AI In Two Years: Are We Designing the Future – Or Just Racing Not To Lose?
“If you’re worried about immigration taking jobs, you should be far more worried about AI. It’s like a flood of millions of digital workers with Nobel-level capability that never sleep.”
— Tristan Harris, The Diary of a CEO
Artificial Intelligence is often framed as the ultimate engine of productivity and innovation. Yet as Tristan Harris reminds us, the story is incomplete if we ignore the speed, incentives, and risks behind the race.
At AMMA Lab, we hold both truths:
AI is both a powerful force for human progress and a systemic risk when built without reflection, governance, or shared responsibility.
This reflection explores how leaders can design the future of AI consciously, instead of merely racing not to lose.
A Race With The Wrong Rules
The global pursuit of Artificial General Intelligence (AGI) is accelerating, and it’s driven less by science than by incentives.
Inside the labs, many believe systems that match or surpass most human cognitive abilities may emerge within the decade.
The risk is not only in creating superintelligent models, but in automating AI research itself, systems that learn to improve their own capabilities.
When fear and competition replace reflection, leaders begin to rationalise existential risk in the name of progress.
This is not just a race of technology. It’s a race of egos, incentives, and fear.
The Bright Side We must Protect
AI’s potential is real and deeply transformative:
Productivity gains through human–AI collaboration.
Breakthroughs in healthcare and sustainability.
Greater accessibility, inclusion, and knowledge democratisation.
When guided with intention, AI expands human capability, freeing people from repetition to create, learn, and connect.
The question is not whether AI can do good.
It’s whether we will create the cultural and ethical systems that make the “good” sustainable.
3. The Risks We Must Confront
The same intelligence that empowers us can destabilise us:
Labour shock without reskilling pathways.
Hyper-personalised manipulation of attention and beliefs.
Democratic fragility, as deepfakes and disinformation erode trust.
Security escalation, from autonomous weapons to cyber-offence.
Psychological harm, when AI simulates intimacy or reinforces illusions.
The goal is not alarmism, it’s maturity.
Leadership means looking at both sides of the system we’re building.
“If We Don’t, They Will” — The Most Dangerous Story
Many justify acceleration with fear:
“If we don’t build it, someone less responsible will.”
“If we slow down, others will win.”
This logic turns the entire planet into an arms race, where each actor is trapped by everyone else’s anxiety.
We’ve seen this before in climate change, in nuclear competition.
AI is simply moving faster and closer to the human mind.
If we treat AI as a race, we will get race-like outcomes: shortcuts, opacity, and systemic risk.
The answer lies in redesigning the rules, not just urging restraint.
Building AI “Only for Good” — or at Least, for Better
No technology has ever been “only for good.”
The real question is: how do we structure intelligence so that it serves life, not replaces it?
A multi-layered answer is emerging:
Clear Principles and Red Lines
Define where AI accelerates value and where it crosses ethical thresholds.
Encourage augmentation, forbid manipulation.
The EU AI Act is one example of turning ethics into enforceable boundaries.
Strong Governance and Internal Guardrails
Every organisation should establish a simple but living AI governance framework:
Risk classification and use-case mapping.
Human-in-the-loop systems for critical decisions.
Clear escalation and reporting channels for unsafe behaviour.
Frontier Oversight
Safety is moving closer to hardware.
Initiatives like “Know-Your-Customer” for compute providers and chip-level safety locks are early steps in preventing untraceable large-scale AI training.
Policy and Collective Action
Regulation alone is not enough.
We need civic awareness, ethical leadership, and public pressure.
AI safety must become a social issue, not just a technical one.
What Conscious Leaders Can Do Now
For CEOs, CHROs, and boards, conscious leadership begins with five commitments:
Learn enough to lead — understand AI’s mechanisms, risks, and limits.
Adopt AI as an enhancer, not a silent replacer.
Design transition plans that protect and empower people.
Create an internal AI governance model that fits your context.
Use your voice — challenge fear-based narratives and support balanced regulation.
Leadership today is no longer about keeping up.
It’s about slowing down with intention, so that progress keeps its humanity.
Human-Centric and AI-Enabling — Not Naïve
At AMMA Lab, our work stands at the intersection of:
Leadership and cultural transformation
Executive transitions and human development
AI as a practical enabler for ethical progress
We are not against AI. We are against unconscious acceleration.
Our vision is clear: a world where technology amplifies presence, not replaces it.
If you want to:
Clarify AI’s role in your strategy and culture,
Design a human-centred roadmap, or
Prepare your teams for the future of work —
We’re ready for that conversation.
“Realistic, human-centric AI strategies — balancing ambition with responsibility — that keep people at the core of progress.”
— Artur, AMMA LabHuman Futures. Powered by Conscious AI.
🎧 Listen to the full conversation with Tristan Harris here: The Diary of a CEO — Episode 6027603
