Introduction

Generative Artificial Intelligence (GenAI) is redefining the business landscape. It is no longer just a technological innovation - it is the strategic tool driving new ways of operating, competing, and innovating across all industries.
While personal use of AI tends to be spontaneous, companies integrating GenAI are doing so strategically to enhance efficiency, reduce costs, and accelerate innovation.

Today, 78% of organizations are already leveraging AI in at least one key business function, with sectors like legal and finance experiencing rapid adoption growth.

In this whitepaper, we show how startups and multinational companies around the world are using GenAI to reshape their reality in 2025, through practical examples that can inspire the future of your organization.
 

What is Generative AI?

Generative AI is a type of artificial intelligence capable of creating new content from large volumes of data. This includes everything from text and graphics to music, video, code, or new product designs.

Unlike traditional AI, which only analyzes or predicts, GenAI can imagine, simulate, and build solutions—areas previously reserved for human creativity.

Why is it crucial today?

• It turns complex data into fast and accurate decisions.
• It enables the creation of personalized campaigns, products, and processes.
• It speeds up tasks that used to take days, enhancing quality and productivity.

 

Industry Sectors and Key Applications in 2025

 

Industry	Notable GenAI Applications (2025)
Healthcare	- Clinical assistants and medical scribes that draft notes, saving thousands of hours for doctors. - AI-assisted diagnostics (summarizing scans and image analysis). - Accelerated drug discovery with AI-generated molecules. - 24/7 health chatbots. - Personalized genomic analysis.
Finance	- Virtual assistants for bankers and clients (data summaries and personalized advice). - Automated report generation and risk analysis. - Real-time fraud detection. - 24/7 banking chatbots. - Portfolio optimization using generative models.
Education	- Personalized AI tutors for students (e.g., Khanmigo). - Adaptive educational content generation. - Automated grading and instant feedback. - Virtual lab simulations. - Chatbots for practicing languages and subjects.
Media and Entertainment	- Automated writing of articles and news summaries. - Creative assistance for scripts and audiovisual content. - Video games with NPCs that improvise dialogue. - Generation of music, images, and concept art. - Synthetic voice dubbing in multiple languages.
Manufacturing	- Generative product design (e.g., BMW car parts 30% lighter). - Predictive maintenance (20% reduction in unplanned downtime). - Digital twins of factories and supply chains. - AI-powered automated quality control.
Legal	- Review and generation of legal documents. - Virtual legal assistants and chatbots. - Intelligent search for case law and precedents. - Automated legal support for clients. - AI integration in law firms (26% already using it, 45% adopting soon).

 

Success Stories Leading the Way

Across industries and geographies, Generative AI is proving that there are no limits when strategically integrated into operations. Explore some of the tangible results already transforming the business world:
 

Healthcare Sector

In healthcare, Generative AI is used both to automate administrative tasks and to drive clinical and research breakthroughs:

• Clinical Documentation and Physician Support

Medical scribes assist doctors and other healthcare professionals by documenting clinical information in real time during consultations, exams, or procedures.

Today, thanks to Generative AI, AI-powered medical scribes are significantly reducing the paperwork burden.

In a U.S. hospital system, AI scribes that record doctor-patient conversations and draft clinical notes saved physicians 1,794 workdays in a single year - nearly five full-time work-years- dramatically cutting time spent on medical records and improving communication with patients. The study, which examined administrative workload, physician satisfaction, and patient satisfaction over a 63-week period, showed that AI saved physicians time, allowing them to focus more on patient care during consultations.

Tools like Abridge and DeepScribe, , based on generative language models, listen to consultations and automatically generate structured summaries for medical records, freeing doctors from typing lengthy notes. This reduces professional burnout and increases satisfaction for both doctors and patients.

• Medical Imaging and Clinical Analysis

In radiology, advanced AI systems analyze X-rays, CT scans, and mammograms, identifying subtle patterns that might otherwise go unnoticed. For example, AstraZeneca trained AI assistants capable of automatically detecting 3D lesions from CT scans, reducing the need for radiologists to manually annotate each image.

In India, institutions like Apollo Hospitals partner with Google Health to conduct large-scale disease screenings. Using generative computer vision algorithms, they detect early signs of tuberculosis or breast cancer, expanding diagnostic capacity in regions with few radiologists.

This technology has enabled the analysis of over 3 million studies in just a few years, significantly improving early detection in large populations with limited access to specialists.

• Drug Discovery and Personalized Medicine

The generative ability to simulate and propose new molecules is revolutionizing pharmaceutical research. Models like AlphaFold, which predicts protein structures, laid the groundwork for this transformation. Today, pharmaceutical companies use generative AI to design drug candidates.

AstraZeneca, for instance, reported expanding its use of these tools to accelerate its R&D pipeline. The company estimates that AI could reduce the time from identifying a therapeutic target to obtaining a clinical candidate by 30% to 50%. It has also developed AI assistants that help extract insights from complex clinical documents and create intelligent prototypes of trial protocols, which are integrated into the daily work of its scientific teams.

In the field of personalized medicine, generative systems analyze genetic and clinical data to suggest treatments tailored to each patient. At Mayo Clinic, for example, AI models are used to design oncology treatment plans personalized to each case, optimizing outcomes and reducing side effects (according to internal reports cited in the industry).

• Patient Care and Health Chatbots

Many healthcare institutions have implemented conversational chatbots to guide patients. These assistants, in some cases powered by advanced models like GPT-4, answer symptom-related questions, provide basic guidance, and help schedule medical appointments.

In Latin America, for example, some clinic networks use bilingual AI bots for initial triage and to provide pre-consultation information, helping to reduce phone line congestion.

A particularly noteworthy case in the public sector is Colombia’s Safety Council, which developed a generative AI chatbot to improve data analysis and emergency response to chemical incidents. This tool has enabled faster and more effective responses to critical situations, demonstrating how even governments are adopting AI solutions to strengthen key public health missions. You can find more details in the report 601 Real-World Generative AI Use Cases from Leading Organizations Worldwide..
 

Finance Sector (Banking, Investment, and Insurance)

The world’s most innovative financial institutions are leveraging this technology to launch hyper-personalized products, create unmatched customer experiences, and achieve unprecedented levels of operational efficiency. This progress isn’t confined to a single region:
 

• North America leads with multimillion-dollar investments and large-scale deployments.
• Europe is using AI to meet complex regulations while ensuring security and transparency.
• Asia-Pacific is setting adoption records, with China at the forefront thanks to massive AI integration in mobile payments and financial Super Apps.
   

The opportunities unlocked by this technology are extraordinary. According to IBM, Generative AI increases revenue, reduces costs, and drives a strategic, cross-functional transformation that strengthens the competitive position of institutions.

Today, those proactively implementing Generative AI are already enjoying tangible advantages:
 

• Streamlined and automated processes.
• Better managed risks.
• More satisfied and loyal customers.

Below, you’ll discover the key use cases already revolutionizing the financial sector—ones that will define the difference between leading the market… or falling behind.
 

• Wealth Advisory and Management

In the world of wealth management, Generative AI is revolutionizing the standard of service and responsiveness to market volatility. Major investment banks have realized that in times of uncertainty, speed and precision are everything.

A clear example of leadership is JPMorgan Chase, the largest bank in the United States - and one of the largest in the world - which has radically enhanced the value it offers to high-net-worth clients. Thanks to its advanced Generative AI tools, JPMorgan advisors can:
 

• Instantly analyze the composition of any portfolio and detect relevant trading patterns.
• Anticipate clients’ most likely questions and have key data ready to respond swiftly and confidently.
• Provide real-time personalized investment recommendations—even during periods of extreme financial turbulence.
   

The result? JPMorgan saw a 20% increase in gross revenue between 2023 and 2024 directly attributed to its strategic use of AI, and now plans to expand its client base by 50% over the next 3 to 5 years, driven by this transformative technology.

And they’re not alone. Goldman Sachs has developed a generative assistant that enhances decision-making for its bankers, traders, and asset managers. Meanwhile, Morgan Stanley, in partnership with OpenAI, launched an internal chatbot that enables advisors to instantly access key documents and information.

The speed, accuracy, and personalization that AI brings to wealth management is becoming the new gold standard. Today, an advisor can scan all the day’s relevant financial news and deliver customized summaries or insights to each client in minutes—building trust and loyalty like never before.
 

• Customer Service and Retail Banking

Today, millions of people enjoy intelligent chatbots capable of answering inquiries, facilitating transfers, and resolving questions in natural language - anytime, anywhere.

In Asia, pioneering digital banks are making a difference by offering 24/7 service in multiple languages and contexts, breaking down traditional barriers and exceeding expectations.

But the revolution doesn't stop there. In India, leading insurers like HDFC ERGO have gone even further by launching AI-integrated Super Apps.

A standout example is the 1Up app, which uses Vertex AI to assist insurance agents with intelligent “nudges” - contextual and personalized recommendations for the next best action during new client onboarding. This makes every interaction faster, more efficient, and significantly more relevant.

Additionally, thanks to advanced data analysis on platforms like BigQuery, these companies can now offer products perfectly tailored to each customer’s location and needs. The result is a seamless, frictionless experience that not only satisfies users but also multiplies sales and loyalty opportunities for the business.

In the new banking landscape, those embracing Generative AI are defining the standard of excellence and bringing the financial future closer to every user.
 

The Assistant of Assistants: How an insurer improved customer service with Gen-AI (read this success story)

 

• Fraud Detection and Risk Analysis

In the fight against financial fraud and money laundering, Generative AI has become the most powerful ally for banks and insurers.

Large Language Models (LLMs) can analyze massive volumes of transactional data and detect anomalous patterns with extraordinary precision.

By 2025, compliance departments have taken a qualitative leap: AI now identifies potential fraud and generates explanatory alerts for analysts, detailing why a transaction is suspicious.

This capability allows human teams to focus on truly critical cases, reduce false positives, and dramatically accelerate investigations.

Moreover, global banks are using AI to simulate financial stress scenarios and generate risk reports written in natural language. This enables executives to understand and act on complex risks without having to decode endless technical documents.
 

• Internal Process Optimization

In back-office departments, routine tasks such as document processing, drafting customer responses, or claim analysis are now automated with solutions like Google's Gemini. A standout case is Pinnacol Assurance ((USA), where 96% of employees reported gaining valuable time thanks to AI - resulting in higher productivity and reduced administrative workload.

In the realm of corporate finance, many CFOs already rely on AI to automatically generate reports and projections. A 2025 survey revealed that the vast majority of financial organizations are prioritizing the adoption of GenAI in key functions such as payments, cash flow forecasting, and other critical processes to enhance operational agility.
 

Accelerating Compliance Processes with GenAI (read this success story)  

Education Sector

Traditionally slower to adopt new technologies, the education sector is now experiencing a surge of Generative AI projects - driving a profound transformation in how learning, teaching, and assessment are conducted across schools, universities, and the online learning ecosystem.

The image of education as a tech-lagging sector is a thing of the past. Today, institutions and governments are heavily investing in AI.

Japan and South Korea are leading the shift with national programs that bring AI-powered English tutors to rural classrooms, ensuring no student is left behind due to lack of resources.

In Europe, the European Union is funding pioneering initiatives for "AI-augmented classrooms," ensuring the ethical and responsible development of this technology. Meanwhile, top universities like MIT and Stanford are deeply researching how AI can boost learning outcomes and prepare students for the future.

While debates continue about how to evaluate students in the age of tools like ChatGPT, the consensus is clear: Generative AI enables access to personalized, high-quality education, opening previously unimaginable opportunities for millions of learners.
 

• Tutoring and Personalized Support

The most disruptive advancement is the arrival of intelligent virtual tutors, accessible to any student with an internet connection. Platforms like Khan Academy have integrated GPT-4 through their assistant Khanmigo, offering one-on-one tutoring to practice math, understand difficult concepts, and explore any area of knowledge—all tailored to the individual student.

In addition to providing explanations, these AI tutors adapt their responses to each student’s level, encourage critical thinking, and promote autonomy. Today, any student can receive high-quality help at 11 p.m., breaking down barriers of time and place.

The same is true in language learning: apps like Duolingo offer “Max” plans where chatbots simulate real conversations, correct mistakes in real time, and significantly boost motivation and user progress. The impact? Record increases in retention and engagement - revolutionizing how languages are learned.
 

• Educational Content Creation

Generative AI has freed teachers and instructional designers from the most repetitive tasks. Now, a teacher can generate lesson plans, original exercises, math problems, language dialogues, or essay examples tailored to their students’ level - in just minutes.

In subjects like history or literature, AI helps design debates, quizzes, and customized case studies. Platforms like Quizlet have adopted AI to create interactive study flashcards, while tools like Eduaide generate full lesson plans, greatly expanding the range of available resources.
 

• Automated Feedback and Assessment

Grading is no longer a never-ending task. Tools like Gradescope use computer vision and Generative AI to automatically grade exams and assignments - and explain to students why an answer was incorrect and how to improve it.

Teachers save hours using systems like GPT-4 that summarize essays, identify key ideas, and allow them to focus on creativity and critical thinking..

In programming education, code assistants like GitHub Copilot help students write and refine their projects, and the same AI can evaluate the submitted code - providing immediate, personalized feedback.
 

• Simulations and Virtual Labs

One of the most impactful trends is the generation of simulated environments for hands-on learning. In medicine, for example, AI can create "virtual patients" that interact with the student, who must diagnose and treat based on simulated symptoms.

In physics and chemistry, students can describe experiments and see simulated results explained step by step - all in natural language and without any risk.
 

Media and Entertainment

The media, publishing, and creative entertainment industries have embraced Generative AI both to gain behind-the-scenes efficiency and to innovate in content creation. AI is no longer just a tool - it’s the new muse reshaping how we inform, create, and captivate audiences.

Globally, AI integration in media and entertainment is unstoppable. The BBC is experimenting with automatic multilingual clip generation; Hollywood is debating the role of AI in scripts and effects; and in Asia, K-Pop and AI-generated digital influencers are dominating social media.

While ethical debates persist regarding copyright and the human role in creativity, the reality is that Generative AI has become an everyday ally for journalists, artists, developers, and creatives worldwide.
 

• Journalism and News Writing

In modern newsrooms, Generative AI is the best-kept (and sometimes “shadow”) secret. Over 42% of journalists already use this technology to boost speed and productivity - from transcribing interviews and summarizing statements to translating texts and mining massive information databases. 69% cite efficiency as the main reason for adoption.

Tools like ChatGPT and other models can transform financial reports into publish-ready articles, automate sports and weather results, and even suggest alternate headlines and social media excerpts. While many media companies still proceed cautiously and are crafting internal ethics and verification guidelines, the reality is clear: journalists are already using AI to go further, faster, and in more languages.

AI-supported translators and reporters publish sooner, while editors use it to spark creativity and drive viral content. The result: faster, multilingual, and more engaging news for a global audience..

Still, formal adoption is cautious: many newsrooms are developing internal guidelines for AI use - focused on ethics, fact-checking, bias avoidance, and transparency - acknowledging that journalists are already using it, with or without formal approval.
 

• Audiovisual Production and Advertising

In film and television, AI is used in both creative and technical stages. Screenwriters use generative models for brainstorming plots and dialogues: they prompt ideas for scenes or jokes on a specific topic, which are then refined by humans. In fact, some short series have already been co-written by AI - under human supervision and in accordance with writers’ union guidelines.

El Eternauta, the Argentine sci-fi series released on April 30, 2025, by Netflix, made history as the platform’s first production to use Generative AI to recreate the collapse of a building.

“AI is an incredible opportunity to help creators make better films and series—not just cheaper ones… Using AI-powered tools, they achieved an amazing result at remarkable speed. In fact, that visual effects sequence was completed 10 times faster than it would have been with traditional VFX tools and workflows,” said Ted Sarandos, Netflix Co-CEO.
 

• Advertising and Marketing

Image generators like Midjourney or Stable Diffusion can create ad mockups in minutes, helping agencies pitch multiple concepts to clients without upfront production costs.

Major brands have been in this game since 2023. Coca-Cola, for example, launched a campaign inviting fans to create AI-generated art.

Personalization has also taken a leap forward: streaming platforms now automatically generate synopses, teasers, and video descriptions tailored to each user—maximizing interaction and engagement.
 

• Interactive Entertainment (Video Games)

In gaming, Generative AI is shifting paradigms. NPCs (non-playable characters) can now interact with players in realistic, dynamic, and unpredictable ways.

Ubisoft, for example, prototyped a system (Ghostwriter) to generate diverse lines of dialogue for minor NPCs.

An indie studio in the U.S. created a game (Retail Mage) where most interactions in the virtual store - from NPC customer reactions to what happens if a player tries something creative - are AI-driven instead of being based on pre-written scripts, opening up limitless interaction possibilities.

This unlocks enormous potential: NPCs that remember past conversations with the player, quests generated on the fly based on playstyle, and more.

Developers are also using AI to generate art and environments at record speed - such as algorithms that build maps or game levels based on parameters, reducing months of design to just days.

In game testing, AI-powered bots are being trained to simulate thousands of playthroughs and automatically detect bugs, boosting quality and accelerating development.
 

• Generative music and art

2025 has been the breakout year for AI-generated music and art. From pop songs featuring synthetic celebrity voices - some going viral, others sparking legal debates - to tools like Jukebox (OpenAI) and MusicLM (Google) that allow musicians and creatives to explore new sounds, accompaniments, and melodies from just an initial idea.

In visual arts, galleries and designers are collaborating with AI to create hybrid (human-AI) artworks, logos, characters, and movie environments.

In film, AI is enabling everything from digital “de-aging” of actors to automatic background and crowd generation - replacing traditional green screens, cutting production costs, and opening up new visual possibilities.
 

Manufacturing and industrial sector

Europe - led by Germany and France - has embraced this technology to maintain global leadership in industries such as automotive and aerospace. These sectors are now designing and refining complex components with the help of generative models, accelerating innovation and reducing time-to-market for new products.

In North America, the focus is on advanced automation and predictive maintenance.

Asia (especially China and Japan) is leveraging AI to drive rapid product innovation. The result: shorter development cycles, lower costs, and near-instant market responsiveness.

This new era of industrial efficiency is redefining what’s possible and preparing the sector to meet the challenges and opportunities of the second half of the decade.
 

• Generative Product Design

Manufacturers are using AI to create and test design prototypes much faster.

A standout example is BMW, which has integrated generative design platforms to transform key vehicle components. Supported by AI, engineers have optimized critical parts like seatbelt brackets, reducing weight by 30% without compromising safety or strength. The impact? Less material usage, better fuel efficiency, and real progress toward sustainability - proof that innovation can drive both performance and environmental responsibility..

In aerospace, Airbus uses Generative AI to design much lighter cabin bulkheads, producing prototypes that are 45% lighter than conventional designs. This translates to significant fuel savings per flight, boosting both profitability and ecological commitment.

AI can propose organic geometries that human engineers might never imagine, which are then validated via simulation. With additive manufacturing (3D printing), many of these complex forms can now be produced - something General Motors is already implementing.
 

• Production optimization and predictive maintenance

Generative AI is revolutionizing industrial production and maintenance, enabling a level of efficiency, control, and foresight unimaginable just a few years ago.

Siemens leads the way with its AI-powered predictive maintenance approach. By analyzing continuous data streams from machinery (like vibrations, temperature, and operating patterns), AI detects even subtle signs of wear or anomaly - and accurately predicts which component is at risk, when it might fail, and the best preventive action.

Thanks to this system, Siemens has reduced downtime by 20% and maintenance costs by nearly 25% at pilot plants, setting a new global standard for productivity and reliability.

Generative AI is also enhancing real-time quality control: advanced vision models identify product defects - from small scratches to malformed components - with sensitivity beyond human vision. AI can even “imagine” and display differences between perfect and defective pieces, allowing instant correction on the assembly line without stopping production.

In logistics, companies like UPS are implementing digital twins of their distribution networks: virtual replicas powered by AI that simulate every hub and delivery route. This enables real-time tracking of every shipment, anticipation of bottlenecks, and dynamic operation adjustments to ensure packages arrive on time.
 

Read these success stories:

• Innovating the Meat Processing Industry with GenAI
• Leading the Upstream Digital Transformation with GenAI

 

• Intelligent agents in operations

Multimodal Agents are also being integrated into factory environments. These Agents can understand, process, and respond to different types of information simultaneously - combining data from multiple sources and formats.

Unlike traditional AI, which typically works with either text or images, multimodal agents can integrate text, images, voice, video, sensors, and more to make decisions or interact with users in a far more comprehensive and natural way.

For example, Toyota trained hundreds of plant workers to use no-code AI platforms, allowing them to build their own custom machine learning models. This approach saved the company over 10,000 man-hours per year by automating repetitive production tasks and freeing up line staff to focus on higher-value activities.

In the chemical industry, some plants use Generative AI to adjust reaction parameters on the fly. The model suggests how to vary temperature or inputs to optimize performance - simulating thousands of scenarios in the background.

This has been key in sparking innovation directly from those who know the production processes best: the workers themselves.

The result is a more agile, collaborative, and resilient work environment - where AI doesn’t replace human teams, but amplifies their creativity and decision-making power.
 

Read these success stories:

• Transforming Support Efficiency in the Forestry Industry
• CREA-RS Revolutionizes ART Issuance with Voice Command and GenAI

 

• Supply Chains and Planning

Advanced platforms like Kinaxis (Canada) have integrated Generative AI into supply chain planning. These solutions can generate multiple scenarios—such as what might happen if a supplier is delayed. In these cases, AI not only identifies risks and bottlenecks before they occur, but also automatically proposes the most efficient purchasing, inventory, and manufacturing plans for each situation. This enables companies to respond quickly to market changes, avoiding overstocking or stockouts.

In retail, a Latin American example is Farmatodo (a pharmacy chain in Colombia), which uses Generative AI to personalize product recommendations for customers and automate internal processes that were previously manual. The result: more efficient teams, more satisfied customers, and an unmatched ability to anticipate and meet market needs.
 

Empowering Sales Agents: How a Utility Company Improved Information Search with GenAI (read this success story)

 

Legal and Professional Services Sector

Law firms, consultancies, and other professional services firms have found in Generative AI a powerful ally to boost productivity and reach. Though traditionally conservative, the legal industry is undergoing a rapid transition in 2025.

According to a study by Thomson Reuters, the adoption of Generative AI in legal services nearly doubled in a year, with 26% of firms actively using it and 45% planning to integrate it into core operations within the next 12 months.

In cities like London, law firms use AI copilots for drafting and reviewing contracts. In Singapore and other innovation hubs, AI is already assisting in arbitration processes - speeding up complex analyses and enhancing service quality.

Measured benefits include faster client response times, reduced billable hours on routine tasks (prompting firms to rethink business models), and fewer human errors in analyzing large volumes of legal text.
 

Empowering a Legal Department with Gen-AI (read this success story)

 

• Legal Assistants and Document Analysis

One of the standout applications is the review and drafting of legal documents.

Today, AI-based legal assistants - such as LLMs (large language models) specifically trained in law, like Harvey AI - have become indispensable tools for cutting-edge law firms.

What can these assistants do?

• Summarize complex case law and identify relevant precedents in minutes.
• Analyze 100-page contracts and deliver clear summaries with key points and flagged legal risks.
• Draft documents, clauses, and legal notices from simple prompts - saving days of manual work.

These solutions speed up tasks that previously took days of reading. For instance, a 100-page contract can now be summarized in minutes with key risks highlighted by the AI. In patent law, AI is used to conduct exhaustive prior art searches, detect similarities, and automatically generate the necessary descriptions to protect new inventions - freeing experts to focus on strategic analysis and intellectual property defense.

Leading consulting firms, including the Big Four (EY, PwC, Deloitte, KPMG), are heavily investing in Generative AI. EY, for example, is training its 400,000 employees to use a full suite of AI agents designed for legal, tax, and industry-specific tasks.
 

• Legal Research and Litigation Support

Generative AI is transforming litigation by providing smart copilots to lawyers, judges, and legal teams. Today, innovative startups offer AI assistants that can, in real time:
 

• Search through millions of pages of court records and legal documents in seconds.
• Automatically identify relevant precedents and suggest tailored legal strategies.
• Propose witness questions based on available evidence - enabling stronger, more dynamic trial preparation.

In countries like the United States, these tools are already integrated with existing legal management software, and adoption is growing rapidly.

But innovation is extending beyond law firms: courts in Brazil and Argentina are already experimenting with AI to filter and prioritize legal cases. For instance, AI can review thousands of case files and suggest which ones could be resolved based on clear precedents - even generating draft rulings for judges to review and finalize. This accelerates justice, frees up resources, and raises the efficiency standards of judicial systems.
 

• Legal Translation and Global Services

In a globalized world, multilingual Generative AI has become an essential tool for international law firms.

Thanks to its ability to translate contracts, regulations, and legal documents across multiple languages - with unprecedented precision and fidelity - AI enables international transactions to close faster and with reduced risk of misinterpretation.

European firms with clients in China can now translate complex legal documents from Mandarin into English or Spanish in minutes, speeding up global contract negotiations and execution.

AI is also democratizing access to justice. In Spain, for instance, a legal chatbot has been successfully tested to answer basic legal questions about fines, leases, and other everyday matters-based on current legislation. This allows any citizen to receive reliable initial guidance at no cost or delay, bringing the law closer to those who need it most.
 

• Adjacent Professional Services

Smart Audits

With Generative AI, it’s now possible to analyze massive volumes of accounting data, detect irregularities, and—most importantly—explain the anomalies found in clear and precise language. This allows auditors to focus their time on investigating relevant findings and making informed decisions, rather than spending hours sifting through data.

Personalized Tax Services

New intelligent agents, trained in the tax regulations of each country, can assist with form preparation, answer complex queries, and automatically update themselves as laws change. This not only speeds up tax management but also reduces errors and increases client confidence.

Knowledge Management in Consulting

At large consulting firms, Generative AI is used to summarize historical reports, analyze past cases, and propose winning strategies based on real precedents. This enables consultants to deliver far more informed and personalized recommendations—without spending days reviewing documentation.
 

Transforming a Consulting Firm’s Advisory Services with GenAI (read this success story)

 

How to Start Transforming Your Organization with GenAI

The question companies and entrepreneurs need to ask today is how to leverage AI to achieve what once seemed impossible.

Adopting Generative AI isn’t just about adding new tools - it’s the moment to fundamentally rethink how value is created in your organization. Beyond the hype, lasting success will come from deeply understanding the forces shaping your market and aligning your tech strategy accordingly.
 

Where to start?

 

1. Automate, but keep purpose and creativity

Use AI to free your team from repetitive tasks and gain time for what truly matters: creativity, experience, and your business’s purpose. Efficiency only has value if it enhances your identity and differentiation.

2. Define your strategy before choosing tools

Don’t adopt AI just because others are doing it. First reflect on your company’s mission, identify where AI can amplify its impact, and set clear goals. Technology is the means, not the end.

3. Prioritize simplicity

Look for AI solutions that simplify processes and allow your teams to focus on delivering value - instead of dealing with unnecessary technical complexity. The real advantage lies in making the sophisticated simple and accessible.

4. Learn and experiment

AI adoption is a continuous learning journey. Foster a culture of experimentation and improvement, where trying, failing, and learning are part of discovering unique and high-impact applications for your business.

5. Choose trusted tech partners

AI is a foundational component of the future of business. So it’s not just about joining the movement - it’s about choosing how and with whom to do it.

With Globant Enterprise AI and GeneXus Next, you gain a unique alliance of tech vision, enterprise governance, and execution power. It’s an ecosystem built to integrate AI from day one - and create the software of tomorrow.
 

GeneXus Next: The Native Agentic Low-Code Platform for Enterprises

If you're evaluating platforms to support your organization's digital transformation, GeneXus Next is the smartest strategic solution - especially for companies seeking technological resilience, operational agility, and long-term control.

While other Low-Code platforms help you build screens or automate tasks with AI as a complement, GeneXus Next is the only one that enables seamless AI integration throughout the entire application lifecycle. This makes GeneXus Next the world’s first native Agentic Low-Code platform.

All systems built with GeneXus Next can:
 

• Orchestrate and version AI assistants using the governance and security mechanisms of Globant Enterprise AI.
• Integrate intelligent agents into any stage of the business flow, with traceability, compliance, and centralized cost control.
• Evolve automatically: when Globant Enterprise AI introduces new models, patterns, or frameworks, your systems and agents built with GeneXus Next can adopt them in minutes - without manual refactoring.
• Leverage a cloud-agnostic architecture, ready for multi-cloud or on-premise deployment - avoiding vendor lock-in.

If you're looking for a platform that delivers speed without compromising quality, innovation without losing control, and evolution without starting from scratch every time technology shifts, GeneXus Next is the answer.

We’re not asking you to believe in promises. We invite you to validate it. Contact us.
 

Take the Next Step and Lead the Transformation in Your Industry

Don’t just watch other companies innovate - bring these possibilities to life within your organization.

Discover how we can help you transform processes, multiply productivity, and bring to life the ideas that will truly make a difference.

👉 Start your own transformation journey today.