A guide to ensure sustainable and humane adoption of the exploding AI Agentic ecosystem
In the last article, “Enabling AI : Re-Engineering the Agile Revolution”, I described how AI Transformations require sophisticated coaching and change management support. You can find that article here. AI is proving to be an accelerant, like pouring fuel on the digital fire. Some organisations, such as ours, are already seeing productivity gains across the Idea to Product lifecycle even at the early adoption stage of in excess of 90% improvement, especially in tasks such as research and analysis. It's no surprise that Consultancies such as the Big Four are investing heavily in AI orchestration and Agentic capability. I posited in that article that Coaching is the bridge that enables and accelerates changes in people’s thinking, behaviour, and leadership, which is essential for the coming AI Transformations to stick.
Chris Chan and I tackle this problem in a series of articles, this being the first.
For years, Agile and transforming ways of working were seen by many organisations as optional. It was mainly for tech teams, suited to digital initiatives, a mindset that only some parts of the business needed to worry about or a buzzword to re-label existing practices. Traditional, hierarchical organisations could afford to sidestep it. Sure, it might have helped them move faster or adapt better, but they could still achieve results through scale, command-and-control structures and brute force. Being slow wasn’t ideal, but it wasn’t fatal.
Not anymore. AI brings speed and complexity that significantly and exponentially outpace traditional ways of working.
The rise of AI has fundamentally shifted the ground beneath us. AI is not going away. You can’t sidestep AI. AI is not just another tool. It’s a force multiplier that accelerates everything - opportunities, risks, disruptions, and demands for change. And this acceleration exposes a critical truth, organisations that don't operate with agility will be too slow, too rigid, and too siloed to harness AI's full potential. Worse, they'll be unable to respond when AI reshapes markets overnight.
If AI is going to accelerate progress, then you cannot scale AI on crappy ways of working. Agile is no longer optional. Organisations with cross-functional, agile operating models have a clear path forward to unlock AI’s full potential. Scaling AI demands scaling how you work first. Tools and technology, like AI, is only as powerful as the system it reside in.
If the organisation’s ways of working are chaotic, slow, siloed, or misaligned, the AI Capability won't deliver results at scale. Instead, it will just amplify the dysfunction. AI depends on how people, processes, and systems work together, not just algorithms.
In software development, refactoring makes code easier to understand, modify, and maintain, leading to more agility, adaptability, and speed. Similarly, through transformation efforts, you are refactoring your organisation’s ways of working to create clearer communication, improved collaboration, faster decision-making, and increased responsiveness to change. This will lead to higher adaptability and organisational performance.
Here are some key reasons why your System of Work is critical for AI transformation:
An understanding of complex adaptive systems and a belief in the idea of complexity are critical attributes of successful transformations to embed AI into an organisation's fabric. Our transformation experience across multiple industries and domains has shown that without this belief, any form of transformation has proven to be difficult and hampered. AI transformation is no different. If you believe every problem can be addressed with Clear simple solutions, that they can be analysed to perfect plans, you don't understand complex adaptive systems.
Agile is a mindset, at its core, not just process, framework or set of practices. A key aspect of this mindset is a belief in complexity. Complexity is when something has many interconnected parts, relationships, or factors, making it hard to fully predict, control, or understand. You often hear about organisations being complex.
Every organisation is a unique, complex adaptive system. Let’s briefly break this down:
In simple terms, you can’t control an organisation like a machine by pulling a few levers. Instead, you need to create the conditions for it to learn, adapt, and thrive on its own.
Organisations behave more like living, evolving ecosystems than simple machines. Culture arises naturally over time from people's interactions, shared experiences, and collective behaviour - it’s not something you can fully design, control, or impose. Leaders can influence conditions (like setting clear values, structures, rituals) but can't force culture directly. Culture is what grows out of what we repeatedly do and experience together. This has been one of the biggest paradigm and mindset shifts over the past 20 years.
Over the past 20+ years, we have learned that people-centric, coaching-based and iterative approaches have been important to organisational transformations and evolutions due to the nature of complex adaptive systems.
A Coach is an individual who plays a crucial role in facilitating organisational change in complex adaptive systems, often acting as a guide, coach, mentor or facilitator. A coach not only has a deep understanding, strong belief and experience working in complex adaptative systems, they also thrive working in it. It’s this experience and skills that is needed to navigate the uncertainty of AI transformation.
Over two decades ago, Lyssa Adkins and Michael Spayd created the Agile Coaching Competency Framework (2011, Agile Coaching Institute). They introduced this framework, which is still in use today worldwide with some adaptations, to delineate the essential competencies required for effective agile coaching.
We believe this model provides a basis for AI Transformation coaching. AI extends and evolves the Agile Coaching Competency Framework to reflect the impact of AI on coaching practices. In essence, an AI coach needs not only a deep understanding of AI's technical underpinnings and tools but also how to strategically integrate these into an organisation's operating model, culture, and existing governance frameworks while prioritising human-centricity and continuous adaptation.
In the next article we delve into the key Competencies we think apply and need to be adjusted, and how AI Coaches will bridge the gap between technical possibilities and business realities, facilitating the cultural and process changes necessary for sustainable AI implementation.
Thanks for reading part one! Check out part two here.
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