🌊 Navigating AI in a Time That Feels ‘Too Late for the Gods and Too Early for Being’
What kind of mindset is needed when familiar ways of working no longer apply—and the new ones haven’t fully arrived?
The future is often treated as something to plan for.
But in the case of AI, organisations are not planning—they’re already reacting.
Old certainties no longer hold. New ones have not yet arrived.
This is a transitional period—where familiar ways of working no longer apply, and new approaches are still taking shape.
In these conditions, mindsets matter more than maps.
“We are too late for the gods and too early for Being.”
— Martin Heidegger
The Deep: Knowing in a State of Unknowing
Most change programs begin by identifying patterns and building plans.
But when the terrain itself keeps shifting, success depends on an emergent way of knowing, sensing, and adapting.
Traditional frameworks—roadmaps, maturity models, five-year strategies—struggle to contain the pace and fluidity of generative AI. The tools are still mutating. Use cases continue to unfold. Risks and opportunities are dispersed unpredictably across teams, roles, and industries.
A recent national study by Humanova (Breaking the Scale Barrier, March 2025) draws attention to a striking insight: mid-sized Australian SMEs are not just keeping pace with AI transformation—they’re leading it. And not because they have the most resources, but because they are more adaptable.
These organisations are cultivating power users—employees who use AI several times daily—not through mandates, but through enabling conditions: experimentation, informal learning, and shared agency.
This isn’t just a skills gap—it’s a mindset gap.
A Philosophical Pause: Thinking in Motion
In a world where tools evolve faster than the frameworks designed to manage them, organisations must learn to think in motion.
Heidegger’s line—“too late for the gods and too early for Being”—captures the disorientation of this moment. Blueprints are scarce. Benchmarks are outdated before they’re published. Best practices have become shifting sands.
The future is already arriving—but not yet in language organisations know how to use.
In this context, rushing to optimise may obscure deeper work: building environments where reflection, iteration, and improvisation are embedded in the rhythm of daily operations.
AI transformation is not just technical.
It is relational. It unfolds through trust, openness, and the willingness to share what’s unfinished.
The Emerging Mindset: Me, We, Us
The Humanova report reveals a useful structure for thinking about AI readiness—one that goes beyond tools and into culture. This can be seen through three concentric layers:
Me
The inner disposition. A willingness to experiment without mastery. To use AI not just for speed, but for stretching cognitive and creative capacity.
Curiosity, not just competence.
We
The team climate. High-performing teams don’t just use AI—they talk about it. They compare prompts, share examples, reflect on missteps. The report notes that 66% of power users actively share their learnings.
This is not a matter of process—it’s a matter of climate.
Us
The organisational rhythm. AI is not isolated in an innovation silo. It’s embedded across workflows and decision-making. Adaptive organisations decentralise capability, align it to purpose, and create the psychological safety required for continual experimentation.
Not a maturity model. A movement model.
The Irony: AI is Fast. But Wisdom Takes Time.
There is a risk of confusing speed with progress. Faster production doesn’t always equal better outcomes.
The Humanova findings suggest that long-term advantage won’t come from slick integrations—it will come from organisations that can learn, unlearn, and relearn as a collective.
Agility is important. But this moment calls for something deeper: emergence.
In a time that feels too late for old certainties and too early for new truths, the most honest response may be this:
Stay open.
Think in motion.
Meet emergence with emergence.
Your Course to Set
🦶 Dip your toe in:
When was the last time curiosity—rather than competence—guided the use of a new tool or approach?
🌊 Take the plunge:
What kind of mindset is being fostered in the current organisational environment? What would it take to make it more emergent?