters. But strategy is something else entirely.
“It’s a process that leaders engage in over time with their teams, with their colleagues,” he says. Yes, the initial ingredients like planning are necessary, “but there’s so much more that comes after.”
Massey describes strategy as an ongoing process of decision-making, implementation and reassessment—not something completed when the document is approved.
In fact, research on resource allocation shows that everyday funding decisions can reinforce—or undermine—a company’s announced strategy. Massey’s project-register test both makes this visible and challenges the assumption that a busy innovation portfolio necessarily signals progress.
“Good innovation is creativity and invention that’s deployed to solve real problems,” he says.
Those problems may belong to external customers or to people within the organisation whose work needs to improve. Massey finds what is often called “innovation theatre” particularly disheartening because the effort behind it can be entirely genuine, yet it’s still people investing energy and passion in projects disconnected from the problems they should address.
That is different from dismissing experimentation, and Massey explicitly recognises a place for research laboratories and open-ended exploration. But the issue is whether the organisation understands the purpose of what it is supporting.
An exploratory project need not promise an immediate commercial return, but attaching “strategic” to an initiative should require more than enthusiasm.
If someone could see only the work your organisation funds, what would they conclude it was trying to become?
Yesterday’s strengths can narrow tomorrow’s choices
Even a well-aligned portfolio can point in the wrong direction.
Massey notes that too many leaders fall into the trap of building the future around the capabilities that explain past success.
“We tend to think about the capabilities that have helped us succeed in the past and that we’ve built our organisation on,” he says. “And we think, OK, that’s what we have to build our strategy around going forward.
“(But instead we should be asking) what capabilities do we need to add to that portfolio to help us be the sort of organisation we need to be to win in 2035, not (what helped us win in) 2025?”
Dorothy Leonard-Barton’s research on core capabilities and core rigidities is useful here, whereby the skills, systems and values that enable an organisation to perform can also inhibit innovation, because what the organisation does well can shape what it is willing to consider.
Instead, Massey notes, leaders need to look beyond their own performance history and give attention to the external environment.
“Very often there’s companies out there who you wouldn’t consider traditional competitors. But as technologies change, you find all of a sudden you’re playing in the same space.”
An unfamiliar opportunity may look unattractive because it offers little value—or because the organisation has never developed the ability to pursue it.
Those are different judgements.
“Thinking about the sort of capabilities that need to be added over time is a continuous question,” says Massey.
Of course, existing strengths remain valuable. But the danger is allowing them to determine the limits of the organisation’s ambition.
Financial discipline should expose assumptions, not disguise them
In terms of practical allocation, organisations can generate more possibilities than they can realistically or responsibly pursue.
Massey sees this in AI, with large organisations maintaining registers of use cases “far more than they could ever experiment with, never mind scale up.”
Connecting those proposals to business needs and assessing potential returns helps distinguish meaningful opportunities from “passion projects masquerading as innovation.”
So: how should leaders assess an opportunity when much of its value remains uncertain?
Consider two proposals. One improves an established process, with costs and benefits that are relatively easy to estimate. The other explores a new market or capability, where customer behaviour and delivery costs remain uncertain and important assumptions remain untested.
The first may deserve investment. But a more confident forecast does not automatically make it the better strategic choice.
The discovery-driven planning approach developed by Rita McGrath and Ian MacMillan addresses this problem by making uncertainty explicit. Managers identify the assumptions on which an opportunity depends and organise learning around them before committing substantial resources.
This offers a way to combine Massey’s demand for commercial relevance with the room he allows for exploration.
Applied to Massey’s argument, financial discipline should expose the assumptions behind an idea. What must be true for this idea to create value? What evidence would justify the next commitment? What would persuade the organisation to stop?
An experiment can be accountable for what it teaches as well as what it produces—and without pretending its outcome is already known. In fact, a standalone business case can also miss value created elsewhere in the portfolio, while an investment that looks modest in isolation may be the prerequisite for several others to succeed.
The pilot worked. Why didn’t the organisation change?
Massey’s Financial Services advisory work highlights the the distance between demonstrating a technology and incorporating it into everyday operations.
“I’ve seen quite a few organisations in FS struggle with scaling up these AI use cases and innovations because there’s quite significant cultural or behavioural barriers around getting people to take on these technologies and implement them and use them in processes.”
Sometimes the difficulty starts with competing directions.
“If your AI strategy is out of sync with the overarching corporate strategy, you’re going to have a divergence and kind of pulling in different directions,” he says, which makes innovation difficult to sustain outside the protected environment in which it was developed.
A successful demonstration can also leave important questions unanswered. Who owns the new process? Whose responsibilities change? What existing work will stop? What would give people confidence to use the innovation in consequential decisions?
These are not uniquely AI problems. A 2001 study of 16 hospitals adopting a new cardiac-surgery technology found striking differences in implementation despite all having highly regarded cardiac departments. Successful adopters followed different team-learning processes, involving preparation, opportunities to practise new behaviours and reflection. Introducing the technology required changes in how people worked together.
“The organisation has to be innovation-ready as well,” says Massey, identifying three connected requirements: strategic alignment, projects tied to real business problems, and an organisational culture capable of incorporating them.
Not every pilot should scale. In fact, discovering that an idea is unsuitable can be a useful result. But demonstrating that something works is only part of establishing whether the organisation can make it valuable. A pilot should not be declared a business success while the condition needed to use it remain untested.
What would an innovation-ready Ireland look like?
Massey’s observation raises a wider question for Ireland: how much of the innovation located here becomes capability distributed across the economy?
The OECD’s 2026 assessment of Ireland identifies business research and development as largely driven by foreign-owned multinationals. It recommends stronger participation by domestic firms in multinational innovation networks, alongside better access to applied research through connections with universities.
There is also a marked difference in technology adoption. CSO data for 2025 show that 58% of large enterprises used AI, compared with just over 17% of small enterprises. Adoption does not establish the value generated, and businesses have different needs. But national progress clearly needs to be examined beyond the most advanced adopters.
The opportunity is to build more capability around Ireland’s existing strengths: suppliers able to participate in sophisticated value chains, businesses able to apply research, and managers able to redesign work around new technology.
But an uncomfortable investment problem sits underneath this.
Research by Erik Brynjolfsson, Daniel Rock and Chad Syverson on the Productivity J-Curve explains how technologies such as AI require complementary investments in processes, business models and human capital. Much of that work is intangible, takes time and can be poorly captured in conventional measures of productivity.
Consider an organisation funding several AI pilots, all dependent on better data or redesigned workflows. Each pilot has a sponsor and an expected return. The shared groundwork may sit in somebody else’s budget, with benefits spread across several initiatives.
The portfolio can look attractive while its common dependencies remain unresolved.
The most strategically important investment may be the one that makes several other investments valuable.
At national level, businesses, research institutions, skills providers and public agencies may each have defensible priorities while shared needs remain underfunded. Where the cost falls on one organisation but the benefits spread across several, the case for collective investment can be stronger than the incentive for any one participant to act. Everyone can have a strategy while the capabilities they collectively depend on remain nobody’s strategic priority.
That extends Massey’s project-register test. Alongside asking whether initiatives support the strategy, leaders need to ask: what else must work for these investments to create value—and who is responsible for making that happen?
AI can improve the output while leaving the organisation more dependent
Questions about capability also apply to the strategic work itself.
Asked whether AI improves strategy or creates new risks, Massey notes “The answer is both. We have to recognise both sides to it.”
While Massey recognises AI’s usefulness for processing large amounts of data and supporting scenario planning, his concern is what happens when assistance becomes dependence.
“The more you get into the habit of outsourcing that knowledge, the more you’re essentially losing an organisational capability that’s really, really crucial to an organisation.”
He compares this with becoming dependent on consultants for a particular function. That may be a legitimate choice, but leaders need to understand what they are relinquishing and what capability they are choosing not to retain.
“Maybe you’re making the explicit decision that we don’t want to have that capability in-house, and that’s fine, but you need to be very, very careful about what you do that with.
“And maybe your capability around strategy is not something to outsource to others.”
In an experiment involving 758 BCG consultants using GPT-4, AI-assisted participants completed tasks within the system’s capabilities around 25% faster. But on one task beyond those capabilities, however, they were 19 percentage points less likely to produce a correct solution. The experiment tested task performance, not long-term skill loss, but demonstrates the importance of understanding where assistance helps and where it misleads.
Massey’s concern goes further: what capability remains inside the organisation after the strategy document has been produced? Can the team explain its choices, challenge the assumptions and recognise when circumstances require a different approach?
“These great technologies are fantastic tools,” he says, but the person using them needs to know “that the process is being run well” and have confidence in the output.
That makes external expertise and technology strategic choices in their own right, with their value lying in what they help an organisation learn, as well as what they help it produce.
However, long-term questions remain around whether each cycle of AI-assisted work leaves the organisation—and its people—better able to think strategically or more dependent on something it cannot adequately interrogate.
Strategy is a capability that needs practice
Massey describes strategy as “an explicit decision craft,” or a process involving engagement, choices and a destination.
His examples show why craft, and not just output, matters. A portfolio can drift away from strategic priorities or a promising innovation can stall because its dependencies were ignored or an impressive analysis can leave the team using it no better equipped to make its next decision—all required people capable of examining how one decision affects the next.
Learning the tools, like AI, is only the beginning.
“You understand the tools and then you build competence in using them,” he says. “You do that through iteration and practice and getting the feedback.
“Having a team of individuals that bring those capabilities together and are able to engage in a good strategy process over time is one of the most powerful capabilities an organisation can ever have.”
For Ireland, what do today’s investments leave businesses, people and institutions better able to do tomorrow?
Whereas for an individual leadership team, the starting point can be as practical as placing its priorities beside its project register.
Finding a mismatch is the beginning of a decision: change the projects, reconsider the strategy, or investigate what the divergence is telling you. Finding alignment should prompt the next question: have we built the capabilities on which these commitments depend?
The future an organisation pursues will be shaped by both decisions.
And maybe a country too.
This article forms part of No Shortcuts, IMI’s series of faculty conversations and written deep dives exploring the capabilities that make organisations work.
Ready to challenge the assumptions shaping your organisation’s future? Explore IMI’s Professional Diploma in Strategy and Innovation with Programme Director Brian Massey.
