The progress of artificial intelligence is at a global acceleration point. For IDC, 2026 will be the year the market moves from experimentation to mass adoption, forcing organizations to turn AI into real value. But this leap will not be easy: Market volatility, pressure for results, and lack of a strong data strategy will set the pace.
Forrester agrees that IT managers will have more budget to invest in AIBut they will also face greater demands. In this area, data quality and governance become a critical differentiator.
“If a player cannot control the ball on the field, he will not be able to score any goal. The same thing happens with artificial intelligence: “Without quality and well-managed data there will be no intelligent AI.”He says Gilson MagalhaesVice President and General Manager of Latin American red hat.
According to the Executive, 2026 will be a pivotal year: projects must demonstrate strategic impact and not just operational improvements. “It is not enough to adopt tools; it will be necessary to restructure journeys, personalize interactions in real time, and redesign processes with integrated AI, from the production floor to management.”Magalhaes adds.
Digital Sovereignty: The Heart of the Next Decade
Data regulation is driving a growing trend: sovereign AIdesigned to ensure that information and forms remain under national or regional jurisdiction.
For Magalhães, mastering data will be a Key competitive advantage: Knowing where they are, how to address them, what their impact is and with whom they are shared. And he warns against it The dangers of the “digital fallacy”: Relying on models trained on incomplete, biased, or faulty data.
“If business, public policy, health care or education decisions are critical “If this data is based on a model that was trained with incomplete or tainted data, we will institutionalize error,” Gilson warns.
Combating this danger requires attention to three axes:
- Strict selection of data
- Transparency in sources and operations
- Constant critical thinking
IDC estimates that by 2026, more than 30% of companies using advanced AI will disclose the data sources with which they train their models.
Infrastructure and heuristics: The components that define the true value of AI
On occasions Red Hat Summit: Connect – With releases in São Paulo, Buenos Aires, Santiago, Mexico City, Montevideo, Lima and Bogotá – the company has highlighted the role of open and hybrid platforms as the foundation of modern AI. In this scenario it was presented Red Hat AI 3, is a solution designed to combine models, data, and automation in hybrid environments.
“The next phase of AI will be hybrid, open and collaborative, based on interoperability and transparency.” Co-creation“Magalhaes says.
Heuristics is another concept that has taken center stage at these meetings. This is the stage where models apply what they have learned to real situations and which gains importance in vital sectors such as health, finance, industry and services. For example, in the financial sector, heuristics are able to detect errors and unusual behavior in real time, and prevent fraud Simplify care.
According to Gartner, by 2028 More than 80% of the computation accelerated for training will go to inference. In this sense, Magalhaes says: “The future of AI is not determined by models, but by what is done with them.”
Intelligent Agents: Toward a New Business Architecture
For Red Hat, 2026 will also mark the integration of intelligent agents within enterprise applications. These technologies are able to operate independently and learn from dataIt will change the way organizations manage their interactions with customers, operate a business, manage inventory, or make financial decisions. The key: real-time personal interactions.
Gartner projects that By the end of 2026, 40% of enterprise software will integrate intelligent agents By 2035, these programs will generate about 30% of enterprise software revenues.
“These context-adapted interactions will require companies to rethink not only what they sell, but also how they do it: what channels they use and how they communicate with their customers,” the CEO explains. “The competitive advantage will lie in how well AI understands and respects human behavior,” Magalhaes says.
Physical AI, automation, and infrastructure ready for expansion
Another growing trend is the so-called Physical AI brings intelligence to the real world through integration with robotics, self-driving vehicles, the Internet of Things, and digital twins. According to Deloitte, by 2026, this technology will transform sectors that are traditionally expensive or complex to automate.
“This infrastructure modernization is the foundation of the new digital economy. “It involves removing silos, integrating the cloud, rethinking the role of data, and embedding automation into the core of operations,” says Red Hat’s vice president for Latin America.
Far from being left behind, classic automation is being improved: Gartner predicts so 30% of companies will automate more than half of their network activities based on artificial intelligence. While McKinsey indicates that combining artificial intelligence with automation can increase productivity by 35% and reduce costs by 20%.
In this context, open source enterprise solutions, e.g Red Hat Ansible platformthey become strategic allies of enterprises, allowing them to scale automation among themselves domains, coordinate workflows, and improve IT operations securely and flexibly.
The key to success for Red Hat
In conclusion, for Magalhaes, The road to 2026 requires a new business architecture based on three pillars:
- Data mastery
- Intelligent reasoning
- Technological modernization
“AI will only add value when it is applied for a clear purpose and in harmony with human knowledge.”concludes the executive branch.