Why Accountability Outperforms Effort

Effort is not a delivery strategy. Ownership is.

Most programmes I have worked on had no shortage of people working hard. Long hours, packed schedules, status updates flying in every direction. And yet the programme was still late, the decisions were still slow, and no one could tell you clearly who was responsible for what.

That is the accountability gap. And it costs more than most leaders are willing to admit.

Busyness has become a proxy for commitment

Research cited in Harvard Business Review shows that when organisations reward primarily how long and how hard people work, productivity and efficiency actually drop. Yet in most transformation programmes, that is exactly the signal being read. The person always in every meeting, always visibly grinding, is perceived as a high performer. The person who delivers cleanly and logs off on time is questioned.

Researchers at Columbia found that busyness has shifted from a symptom of stress to a status symbol, particularly in knowledge-intensive economies where being in high demand signals value. Delivery environments have absorbed this norm entirely. We have normalised the theatre of effort.

The result is that accountability gets quietly displaced. No one is responsible for the outcome. Everyone is responsible for their piece of the process.

What accountability actually requires

Accountability is not about blame. It is about clarity.

It requires someone to say: this outcome is mine. Not this workstream, not these deliverables, not this sprint. The outcome. If it does not land, I own that.

A 2022 meta-analysis published in Frontiers in Psychology found that for complex tasks, outcome-based accountability produces meaningfully better performance than process-focused accountability. Complex transformation programmes are precisely the environment where this distinction matters most. When accountability is anchored to process rather than outcome, people can be completely compliant and still not deliver.

This is what I see in programme governance that has gone wrong. Beautifully maintained RAID logs. Immaculate status reports. And a programme that is fundamentally off track because no one owned the outcome of the thing that actually mattered.

The leader's role in this

Accountability does not emerge on its own. It has to be established, named, and protected.

That means being specific about who owns what, not in terms of tasks but in terms of results. It means creating the conditions where someone can raise their hand early and say this is not going to land, without that being a career-limiting move. Research from McKinsey highlights that in high-performing teams, people feel both able and expected to speak up, and that this is a defining characteristic of teams capable of handling complex work.

It also means not rewarding effort as a substitute for delivery. When you praise visible busyness, you signal that activity is the measure. You will get more of it.

AI makes this more urgent, not less

There is a version of this conversation that is becoming unavoidable on programmes right now.

AI is being introduced into workflows at pace. It is compressing timelines, automating outputs, and cutting the visible effort required to produce something. Which means the busyness signal, already unreliable, is becoming even harder to read. A team can now produce more with less effort, which sounds like a good thing, and often is. But it creates a new risk that very few programmes are designed to handle.

As AI takes on more business-critical tasks, the assumption that machines can shoulder responsibility is falling apart quickly. Real accountability still sits with humans, and successful AI adoption depends on leadership defining objectives, managing risks, and taking ownership when things go wrong.

AI does not hold outcomes. It does not own decisions. It cannot be accountable for what a programme delivers. A 2024 Gartner survey found that while 80% of large organisations claim to have AI governance initiatives, fewer than half can demonstrate measurable maturity, with most unable to connect policy to practice. That gap is not a technology problem. It is an accountability problem dressed up as a governance one.

Which means if your programme flows were not built with clear human accountability before AI entered them, they are definitely not built for it now. AI will reduce the effort. It will not replace the owner.

The question worth asking before the next phase of your programme is not what AI can automate. It is who is accountable for what it produces.

References

Waytz, A. (2023). Beware a Culture of Busyness. Harvard Business Review, March–April 2023.

Bellezza, S., Paharia, N., & Keinan, A. Research summarised in: Busyness is Bad for Business. Science House.

Sharon, I., Drach-Zahavy, A., & Srulovici, E. (2022). The Effect of Outcome vs. Process Accountability-Focus on Performance: A Meta-Analysis. Frontiers in Psychology.

McKinsey & Company research summarised in: Psychological Safety at Work. Berkeley Executive Education.

Franco, A. (2025). The AI Accountability Gap. UX Magazine.

Gupta, A. (2025). Building a Practical Framework for AI Governance Maturity in the Enterprise. Dataversity.