What parenting, neuroscience, and digital transformation have in common — a personal reflection on how to apply artificial intelligence with a balance of logic and creativity.
The child’s brain, the organisation’s brain
In recent weeks, I’ve been delving into “The Whole-Brain Child” by Daniel J. Siegel and Tina Payne Bryson. My motivation is simple and very personal: I’m a mother to a two-and-a-half-year-old, and, like many parents, I’m trying to better understand how I can support his emotional and cognitive development.
But, as so often happens (and thankfully so), personal and professional life topics intersect – and this book was no exception. As I reread about the importance of integrating the brain’s two hemispheres (the left – logical, structured, analytical – and the right – creative, intuitive, emotional), I found myself revisiting ideas I’ve explored in other contexts and experiences.
For years, I was responsible for implementing various innovation processes in large organisations and training executives, where I precisely used this metaphor of brain hemispheres to discuss leadership, learning, and organisational transformation. It was an effective way to illustrate the importance of balancing structure with creativity, and reason with emotion.
Today, I lead projects at the intersection of data, artificial intelligence, and strategy, and that same metaphor has become relevant again – perhaps more than ever.
I see many organisations investing heavily in AI, but often with an unbalanced vision: a strong focus on the “left” side – automation, efficiency, processes, predictability – and little room for the “right” side – experimentation, empathy, innovation, and creative value generation.
Just as a child needs to learn to connect both sides of their brain to grow healthily, companies also need to learn to apply artificial intelligence with a truly holistic vision. Only then can we build a truly intelligent “organisational brain” – one that thinks, but also imagines.
This article stems from that reflection: what lessons can we draw from the human brain to better apply AI in organisations? And is your company using its full brain potential – or just half?
The left side of AI — Structure, efficiency, and control
If we think of the brain’s “left side” as what helps us organise ideas, analyse data, follow a logical sequence, and make rational decisions, it’s easy to see the parallel with the type of artificial intelligence applications we currently see most in organisations.
This is the side of AI that most quickly gained ground in the corporate world: the one that allows for task automation, reduced operational costs, improved predictability, and data-driven decision-making.
We’re talking about solutions like:
- Predictive models for sales forecasting or inventory management.
- Intelligent automation of repetitive processes through RPA (Robotic Process Automation) with AI.
- Risk and fraud analysis with machine learning.
- Personalised recommendations based on behavioural patterns.
- Smart dashboards that interpret real-time data.
These are all extraordinary advances, and many of them are well-established today. However, they still reflect a very “left-brained” approach (not to be confused with political views): oriented towards logic, structure, control, and efficiency.
It’s also, curiously, the side that organisations most easily integrate into their business models – because it fits well with the language of CFOs, operations directors, and those responsible for efficiency and control.
But… is it enough?
My experience in strategic projects has shown that while this type of AI solves many “known problems,” it rarely answers a more complex and powerful question: “What if we did things differently?”.
And that’s where the right side comes in.
The right side of AI — Creativity, experimentation, and vision
If the left side of AI answers questions like “what’s happening?” or “how can we do this more efficiently?”, the right side invites us to go further: to imagine what hasn’t been done yet, to explore unexpected possibilities, and to create new paths.
It’s the side of intuition, empathy, creativity, and imagination – all human capabilities that, until recently, we considered beyond the reach of machines.
But reality has changed. With the advancement of generative technologies, AI has also started to occupy this creative space:
- Generation of visual and textual content, such as images, videos, advertising campaigns, or storytelling.
- Co-creation of products, through AI that suggests design ideas, functionalities, or market approaches.
- Exploration of future scenarios, with models that help simulate consumer behaviour or market dynamics.
- Assistance to human creativity, through tools that amplify, refine, or challenge existing ideas.
This right side of AI doesn’t replace human creativity – it expands it. It acts as an extension of our imaginative capabilities, offering us new ways to think, express, test, and even feel. To quote the brilliant Gary Kasparov: “Say Augmented Intelligence and not Artificial. We are being promoted.”
How many times have you used ChatGPT, for example, to get inspiration for a more structured message, a clearer text, or even an idea that was difficult to articulate? But that only truly works when we know what we want to ask – when we can structure our thoughts, or “prompt” with intention and clarity. In other words, for creativity to flourish, the logical (and human) side must be strongly present.
However, it’s also the right side that often scares or disorients more traditional organisational structures – because it deals with less predictable, more open, more “fluid” areas. But precisely therein lies the greatest potential for transformation.
Throughout my career, I’ve worked with many innovation teams and seen first-hand how organisational creativity can be stifled by an obsession with efficiency. AI, used intelligently, can give back that space for exploration – provided we trust it to be a partner in the creative process, not just a logical executor.
Integration — The true power lies in using the whole brain
Just as we learn in “The Whole-Brain Child,” healthy development isn’t built with a single hemisphere. True intelligence emerges from the ability to integrate – to connect the rational with the emotional, structure with intuition, control with creativity.
In the context of artificial intelligence, the principle is the same.
Over the past few years, we’ve seen rapid and consistent evolution in the use of AI oriented towards efficiency: faster decisions, less human error, greater scale. However, this approach, focused on the “left” side of the organisational brain, isn’t enough on its own. It becomes limited when the goal is to innovate, reinvent, adapt to new realities, or create truly differentiating value propositions.
On the other hand, the “right” side of AI – with generative tools, creative models, design assistants, and scenario simulations – offers a new layer of potential. A layer that allows us to imagine products, experiences, and strategies that were previously unthinkable or too time-consuming to test.
But the real turning point lies in the ability to bring these two worlds together. To put analytical thinking at the service of creativity. To use data to fuel ideas, and ideas to generate new data. To create a culture where AI is not just an efficiency engine, but also a catalyst for strategic imagination.
Integrating both sides means, for example:
- Stimulating multidisciplinary teams where data scientists work alongside designers, marketers, or strategists.
- Using the same models that power operational dashboards to create simulations of possible futures.
- Incorporating creative AI at key moments of product development, strategy, or communication, without losing the rigour that underpins execution.
As a mother, I observe with amazement how my son’s still-developing brain already shows signs of this duality – how it oscillates between free curiosity and the search for patterns, between emotion and the attempt to understand it.
As a professional, I recognise the same challenge in organisations: knowing how to use AI not just to solve existing problems, but to discover new problems, invisible opportunities, and nonlinear paths.
Because, in the end, the important question is this:
Is your organisation building a complete brain – or is it leaving half its intelligence out?