Growth is a collective development. We should grow as a community. We should grow as a humanity, we cannot succeed individually.

In a world already obssesed with growth, and AI bringing speed that we've never seen before, understanding how to intentionally design for human centred growth strategies is so important. Systems only work when the humans inside the systems are seen, valued, and allowed to grow.

Bala and I discuss the fact that building effective systems—engineering, organizational, or community—is fundamentally a human design problem, and how AI makes this more urgent. Bala shares invaluable insights from advising startups to teaching coding in public schools.

We dive into redesigning organizations around AI without losing the human element, ethical AI as a design principle, and building human-centered communities when tools change faster than people. Many see AI as a tool for efficiency, a way to move faster. But if you purely optimise with AI without deeply examining your organizational structure and culture, you’re merely moving the bottleneck, not solving it. AI accelerates discovery, highlighting existing issues, especially in low-trust environments. Introducing AI into a low-trust culture doesn’t magically build trust. It automates around the lack of it, potentially exacerbating issues and inciting the use of 'shadow AI'. The foundational element for any successful team remains trust.

As leaders, we must focus on fostering environments where trust is built proactively, before the pressure of AI-driven decisions.

The main insights you'll get from this episode are :

Systems only work when the humans inside are seen, valued and allowed to grow; humans are also the meta point in organisations, so it is vital to understand what motivates them (before they decide to leave).

Building a team in a fast-scaling company requires first and foremost the right environment and culture, i.e. how people interact, how things are set up; AI acts like an x-ray machine, quickly showing what is broken and mirroring what is happening.

Any team success requires trust and in the AI age, this entails trusting (or not) in AI as a system, trusting (or not) the output I produce (direct), and trusting (or not) others to use AI properly (indirect).

The human aspect is about making things come together; AI requires fast decisions from leaders so leaders must trust their people, not identify or label them by their mistakes.

AI governance is both a legal and human/behavioural issue – everyone should be involved in the conversation as AI is not an entity in itself; we give it life/power, which gives rise to ethical issues.

New generations have access to tools/power and are already thinking about impact (moving away from the conventional leadership model) and the need for community, factoring this into decision-making to make it easier to create new tools quickly.

Growth is a collective development, and success is not possible individually because access is now decentralised; the infrastructure must be a community as a living thing, helping others unbidden and building networks of trust.

Leaders must intentionally make time for and ‘invest’ in community, taking off their leader ‘hat’ in an informal setting, for example; it all starts with objective communication, removing the subjects to change the perspective.

AI is an opportunity to revamp organisational design with humans as the connective tissue in the system; in future, governments, education/industry, and economies must come together to include everyone and work for humans.

Being curious is good enough and will guide us to the next step; we should get our hands dirty and humbly remember that our day jobs are creating a world for the next generation.

Find out more about Bala and his work here :

https://balamuthiah.com/

The biggest danger in today’s hyperconnected world isn’t moving too slowly. It’s moving too fast without understanding the system.

The world today operates with unprecedented interconnectedness, where a single decision in technology can impact climate systems, and policy shifts can ripple across global supply chains. We no longer manage isolated organizations. Instead, leaders navigate a complex, living ecosystem. This fundamental shift requires a new kind of awareness and a deeper understanding of the systems at play.

Matt & I explore the evolution of leadership from data-savvy to AI-savvy, drawing on insights matt's decades of experience in technology, ecosystems, and supply chains. He understands how interconnected decisions impact industries, communities, and even the planet. His journey from deep tech innovations to corporate data science and now to Earth Savvy provides a unique perspective on the challenges and opportunities for modern leaders.

Today’s hyperconnected world means we must understand connections; an architecture based on AI agents enables us to ask our own questions about the world around us to get simple insights/answers one at a time.

In this hyperconnected landscape, understanding what happens outside your immediate business becomes crucial. While asking the right questions remains vital for leaders, AI offers something more profound. AI provides the ability to go deeper, to question assumptions more thoroughly, and to imagine connections in ways previously impossible. AI agents can perform work on our behalf, multiplying our abilities in driving transformation, but they need to be directed by human input and questions. The key is to ground AI use in our desired direction and questions, rather than simply outsourcing our thinking to an AI model.

What’s one aspect of your business where you’re actively exploring broader systemic connections, rather than just refining existing processes?

The main insights you'll get from this episode are :

• To project into the future, leaders must heed current circumstances elsewhere in the world; experts know the key questions to ask but need help to get the answer from huge volumes of data.
• Being data savvy now means being AI savvy, and asking the right questions is at the heart of transformation; AI brings an ability to go deep and question ourselves first and foremost.
• AI agents can work on our behalf and act as multipliers for our own abilities as long as they are directed by human questions – but moving too fast and ignoring the system is dangerous.
• Human-agentic collaboration complexifies decisions and a core skill for leaders is true systems thinking, i.e. understanding your own hypothesis to fit into an AI framework - simplicity and focus are vital to get answers.
• A big deep tech issue is to make data understandable and valuable - innovation is no longer about creating new products/solutions/tools, but about curation and removing complexity.
• Leadership is moving from control to orchestration – in future, thriving organisations will build connections/value chains internally; AI is both a blessing and a curse here as it can stop humans connecting.
• AI is no different from previous automations but the insights it delivers need to be human; the increasing power of software will help us understand the data and enable us to simplify processes via agents.
• Satellite data will be as integral to our lives in future as GPS data is today; earth observation data is much richer than GPS data and we will come to rely on it - EarthSavvy will provide the platform while we ‘update our human software’.
• Leaders should consider all touchpoints outside the organisation over a large surface area to build a mental model for change - taking an inventory as a starting point shows where you fit into the broader system around you.

Find out more about Matt and his work here :

https://earthsavvy.ai/

https://www.linkedin.com/in/matthew-evans-8756726/