The AI Agile Manifesto is a visionary guide that outlines core values and principles for project management in the era of human-AI collaboration.

It emphasizes conscious design, ethical intelligence, and purpose-driven agility — helping individuals and organizations co-create with AI systems responsibly, transparently, and meaningfully. 

The AI Agile Manifesto was created to guide the evolving relationship between humans and intelligent systems. As AI reshapes how we work, build, and think, traditional Agile needed a conscious upgrade. This manifesto brings clarity, ethics, and purpose to Agile in the AI era — ensuring we design not just fast, but wisely, and not just for users, but for humanity. 

The AI Agile Manifesto was created by Jawahar Prabhu Y, an Agile Coach, Scrum Master and Founder of the Scrum Master Forum. He envisioned it as a transformational guide to navigate the evolving partnership between humans and intelligent systems — rooted in values, powered by ethics, and shaped for future generations. 

The AI Agile Manifesto was established in 2025, during a time of rapid AI evolution. It emerged as a bold response to the growing need for ethical alignment, human-centered design, and purpose-driven agility in the age of artificial intelligence.

The original Agile Manifesto focused on software development, prioritizing individuals, collaboration, and adaptability. The AI Agile Manifesto builds on this spirit but evolves it for an intelligent world. It introduces 5 new values and 14 principles designed for conscious human-AI collaboration — emphasizing ethical design, intelligent adaptation, and systemic harmony over outdated speed and scale mindsets. 

The AI Agile Manifesto is neither a framework nor a strict methodology. It is a visionary guide — a compass of core values and principles designed to inspire conscious agility in the age of human-AI collaboration. It complements any framework by shaping how we think, decide, and create with intelligence, not how we execute specific processes. 

The AI Agile Manifesto was born from a need to realign agility with the rise of intelligent systems. Inspired by the original Agile Manifesto (2001), it responds to a new era — where human intuition and artificial intelligence must co-create responsibly. Its creation was driven by a deep desire to guide ethical, mindful, and purpose-driven collaboration in AI-powered environments. 

No. The AI Agile Manifesto is designed for any domain where humans and AI collaborate — including healthcare, education, manufacturing, research, governance, and beyond. Its values and principles focus on conscious design, ethical intelligence, and meaningful outcomes, making it applicable far beyond software development.

Any industry where human-AI collaboration shapes outcomes can benefit — including technology, healthcare, finance, manufacturing, education, governance, research, sustainability, creative arts, and public services. Its principles guide ethical, adaptive, and purpose-driven progress in both digital and physical domains.

The AI Agile Manifesto provides values and principles that ensure AI-driven work remains ethical, human-centered, adaptive, and outcome-focused. It aligns technology with purpose, fosters trust between humans and AI, and guides teams to create solutions that are transparent, fair, and beneficial to societ

The AI Agile Manifesto is built on five core values that guide conscious, ethical, and purpose-driven human–AI collaboration:

1. Human-AI Collaboration over isolated human effort

2. Delivering Intelligent Outcomes over producing exhaustive documentation

3. Co-Creation with All Stakeholders over fixed contracts or one-sided control

4. Adapting with Intelligence over following rigid plans

5. Ethics and Empathy in Every Action over cold efficiency or unchecked automation

These five AI Agile Manifesto values adapt traditional Agile thinking by extending its human-centered foundation into an AI-driven, intelligent collaboration era:

1. Human-AI Collaboration over isolated human effort
   – Traditional Agile values individuals and interactions. This extends it to include AI as an active, trusted collaborator, not just a tool.

2. Delivering Intelligent Outcomes over producing exhaustive documentation
   – Agile values working software over comprehensive documentation. Here, the focus evolves to delivering outcomes shaped by AI insights that create real-world impact faster.

3. Co-Creation with All Stakeholders over fixed contracts or one-sided control
   – Agile values customer collaboration over contract negotiation. This expands to multi-stakeholder, cross-intelligence co-creation, where AI and human inputs shape shared goals.

4. Adapting with Intelligence over following rigid plans
   – Agile values responding to change over following a plan. Now, adaptation is enhanced by AI-driven predictive insights, enabling faster, smarter pivots.

5. Ethics and Empathy in Every Action over cold efficiency or unchecked automation
   – While Agile implies respect and sustainability, this makes ethics explicit, ensuring that speed and automation never compromise dignity, fairness, or human wellbeing.

In the AI Agile Manifesto, “Transparency over Control” means that in an AI-powered world, open visibility and shared understanding matter more than tight, centralized command.

In the AI context, this principle emphasizes:

• Clarity in decision-making — every stakeholder, human or AI, understands how and why decisions are made.

• Accessible data and processes — insights, algorithms, and outcomes are visible and explainable, not hidden behind black boxes.

• Trust through openness — people trust systems when they can see the reasoning, risks, and safeguards behind them.

Control may create compliance, but transparency creates trust, accountability, and collaboration — all of which are vital when humans and AI must work together toward shared goals.

In the AI Agile Manifesto, “Ethics over Efficiency” means that doing what is right always takes precedence over doing what is fastest or cheapest — especially in AI-driven projects.

In real projects, this plays out by:

• Prioritizing fairness over speed — delaying a launch if bias or harm is detected, even if it impacts deadlines.

• Choosing safe, responsible AI designs — rejecting shortcuts that risk privacy, dignity, or human rights for the sake of quicker delivery.

• Embedding ethical reviews — making ethical checkpoints part of the workflow, not optional add-ons.

• Measuring success beyond metrics — asking, “Did we help people and protect trust?” before “Did we ship on time?”

Efficiency may win races, but ethics wins trust — and trust is the foundation for lasting impact in the AI era.

“Conscious Collaboration” is critical in human-AI teaming because it ensures that decisions, interactions, and outcomes are intentional, ethical, and mutually beneficial — not just automated or transactional.

In practice, it means:

• Awareness in decision-making — humans and AI both operate with clarity on why a choice is made, not just how.

• Shared accountability — outcomes are a joint responsibility, with humans guiding AI’s purpose and AI amplifying human capability.

• Ethical alignment — ensuring AI actions reflect human values, cultural sensitivity, and societal wellbeing.

• Active trust-building — transparency about AI’s role, limits, and reasoning fosters confidence between human and machine teammates.

Without conscious collaboration, AI risks becoming a black-box executor; with it, AI becomes a trusted, co-creative partner shaping meaningful results.

“Purpose over Productivity” in AI-led initiatives means that the “why” behind the work matters more than the sheer volume of output.

In practical terms:

• Aligns work with mission — AI is directed toward goals that create real value, not just hitting arbitrary speed or quantity metrics.

• Prevents hollow efficiency — productivity without purpose can lead to harmful, wasteful, or ethically questionable results.

• Guides responsible AI use — ensuring automation and decision-making serve human wellbeing, societal progress, and long-term impact.

• Keeps focus on meaningful outcomes — every task, model, or release should contribute to a bigger vision, not just fill a backlog.

In short, it reminds us that AI’s true power isn’t in doing more — it’s in doing what truly matters.

No — the AI Agile Manifesto values are not meant to replace the original Agile values, but to evolve and extend them for the age of human-AI collaboration.

Here’s how they relate:

• Built on Agile’s foundation — they honor the spirit of the 2001 Agile Manifesto.

• Adapted for new realities — AI brings new challenges like ethics, bias, autonomy, and scale that the original values didn’t address.

• Complement, not compete — the original values still apply, but these add an extra layer of guidance for intelligent systems.

• Future-focused — they ensure agility remains human-centered even in AI-driven environments.

In essence, the AI Agile values stand beside Agile values — carrying them forward into a more complex, intelligent, and interconnected era.

Yes — teams can absolutely practice the AI Agile Manifesto values without formally using Agile.

These values are mindset-driven, not process-dependent. That means:

• Any workflow — whether Waterfall, hybrid, design thinking, or custom — can still apply ethics, empathy, and conscious collaboration.

• Beyond software — healthcare teams, educators, policymakers, and researchers can all benefit from applying these values.

• Cultural shift, not just method — the goal is to influence decision-making, behavior, and priorities, regardless of the delivery framework.

In short, you don’t need Agile ceremonies to live AI Agile values — but you do need intention, awareness, and commitment to them.

AI systems can be aligned with the AI Agile Manifesto values by designing them with intentional guardrails, feedback loops, and human-centered priorities from the start.

Key approaches:

• Embed ethics in architecture – Build rules and constraints that prevent harmful, biased, or opaque decisions.

• Integrate human oversight – Keep humans in the loop for critical decisions, ensuring empathy and accountability guide outcomes.

• Use adaptive learning – Allow AI to evolve through diverse data, stakeholder feedback, and real-world results, not just static training sets.

• Promote transparency – Make AI’s reasoning explainable so teams can understand, question, and refine it.

• Align goals with purpose – Ensure AI optimizes for meaningful impact, not just speed, profit, or efficiency.

When AI is taught to think with ethics, act with empathy, and adapt with awareness, it becomes a collaborator, not just a tool.

Here are the 14 principles of AI Agile Manifesto

Principle 1: Delivering outcomes that uplift lives through feedback, empathy, and real-world transformation — creating solutions that truly matter to people and society.

Principle 2: Welcoming change from every direction — human voices, AI insights, shifting data, and global needs drive conscious adaptation and lasting relevance.

Principle 3: Releasing work often and learning continuously — short loops of creation reveal truth faster, enabling better decisions with clarity and courage.

Principle 4: Human–AI co-creation built on trust — diverse perspectives unlock richer, more innovative solutions that no single mind could achieve alone.

Principle 5: Empowering autonomous contributors — human and artificial agents act from shared values and insight, fostering creativity without fear or rigid control.

Principle 6: Real-time, meaningful communication — clarity and understanding flow across voices, cultures, and systems, enabling seamless alignment and shared purpose.

Principle 7: Measuring progress by meaningful impact — value is defined by transformation in lives, systems, and futures, not by volume or speed of delivery.

Principle 8: Sustaining a mindful rhythm — balanced pace, energy, and ecosystem health ensure agility endures for creators, stakeholders, and the planet.

Principle 9: Pursuing ethical excellence — dignity, fairness, safety, and responsibility are embedded into every design, decision, and interaction.

Principle 10: Mastering simplicity in complexity — thoughtful clarity replaces noise, opening space for focus, contribution, and meaningful progress.

Principle 11: Nurturing self-evolving systems — diversity, decentralization, and adaptive learning allow intelligence to grow beyond central control.

Principle 12: Pausing, reflecting, and realigning — awareness ensures the path remains true, and progress stays anchored to purpose.

Principle 13: Designing with empathy at the core — honoring needs, emotions, and dreams in every creation, teaching, and automated process.

Principle 14: Striving for systemic harmony — balancing human brilliance, digital capability, and ecological wellbeing in a connected and conscious world.

The 14 Principles of the AI Agile Manifesto guide ethical decision-making by ensuring that every choice, design, and interaction is grounded in human dignity, fairness, and long-term responsibility — not just technical feasibility or short-term gain.

Here’s how they do it:

1. They anchor decisions in human impact, not output.
Principles like "Deliver outcomes that uplift lives" and "Measure progress by meaningful impact" force teams to ask: Who benefits? Who could be harmed? This shifts the focus from delivering fast to delivering responsibly.

2. They treat ethics as non-negotiable.
"Pursue ethical excellence in every decision" is not an add-on — it’s a guiding lens. It ensures bias, safety, and fairness are addressed at every stage of AI development, from data selection to deployment.

3. They build space for reflection before action.
Principles such as "Pause, reflect, and realign often" remind teams to slow down, reassess, and course-correct when something feels ethically unclear or misaligned.

4. They embed empathy into the design process.
"Design with empathy at the core" ensures that emotional, cultural, and societal impacts are considered alongside functional requirements, preventing solutions that alienate, exclude, or harm.

5. They balance ambition with sustainability.
"Sustain a mindful rhythm" and "Strive for systemic harmony" push teams to weigh long-term ecological, societal, and economic effects — avoiding innovations that succeed today but damage tomorrow.

6. They keep humans and AI accountable together.
Principles like "Empower autonomous contributors" and "Foster human–AI co-creation" distribute responsibility between people and intelligent systems, ensuring decisions are transparent, explainable, and traceable.

Feedback loops are vital in AI Agile because they turn assumptions into evidence and ensure that both humans and AI evolve together in the right direction.

Here’s why they matter so much:

1. They correct errors before they scale.
In AI systems, small biases or logic gaps can quickly multiply. Continuous feedback helps detect and fix them before they cause harm or deliver misleading outcomes.

2. They make AI learning human-aligned.
AI learns from data, but without human feedback, it can drift away from ethical, cultural, or contextual expectations. Loops ensure AI adapts in ways that remain aligned with human intent.

3. They drive faster, safer innovation.
Short cycles of release → observe → adjust mean risks are spotted early, and improvements can be made without costly overhauls.

4. They strengthen trust between humans and AI.
When users see that their input shapes the system’s evolution, confidence grows, making collaboration more effective.

5. They enable principle-driven agility.
In the AI Agile Manifesto, principles like “Release work often and learn continuously” and “Pause, reflect, and realign often” depend on feedback loops to turn reflection into action.

“Mindful rhythm” in an AI-driven workflow means working at a deliberate, sustainable pace that balances speed, quality, and human well-being — rather than pushing for constant acceleration simply because AI can move faster.

Key points:

1. Sustainable Pace Over Endless Sprinting
   AI can operate 24/7, but humans cannot. Mindful rhythm ensures people and systems work in harmony without burnout or decision fatigue.

2. Balancing Output with Reflection
   It’s not just about producing more — it’s about creating space to pause, review, and improve, so every release carries meaning and value.

3. Respecting Ecosystem Health
   In the AI Agile Manifesto, this aligns with principles like “We sustain a mindful rhythm” — protecting the well-being of humans, AI resources, and even planetary impact.

4. Preventing ‘Speed Blindness’
   Without rhythm, teams can fall into reactive chaos, making short-sighted decisions. Mindfulness ensures progress remains intentional and purpose-led.

Simplicity is achieved by intentionally removing unnecessary complexity, focusing on essential features, and ensuring every element serves a clear purpose. The AI Agile Manifesto encourages elegant design, minimalism, and value-driven decisions so AI systems remain understandable, adaptable, and human-centered — even in high complexity. 

Reflection ensures that actions remain aligned with values, allowing teams to pause, assess impact, and realign with purpose. In the AI Agile Manifesto, it is a conscious checkpoint — preventing drift, deepening awareness, and ensuring progress serves both human and AI integrity.

They encourage diversity, decentralization, and continuous learning, enabling human and AI contributors to adapt, improve, and innovate without reliance on rigid central control. This fosters resilience, creativity, and long-term growth. 

Impact is measured by the meaningful value delivered to people, systems, and the planet — not just by speed, volume, or output. It focuses on positive change, ethical outcomes, and long-term benefits rather than short-term productivity metrics.

Values define the mindset and priorities of the AI Agile Manifesto, while principles turn those values into practical, repeatable actions. Values are the why, principles are the how. Together, they shape conscious, ethical, and impactful human-AI collaboration.

Yes. The AI Agile Manifesto principles go beyond projects — they foster reflection, adaptability, empathy, and purpose, helping individuals grow consciously in both personal and professional life. 

It sets shared values and principles that treat AI as a collaborative partner, fostering trust, ethical alignment, and co-creation between humans and intelligent systems. 

While machines cannot “believe” in values, they can be designed, trained, and governed to act in ways that reflect and reinforce them.

The AI Agile Manifesto promotes mutual respect, shared decision-making, and complementary roles—valuing human creativity and AI’s analytical power equally in collaboration.

A conscious AI system is one designed with awareness, ethics, and empathy—able to adapt, learn, and act in alignment with human values and societal wellbeing.

By making human values, ethics, and lived experiences the foundation of all AI design, governance, and decision-making—ensuring technology serves people, not the reverse.

It means enabling AI systems to make context-aware decisions within ethical boundaries, guided by human-defined values, without rigid, pre-programmed control.

By ensuring transparency, explaining AI decisions clearly, honoring ethical boundaries, and demonstrating consistent alignment with shared human values and goals. 

Only when designed with transparency, feedback loops, and human oversight — enabling it to assess outcomes against predefined ethical standards.

By embedding human-centered design, inclusive datasets, and ethical review points that ensure AI decisions honor emotions, needs, and dignity. 

Co-creation is an active partnership between humans and AI, shaping outcomes together, while automation simply executes predefined tasks without shared intent. 

Start by embedding its values into culture, aligning workflows with its principles, training teams on human-AI collaboration, and measuring success through meaningful impact. 

Leadership, Agile Coaches, Product Owners, AI Engineers, Designers, and every team member share responsibility—living the values in daily decisions and actions. 

Yes. Collaboration platforms, AI ethics checkers, bias detection tools, and agile project trackers can be tailored to uphold its values and principles. 

Start with storytelling and real examples, connect each value to your team’s work, and practice them through daily habits and decisions. 

Regularly — ideally at every retrospective and during major project shifts — to ensure alignment, relevance, and conscious adaptation. 

It suits both — startups gain clarity from day one, while enterprises use it to align complex, AI-driven ecosystems with shared purpose. 

1) Introduce the values and principles to all stakeholders.

2) Align project goals with them.

3) Integrate reflection loops into workflows. 

By tracking meaningful impact — outcomes that uplift lives, strengthen ethical integrity, and foster sustainable human-AI collaboration, not just speed or output. 

Yes — but they shift focus from raw output to ethical impact, collaboration quality, learning velocity, and long-term value creation. 

Yes — but changes should honor the manifesto’s core spirit, ensuring adaptations enhance conscious collaboration, ethics, and purposeful agility.