Kevin Janzen, CEO of Gaming & EdTech AI Studio at Globant, on how AI will change the way games are made and expand the market

Every major games studio is now experimenting with artificial intelligence. From generating NPC dialogue to automating animation and video assets. AI is promising to speed up production and lower costs for developers.

According to Boston Consulting Group (BCG), the gaming industry finds itself at a crossroads…. Looking to gain the momentum it felt between 2017 and 2021, where revenue surged from $131 billion to $211 billion. And AI could be at the forefront of this pivotal moment. 

But as AI becomes central to how games are built, studios face a major challenge. Adopting automation without losing authenticity. For developers and retailers alike, this becomes a business concern that deserves close attention. Creativity sits at the heart of gaming, and the choices studios make today will influence what reaches players tomorrow. For the technology channel, this transformation means faster release cycles, broader product diversity, and a need for sharper forecasting.

A New Phase in Gaming’s Evolution

For most of gaming’s history, every era has been defined through visuals. Each generation has delivered stylistic, immersive worlds, such as the blocky charm of Minecraft to the cinematic realism of Red Dead Redemption 2. 

Now, the real change is happening behind the scenes. AI is reshaping how games are built and experienced. Development teams are using AI to handle time-consuming tasks such as vast world-building creation and animation. This frees artists to focus on what players remember – the design and storytelling.

Players are already seeing the benefits in their gameplay. AI lets games adapt or adjust difficulty based on players’ skill levels, or change dialogue based on a player’s choices. This makes gaming worlds feel realistic, responsive and more personal.

With budgets continuing to climb for gaming studios, these new features matter. AI gives studios breathing room to experiment. Smaller teams can take creative risks, and established developers can experiment and test new ideas without derailing production. However, efficiency and costs aren’t the only gains as AI is creating space for developers to be more ambitious than ever before.

Automation and Artistry

For all its promise, AI also brings creative risk. Gamers notice when a quest feels repetitive or when dialogue sounds mechanical. And if AI is used carelessly, developers risk losing authenticity.

That sense of care is what keeps players invested. Whether it’s hand drawn detail, or play-driven choices. Games like this show what happens when technology supports vision rather than replacing it.

That’s why the industry’s embrace of AI is such a gamble. Used well, AI can help developers create richer, more personalised worlds. But used carelessly, it risks stripping away the artistry that makes games memorable.

The Ripple Effect Across the Supply Chain

As AI becomes a standard tool, development processes are speeding up and opening new creative possibilities. Independent studios now have access to the kind of production power once limited to major developers. That shift means faster pipelines and ultimately, more games reaching the market.

For retailers and resellers, this brings both opportunity and pressure. A consistent stream of releases can guarantee sales across the year, while lower production costs encourage more niche or experimental games that appeal to new audiences. Greater variety and volume benefits the market, but it also makes it harder to predict which games will break through.

Players are becoming more aware of how games are made and AI’s role in development. They’re starting to ask not only how a game plays, but also how it was built. Understanding the intent behind a studio’s use of AI – one that uses AI as a genuine creative tool and those that rely on it as a shortcut – will help retailers anticipate demand and spot the games with long-term potential.

The Right Way to Play the AI Game

The studios using AI most effectively have a few things in common. They keep AI in the background, using it to manage routine work, such as generating textures and landscapes, so creative teams can focus on narrative and emotional tone.

They also use AI to make experiences more personal. Thoughtful application of adaptive systems allows games to respond to individual play styles, adjusting difficulty and pacing to keep players engaged. This level of design deepens engagement and gives players a sense that the world responds to them personally.

Another area where AI is also making an impact is making games more inclusive. More than 400 million people around the world play with a disability, and new tools are expanding access – from adaptive controls to real-time translation that lets players connect across languages. As gaming becomes more diverse, the audience grows for everyone, including retailers, who can reach a larger, more engaged customer base.

When automation complements gaming artistry, it strengthens the relationship and trust between the developer and the player. Creativity becomes the main focus again, and that’s what keeps players loyal.

Balancing Innovation and Trust

AI is fast becoming integral to how games are conceived, built, and experienced — and that shift will reshape the entire value chain. For developers, success will come from balancing automation with artistry, ensuring that AI enhances creativity rather than replaces it.

For retailers, distributors, and partners, this transformation offers both opportunity and responsibility. A faster, more diverse release pipeline will bring fresh sales potential, but also greater complexity in forecasting and curation. The winners in this new phase of gaming will be those who can spot titles where AI adds genuine depth, inclusivity, and player connection — not just production speed.

Handled thoughtfully, AI won’t just change how games are made, it will expand the market for everyone involved in bringing those experiences to players. That’s a game worth playing for the entire tech channel.

Learn more at globant.com/studio/games

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Dr Antoni Vidiella, CSO of Financial Services at Globant, on why the next stage of AI in financial services depends on modernising the legacy systems that still underpin banking and FinTech

Many financial service institutions are now moving beyond simple automation and exploring how to embed artificial intelligence across every layer of their operations, from payments and compliance to customer engagement. As banks and FinTechs continue this shift, the sector is entering a new phase in which real-time intelligence, connected data and adaptive systems will define competitiveness.

Yet unlocking this value requires far more than the introduction of new AI tools. To turn data into meaningful business intelligence and to enable new growth models in digital finance, financial institutions must modernise the systems at their core. Without strong foundations, AI cannot scale effectively or operate in a responsible, transparent or secure way. The potential may be vast, but the path to achieving it begins with the fundamentals.

The Challenge of Legacy Systems

Like many other industries, financial institutions still rely on architectures that were built decades ago. These systems continue to support essential functions such as payment processing and risk modelling, yet their rigidity and fragmentation severely limit the potential of AI. Information remains scattered across mainframes, cloud platforms and on-premises databases. As a result, the data required to train and operate modern AI systems is often incomplete, inconsistent or inaccessible in real time.

This fragmentation reflects a deeper structural issue. Many core banking systems were designed around periodic or batch processing. Fraud detection, credit assessment and compliance monitoring therefore remain reactive, even as customer expectations shift toward instantaneous experiences. The consequence is a widening gap between what AI can theoretically deliver and what institutions can achieve with the infrastructure they currently have.

The scale of adoption shows how urgent this challenge has become. A 2024 study by the Bank of England and the Financial Conduct Authority found that 75 percent of UK financial services firms already use AI, with a further 10 percent planning adoption within the next three years. Yet research in 2025 by Lloyds Banking Group indicates that while institutions are beginning to see gains in productivity and customer experience, many acknowledge that their underlying systems are not ready for the next stage of AI maturity. The ambition is there, but the technical foundations remain uneven.

Modernisation as the Foundation for Scalable, Trustworthy AI

Modernisation represents the most significant step institutions can take to prepare for the intelligent financial systems of the future. Moving to cloud-native architectures, adopting microservices and improving data quality all make it possible to activate AI across an organisation rather than in isolated pilots. These shifts also make the resulting systems more secure, more transparent and easier to govern.

Importantly, modernisation is no longer the slow, resource-intensive process it once was. AI-assisted approaches have transformed what is possible. Automated code analysis, conversion and validation can reduce modernisation timelines dramatically. In one example, more than 11,000 lines of legacy COBOL code were migrated to modern Java services in only 105 hours, a task that would traditionally have taken several months. These advances illustrate how quickly institutions can begin creating the environments required for real-time intelligence.

The global opportunity reinforces the need for speed. AI adoption in banking is accelerating rapidly, with institutions racing to modernise their systems and unlock new operational efficiencies. Those that move first will capture the earliest benefits and operate with a level of agility that older architectures simply cannot match.

How Intelligence is Reshaping Payments and Embedded Finance

Payments provide a clear view of how AI is transforming the financial landscape. As digital transactions grow in both scale and complexity, the industry needs systems that can act instantly and intelligently. AI models can analyse behavioural patterns in real time, reducing false positives in fraud detection and strengthening overall resilience. They can also optimise transaction routing, identifying the most efficient or cost-effective paths in ways legacy systems are not equipped to handle.

These shifts extend beyond payments. Embedded finance is becoming a central feature of retail, mobility, insurance and platform-based services. As the ecosystem expands, it will rely heavily on AI to offer tailored credit decisions, contextual payments and adaptive insurance coverage. These capabilities require unified, real-time data environments that can only be delivered through modernised core systems. Without this foundation, the benefits of intelligent payments remain out of reach.

The Essential Role of Responsible Innovation

As AI takes on a larger role in high-impact financial decisions, responsible innovation becomes a defining priority. Trust must be maintained at every stage of the customer journey. Findings from the Bank of England and the FCA show that 55 percent of AI systems in UK finance involve some form of automated decision-making, though very few operate without human oversight. This balance reflects a clear need for systems that are transparent, explainable and accountable.

Responsible AI requires more than good intentions. It depends on strong governance frameworks, rigorous monitoring for bias and clear visibility into how decisions are made. It also relies on consistent, well-managed data. Modern cloud-enabled infrastructures make these practices more achievable, allowing institutions to meet regulatory expectations while building customer confidence. Legacy systems, by contrast, make responsible innovation significantly harder to sustain because they lack the transparency and control required for effective oversight.

How GenAI is Reshaping Operations and Customer Experience

Generative AI expands the possibilities for transformation even further. In customer engagement, GenAI enables natural, personalised interactions that respond to customer needs in real time. It can simplify onboarding, deliver proactive financial insights and support customers throughout complex journeys without compromising clarity or accuracy.

Within operations, GenAI reduces the administrative burden that regulatory compliance often creates. It can summarise complex legislation, draft documentation and support audit processes far more efficiently than manual methods. In product development, it helps institutions test new ideas, model risk scenarios and understand customer behaviour more quickly, reducing time to market and increasing innovation capacity.

However, all these capabilities rely on a consistent and reliable data environment. GenAI cannot deliver meaningful insights if the data underpinning it remains fragmented or outdated. The quality of the output will always reflect the quality of the foundations beneath it.

Building a Resilient Path to Long-Term Innovation

Modernisation is frequently described as a technical necessity, yet its impact is far more strategic. Institutions that invest now will be better equipped to integrate new technologies, respond to regulatory changes and develop AI-enabled products with greater precision. They will also be better positioned to enhance the customer experience, which increasingly depends on real-time intelligence and personalised insight.

Most importantly, modernisation elevates human expertise rather than replacing it. AI supports judgement, strengthens decision-making and frees teams from manual tasks, allowing them to focus on the relationship-building and strategic insight that define successful financial services.

Creating the Intelligent Financial Institution of the Future

Financial services are entering a new era shaped by real-time intelligence, interconnected digital journeys and deeply personalised experiences. Achieving this vision requires modern, resilient systems that can support advanced AI and GenAI. Institutions that begin modernising now will lead the next decade of innovation and create financial ecosystems that are more adaptive, more secure and more connected than ever before. The future is intelligent, but it can only be built on strong foundations.

Learn more at globant.com

  • Artificial Intelligence in FinTech
  • Digital Payments
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