“Is your calendar a reflection of your priorities — or a record of what other people asked for?”
From More to Better
The productivity conversation has changed. For twenty years it was about doing more in less time. Cal Newport’s 2024 book Slow Productivity named the turn: the work that matters is not fast or fragmented. It’s deep, considered, and finished.
MIT Sloan Management Review and BCG’s 2024 research on AI-augmented work reached a parallel conclusion — leaders who use AI well don’t do more work, they do different work. The shallow tasks compress. The thinking expands.
Sources: Cal Newport, Slow Productivity (Portfolio, 2024); MIT Sloan Management Review and BCG, AI research (2024); Microsoft Work Trend Index (2025).
Three Principles of Slow Productivity
Newport’s 2024 update to his earlier work. Less is more, done properly.
Do Fewer Things
The number of parallel commitments is the silent killer of leadership quality. Reduce the count, raise the standard.
In practice: name your three real priorities this quarter. Push everything else out, down, or off.
Work at a Natural Pace
Sustainable effort beats frantic sprints. Seasons of intensity, followed by seasons of consolidation.
In practice: plan in weeks and quarters, not days. Build in recovery rather than collapsing into it.
Obsess Over Quality
The work you’re remembered for is the work you took seriously. Quality is its own productivity.
In practice: pick one output a month that you want to be proud of — and treat it differently.
Deep Work vs Shallow Work
Newport’s 2016 distinction, still the simplest frame for an honest time audit.
Deep Work
- High-cognitive, high-value output
- Needs sustained focus (60–90 minutes minimum)
- Creates results that move your career forward
- Hard to automate or delegate
- Examples: strategy, writing, complex analysis, developing people, creative problem-solving
Shallow Work
- Logistical, low-cognitive effort
- Easily interrupted and resumed
- Necessary but doesn’t compound
- Often automatable or delegatable
- Examples: email, scheduling, status updates, routine approvals, most recurring meetings
Your time audit: track one working day. For each block, mark Deep or Shallow. What percentage of your day is deep work? Most leaders are quietly shocked by the answer.
The AI-Augmented Leader
McKinsey’s 2024 State of Organizations research and the World Economic Forum’s 2025 Future of Jobs report agree on the direction: AI is reshaping management work. The value doesn’t move to the AI. It moves to what only humans can do with the AI.
Wisdom
AI contributes: data analysis, pattern detection, outcome prediction
The leader brings: judgement in ambiguity, ethical weight, context the model can’t see
Empathy
AI contributes: sentiment analysis, feedback summaries, morale signals
The leader brings: real human connection, psychological safety, trust earned over time
Creativity
AI contributes: options, remixes, variations at speed
The leader brings: original thinking, unlikely connections, the vision that sets direction
Influence
AI contributes: drafts, optimised messaging, personalisation at scale
The leader brings: authenticity, coalition-building, culture shaped by relationships
Sources: McKinsey, State of Organizations (2024); World Economic Forum, Future of Jobs (2025).
Three questions before you adopt any AI tool
Tool lists go out of date in months. These questions don’t.
- What is this replacing? If you can’t name what it replaces, it’s additional work, not leverage. Be specific about the task, the time it takes today, and what “good enough” looks like.
- Where does the human judgement sit? Every AI output needs a person deciding whether to trust it. Name that person, their responsibility, and what they’re accountable for.
- What does this cost your team to adopt? Training, trust, change fatigue, data risk, supplier risk. The tool’s monthly price is the smallest number in the equation.
What I’m seeing leaders get wrong with AI right now
Two failure modes, both common, both costly.
The first: leaders who outsource their thinking to the tool. They use AI to draft, decide, and summarise — and then stop noticing when the output is subtly wrong. Over months, judgement atrophies. The leader becomes a reviewer of machine-generated work rather than the author of their own.
The second: leaders who refuse to engage at all. They dismiss AI as hype, let their team adopt it without guidance, and miss the chance to shape how it’s used. A year in, they’re leading a function they don’t fully understand.
The leaders navigating this well are doing something different: learning the tools deeply enough to have an opinion, and protecting the thinking that only they can do. That’s the skill to build.
Want to work better, not just harder?
Productivity is one of the things leaders most often want to change — and one of the hardest to change alone. Book a free discovery call to talk about what’s eating your time.
Last reviewed: April 2026