How to can we use Generative AI to foster a culture of growth and innovation

In today’s rapidly evolving business landscape, fostering a culture of growth and innovation is more crucial than ever. But let’s not get lost in easy assertions – this is a difficult task, and one that is depends a lot on the people driving that culture, and in the talent that must foster the mindset from every level of the organization. It is also a shared effort that takes time and is, more than directive, about setting up the right examples and turning them into habits. Generative AI is adding something to the mix as well, as it emerges as a powerful and transformative tool, helping organizations to collaborate, experiment, and unlock creative potential. Let me give you my view on three dimensions that forward-thinking companies can harness through generative AI to drive meaningful cultural change.

Breaking Down Silos and Enhancing Collaboration

One of the most powerful impacts of generative AI is its ability to break down traditional organizational silos. Now, these are easy words – let’s try to be a bit more concrete. Gen AI can help you to:

-            setup real-time translation, making easier for everyone to understand what is happening in their own languages;

-            automate meeting summaries, allowing you to, in seconds, send a concise list of what’s been discussed, next steps and actions, deadlines and communicating clear ownership;

-            democratize access to information, making it easier and faster to communicate across teams, departments, geographies and backgrounds.

This is a lot about automating agility of communication – you want to enable a seamless exchange of ideas and different perspectives that accelerates problem-solving and sparks innovation.

Creating a Culture of Experimentation

Innovation thrives in environments where experimentation is encouraged, and failure is seen as a learning opportunity. Earlier, I talked on how Generative AI dramatically lowers the barriers to experimentation by making rapid prototyping and iterative pilots faster and more affordable. This means teams can quickly test new ideas, gather feedback, and refine their approaches – and, if done right, this can have a very positive effect on culture. If you are able to improve ideas better and faster (and killing the bad ones the same way), you are making it cheaper, and lowering the cost of failure – and this setups it up to see failure as part of growth, creating a safe-to-fail environment where creativity flourishes. This shift not only reduces the risks traditionally associated with innovation but also empowers employees to take bold, imaginative steps. Let’s be clear on this, it depends a lot on how you ask the “why”. If after a failure you snarl “why?” you aren’t actually creating this safe-to-fail environment. You need to ask the “why?” in a positive tone, in a “what did we learn from this and how will we use it for better ideas?” way.

Accelerating Design and Optimizing Processes

Generative AI’s ability to automate routine tasks and optimize processes is a game-changer for organizations seeking to maximize their talent – because, let’s be clear, you don’t pay great talent to write reports. By handling repetitive or time-consuming work, AI frees up employees’ time and energy to focus on higher-value, imaginative tasks that drive growth – and that are inherently human. Whether it’s accelerating product design, streamlining workflows, or uncovering new business opportunities, AI enables teams to move faster and think bigger - amplifying both productivity and creativity. The key words here are automation, easier and faster, you want to enable processes at scale that foster your internal processes so your team can focus on higher-value tasks that can deliver differentiated output to the market. So… automate, as much as you can!

Embracing the Future of Work

As generative AI continues to evolve, its potential to foster a culture of growth and innovation will only expand. Organizations that embrace AI not just as a tool, but as a catalyst for cultural transformation, will be best positioned to thrive. By breaking down silos, nurturing experimentation, and empowering talent, generative AI helps create workplaces where innovation is not just possible, but inevitable. But we should keep in mind that culture is not only about tools, but especially about mindsets – Gen AI can only bring transformation if everyone is committed to it, not through orders and speeches, but with actions, examples and incentives.

Future thinking

 I recently embarked on a journey of future thinking learning, understanding the models, techniques and frameworks that enable us to think 10 years into the future, but also on how to stretch creativity and imagination linked to the signals we already have on how that future might be. I believe the future is a great tool to build the present. Because we don’t necessarily want to understand how the future will be, we actually should want to think about the future in order to figure out how we want to make things different, how to innovate or change – and how we need to do that nowadays to impact the future.

 

“When it comes to thinking about the future, it’s far more important to be imaginative than to be right” – Alvin Toffler. Because the future is still probabilistic, and we want to influence it to become better.

Total Economic Value

 Warning, slightly technical post coming.

If you own rural property, especially if that is a forest, you should pay special care at its value – and remind it as the season to prevent forest fires is drawing to an end. And for that, the Total Economic Value (TEV) framework offers a comprehensive perspective for understanding the full suite of benefits forests provide - not just timber or land, but also carbon sequestration, water regulation, recreation, and cultural values. And it helps you to consider the aggregated value of each of these dimensions.

By incorporating TEV into their valuation considerations, forest owners can better capture the true worth of their land, making informed decisions that reflect both market and non-market benefits. This approach not only supports sustainable management but also strengthens the case for conservation investments and responsible stewardship, helping you to understand now the future of forests as a full asset – and, maybe even, to start generating part of that value in the present.

From a sustainability perspective, and as global attention shifts toward ecosystem services and natural capital, recognizing the total value of forests is essential for ensuring their protection and long-term prosperity – so, aligning sustainability to economic and financial values. If each forest landowner recognizes the broader perspective on forest value (now and potential), than it will be easier to ensure both economic returns for landowners and ecological resilience for future generations.

Renewables as the 21st century energy

As we navigate the energy transition, the economic advantages of renewable energies are becoming undeniable, especially when compared to fossil fuels – and I would (maybe boldly) say that this is like comparing 21^st and 19^th century-developed technologies. Both technology systems have very different economic and financial playbooks, with renewables typically requiring bigger capex, but then with considerable advantages when we look at operational costs at scale – I have seen figures that point out to less than half of fossil’s operational costs per MWh. It’s also worth noting that R&D focus on renewables has also been driving capex requirements down – and this is expected to keep on going for, at least, the next couple of decades. Renewables also offer long-term savings by eliminating fuel costs and reducing exposure to price volatility, while fostering energy independence.

 

Let’s not downplay fossil. Fossil fuels were instrumental in powering industrial growth during the 19th and 20^th centuries, and are a proven and tested technology, easy to implement and to run – and that probably plays a lot on the importance of coal on today’s energy grids (and, by the way, they are independent from the weather and day/night transitions). But their finite nature, higher operational costs, and reliance on volatile markets present significant challenges today (and I am leaving environmental external costs aside, on purpose). Renewables, on the other hand, are abundant (virtually infinite), with lower opex and aligned with modern economic priorities like energy security and electrification.

 

On the long-run, and at scale, it’s probable that fossil fuel-based economies will be facing a significant economic disadvantage when compared to the ones that combine renewable sources and smart-grids. What I am saying here is that it is foreseeable that products produced under fossil fuel-based systems will be naturally more expensive. And so, that economies that are not already transitioning to renewables (and that are trying to protect their fossil fuel systems through state sponsored initiatives) will probably be playing in an uneven (against them) field in the medium term.

 

Prioritizing renewable energy solutions is not only an environmental and quality of life imperative but a smarter economic choice for the future. The shift to 21st-century energy is here – so, let’s embrace it!

Professor Mark Fritz on Leadership

Today I was lucky enough to be at a conference listening to Mark Fritz about leadership (courtesy of IE Business School and PwC Portugal), and there were a couple of messages that came through as especially important:
- the importance of driving clarity of objective, target and purpose to the team, in order to empower them to own the outcomes;
- that leadership is a lot more about asking than telling
- and that as a leader, one of your roles is that "your how is who" - meaning, you know the objective, you need to find the right person to do the job.

But then, there was another snippet - a quick sentence Mark said, jokingly, but that, for me, is a true statement about companies social cultures:
- "Great leaders share their weaknesses because their people already know them".

Do you share your weaknesses - or do you let your teams find them out by themselves and own your narrative? 

On diversity and inclusion

I think there is a strong misconception going on in some circles. Diversity and inclusion in business is not about justice. Well, it actually is, but only partially. Diversity and inclusion is also about making sure we all have equal ground, the same opportunities, smoothing biases, to let the best talent come forward.

And the best talent is the one that will do a better job. Perform the best. Generate more value. Create more value for the company and shareholders. Make a business more successful.

So, what I am saying here is quite simple. If you let biases come in the way of your talent development and team building, your business won’t be as successful. Period.

Now, it’s your turn to choose what you want.

How to use Gen AI to get early feedback on prototypes

When developing an innovative product, getting early feedback from your target personas is critical to refining your prototype (whether physical, digital or even a communication asset). AI tools can help you with this, by giving you early and quick feedback at an early stage. They can help you simulate user interactions and identify usability issues before involving real users. This approach not only saves time but provides actionable insights to improve your design early on. How do you do it? Well, with “people” of course!

So, you start by creating detailed personas that reflect your target audience – and knowing your target is always the secret. With Gen AI, you can generate dynamic personas by feeding it demographic details, behaviors, goals and pain points. For example, you might ask ChatGPT to create a persona for a busy parent who struggles with meal-planning – be as detailed in the arguments you throw to the AI model as you can and demand it to generate a persona as complete as possible. These personas form the foundation for realistic simulations that mimic how users might interact with your prototype.

Then, input your prototype directly into the AI model by uploading screenshots, wireframes, or even interactive mockups (alternatively, if your model can’t analyze visuals directly, describe them in words). The model can analyze these visuals and simulate interactions step-by-step. For instance, if you’re testing an e-commerce site, upload images of the homepage, product pages, and checkout flow. Assign a goal - like purchasing shoes - and let the AI simulate how different personas navigate through the process. Its recognition capabilities allow it to identify usability issues such as unclear buttons or confusing layouts.

Don’t’ stop there. To uncover friction points, introduce challenges or ambiguities in the prototype and ask the AI to respond as the persona would. For example, you might upload a product page with a poorly placed “Add to Cart” button and ask how this affects the persona’s experience. The AI can then analyze spatial relationships within the image and provide feedback like: “The button is too small and located far from the product description - it’s easy to miss.” This level of detail helps pinpoint design flaws early, so you can correct them fast.

Finally, use these insights to iterate on your design and test again with refined visuals. And do it over and over again, always changing your prototype, accommodating feedback, testing different solutions or dimensions. Because this is the point – Gen AI’s ability to analyze updated prototypes ensures you’re continuously improving usability based on actionable feedback. Of course, it is not perfect, but this process allows you to give an efficient first step in identifying issues before real testing begins. The goal of this early loop is not to get it right, but to get it better before you start testing with real people, accelerating the process and making it cheaper.