Site icon Modeling reality, generating software

Creation and Innovation in the Age of AI

Gabriel Simonet
Creation and Innovation in the Age of AI

Artificial Intelligence (AI) is redefining how we create everything — from medicines to software and even businesses.

Artificial Intelligence (AI) is redefining how we create everything — from medicines to software and even businesses.

For decades, creating a product and using it were two separate processes. First, we would design, develop, deploy, and refine something; then, we would put it into the hands of users. There was a large gap between the moment of creation (engineering) and the moment of use (users).

Over time, this gap began to shrink. Platforms like GeneXus brought creation closer to use, enabling people without engineering backgrounds to develop software.

Later, No-Code tools gave users the ability to build and use increasingly sophisticated systems in just minutes.

This phenomenon of convergence between creation and use is not new, but AI — particularly Generative AI, or GenAI — is taking it to an entirely different level. Now, AI is not only present at the moment of creation but also actively participates during use. In fact, we have been talking about this creation-use convergence for some time now.

This transformation not only redefines how we design, build, and experience software, but it’s also impacting physical, digital, and even analog products. A perfect example is AlphaFold, DeepMind’s AI that won a Nobel Prize for predicting protein structures with unprecedented accuracy.

But this change goes beyond technology: business models are also being redefined by this convergence. Less and less specialized or technical knowledge is required to bring ideas to life because AI is solving more and more parts of what we want to accomplish. This, in turn, accelerates innovation across all sectors. From healthcare to commerce, industries are innovating with AI, removing the friction between ideas and execution. We are in a moment where ideas, vision, and goals seem to be gaining value, while execution itself becomes easier than ever before.

We are experiencing a new — and much more intense — relationship between humans and machines, with an unprecedented level of collaboration, where artificial intelligence enhances human creativity and imagination, and productivity skyrockets like never before. It’s a paradigm shift that is transforming not only how we work but also what we are capable of creating.

If I had to summarize, I’d say AI is having massive implications in the following areas:

It allows anyone to create customized solutions and new products without requiring advanced technical knowledge.

It removes the friction between idea and execution, driving transformation in sectors as diverse as healthcare and commerce.

It redefines the relationship between humans and machines, fostering hybrid teams and agile processes.

In this article, we explore the new opportunities AI is opening up, how it’s transforming entire industries, and what we need to consider to leverage it strategically.

1. The New Era of Creation: Opportunities That Didn’t Exist Before

As with every new technological revolution, most of what we’ve done with AI so far is simply speed up what we already knew how to do: optimize processes, automate or accelerate tasks, and improve efficiency. But AI is enabling something entirely different: creating new types of solutions that were previously impossible.

Why? Because AI has learned the language of the world. Before, if we wanted software, we had to code it line by line. If we wanted to analyze data, we had to design specific algorithms. If we wanted a photo, diagram, or painting, we needed human experts in those fields. Now, AI translates between domains, allowing it to convert images into words, transform text into code, text into images, images into text, audio into video, and even detect and analyze patterns that were previously invisible to us.

This ability has opened up completely new spaces. It’s not just about speeding up the work that used to require experts — it’s about enabling things that were simply impossible before.

Companies like Insilico Medicine are using generative AI to design new molecules with therapeutic potential, accelerating drug development at unprecedented speeds.

In business, tools like Vellum AI are redefining how companies discover opportunities and make strategic decisions.

Today, organizations can simply ask a natural language question and receive actionable insights in seconds.

We also see examples in education: with the arrival of AI assistants like Khanmigo from Khan Academy, students now have AI tutors that adapt in real time to their learning pace and style, providing personalized explanations and adjusting content based on their level of understanding. It’s like having custom, one-on-one tutoring.

With Globant Enterprise AI, ecosystems are being built where AI agents can integrate at the enterprise level to solve countless problems — from bug fixing to automatic use case definition, testing, and even addressing previously intractable challenges like Legacy System modernization. Today, AI can read legacy code, interpret the logic the original programmers intended, and automatically generate optimized versions using modern technologies.

It’s clear that the key question is no longer
“How can we do this faster or more efficiently?”
, but rather
“What can we do now that was impossible before?”
As Nicolás Jodal (CEO of GeneXus) said, there are new areas of interest that once seemed irrelevant, but now they are viable and attractive thanks to AI. It’s essential to seek out those new opportunities enabled by AI.

Entrepreneurs and companies that understand this new reality will discover entire markets and opportunities that don’t even exist yet. AI isn’t just another technology — it’s the first major platform capable of creating what was previously unthinkable, either because it was technically impossible or we lacked the means to make it happen.

2. Traditional Interfaces Are Disappearing

For decades, interacting with software meant clicking on menus and buttons within a graphical interface. Now, conversation is replacing traditional interaction. Previously, generating a financial report required navigating spreadsheets and applying formulas manually. Today, you can simply write — or in some cases, say —
“Generate the 2024 financial report,”
and AI finds the information, performs the calculations, and displays the result — in whatever format you request — in seconds.

This is a radical shift in the types of interfaces we are used to.

Not only does this make software more accessible, but it frees professionals from mechanical tasks, allowing them to focus on strategic decisions. It also invites us to rethink what kinds of touchpoints will exist between users and data, and how users will interact with AI at those touchpoints — which leads to the next point.

3. It’s Not Just About Adding AI, It’s About Rethinking Software from Scratch

Many companies are adding AI features to existing products, but the real change isn’t in adding features — it’s in rebuilding software from the ground up to take full advantage of AI’s potential.

AI plays a crucial role in this rethinking and reconstruction of software because AI opens new doors:

The traditional software development model is being left behind, replaced by a new approach:
“Describe what you want and let AI create it.”

4. Business Logic is Being Simplified

Historically, developing business solutions meant translating business rules into lines of code. Now, AI allows organizations to define objectives in natural language, and the AI handles everything necessary to execute them — including building the business rules themselves.

For example, a financial company could implement an AI agent that automates credit approvals, considering risks and historical data patterns, without anyone needing to write algorithms, rules, or business logic. The AI can rely on the company’s prior experiences or even industry-wide knowledge.

This shift means that corporate knowledge and industry expertise — stored in information systems or other recoverable formats — is gaining new value thanks to AI. The quality of this knowledge base will directly impact our ability to make the best decisions in partnership with AI.

5. Backends Are Fading into the Background

It’s not just that AI is pushing various aspects of system generation into the background — even the backends we used to interact with constantly are becoming increasingly invisible. AI agents can orchestrate the access and recording of information, completely separating users from backend systems.

For example, imagine a retail business with an AI agent that, when a customer places an order, automatically syncs inventory, predicts product demand, and recommends stock adjustments — all without the user ever directly touching the software.

It’s becoming easier for users — but make no mistake, the objective information systems, such as databases, still exist. We just see them less, but they are still there.

6. Specialized Niches Offer Huge Opportunities

While large companies like OpenAI, Microsoft, and Google create general-purpose tools, there’s a massive opportunity for solutions tailored to specific industries.

Companies don’t want a generic AI model or agent. They want AI that understands their unique processes and delivers real value in their business context. These solutions may come from developing Small Language Models (SLMs), fine-tuning existing models, or optimizing retrieval-augmented generation (RAG) systems with proprietary data. While training models, even small ones, is still expensive, fine-tuning and RAG optimization (known as SRAGs) can yield high-quality results, even in information-scarce domains.

Companies that develop specialized niche AI products will gain a competitive advantage over larger companies, which cannot customize solutions for every niche.

7. New AI-Powered Business Models

AI is also transforming how companies generate value and monetize their services. Traditional business models, based on product sales or fixed subscriptions, are evolving into more flexible, dynamic approaches where AI plays a key role.

As AI becomes more capable of making decisions, automating processes, and adapting in real time, entirely new business models are emerging:

Some startups are building businesses with extremely small operational teams, where AI enhances human capacity. This goes beyond simple task automation — AI assists with marketing, sales, customer service, product development, and operational optimization.

Previously, knowledge was sold through books, courses, or consulting. Now, AI allows knowledge to be delivered on demand and personalized. AI models trained in specific fields can provide expert advice, advanced content creation, and real-time strategic decision support.

AI allows companies to shift from charging for products or subscriptions to charging for concrete results. Instead of charging a flat fee, companies increasingly monetize based on the value generated for the customer. While this isn’t possible with all clients (due to regulations or internal policies), it’s becoming more common.

AI is also driving a shift toward pay-as-you-go models, where companies only pay for the computing resources they actually use. This offers greater flexibility, optimizes costs, and is ideal for environments with variable workloads.

8. AI Agents: A Key Differentiator

AI isn’t just accelerating the creation of software, products, and business models — it’s enabling an even deeper evolution: the rise of AI Agents. While there’s no universally accepted definition of AI Agents, we can think of them as abstractions representing various levels of autonomous systems capable of interacting with their environment, systems, and tools, learning, adapting, and executing tasks.

In the context of the creation-use convergence, AI Agents represent the new frontier of intelligent automation. It’s no longer just about building tools to perform specific tasks — it’s about developing agents that understand complex contexts, optimize processes in real time, and actively collaborate with humans on strategic decision-making.

How Can We Seize This New Opportunity?

Once again, the key question companies and entrepreneurs should be asking isn’t
“How can we do this faster or more efficiently?”
, but
“What can we do now that was impossible before?”

Adopting AI isn’t just about integrating new tools — it’s about rethinking from first principles (Principles First). To paraphrase John Reed in
Succeeding
, real success doesn’t come from blindly following technology trends, but from understanding the fundamental principles that govern market evolution and designing strategies aligned with them.

In this case, there are three key principles that should guide AI adoption in any organization:

AI should free up time and resources, but without losing the core essence of the business and human creativity. It’s not just about doing more with less — it’s about doing what truly matters better, without losing our identity.

Implementing AI without a clear vision will backfire. The companies that lead this shift will be the ones that first understand their purpose and mission, and then use technology to amplify them — not the other way around.

AI has the potential to make software more intuitive and accessible — even invisible — pushing technical complexity into the background.

At GeneXus, we continue to simplify software development so that more people can explore these opportunities and build the software of tomorrow today.

The road to an AI-powered future won’t be easy for anyone. We’ll have to learn how to use AI while also understanding how the rules of the game are changing and discovering how we can apply AI to our own core principles. Only by doing this can we lead the next era of creation and innovation in our industries.

The challenge is great — but the opportunity is unique.

You may also be interested in reading:

What is Globant Enterprise AI?

What is GeneXus?

DeepSeek: An unexpected yet inevitable disruption

What is GeneXus used for?

Exit mobile version