Artificial intelligence, although conceptually present in the technological imagination for decades, is experiencing a momentum that can only be defined as frenetic. This renaissance, comparable in its scale and speed to the emergence of cloud computing, has transcended the academic field to consolidate itself as a fundamental and unavoidable competitiveness tool for companies in any sector. In this new paradigm, hyperautomation emerges as one of the most exciting and perhaps most controversial aspects of AI.
It is a technology that, although it may generate logical concern in teams at the prospect of substitution, in reality what it provides are extremely powerful tools to transform the business, freeing human talent from repetitive tasks and redefining the limits of operational efficiency. The confluence of AI and process automation has become the epicenter of technological evolution in the business sphere, promising not only incremental optimizations but the creation of radically new customer experiences and the redefinition of entire business models.
To unravel this complex reality, a recent roundtable organized by Appian y MCPRO On October 7, it brought together a panel of experts in technology and Artificial Intelligence from some of the most relevant sectors of the Spanish economy. Their perspectives forged on the front lines of implementation offer an indispensable roadmap. The expert panel, moderated by Gustavo de Porcellinis (MCPRO editorial director) included:
- Carlos RanzDirector of Digital Transformation and Operational Excellence at Santalucía Seguros.
- Xavi GodoyDirector of CX and Automation of HBX Group.
- José Ramón ReboredoGlobal Head of Data Analytics & A Piñero Group
- Irene del Mar Muñoz GilHead of Cloud Engineering at Renfe.
- Sara de la RúaInnovation Manager at Airbus Crisa.
- Jose Miguel González AguileraDeputy Director General of Innovation of Emerging Services of the Madrid City Council.
- Jacobo ArizaHead of Staff & Services Digital Enabler Iberia de Endesa.
- David GomezAccount Executive de Appian.
- Angel NebreraSenior Strategic Account Executive de Appian.
Governance, culture and strategy
The debate made it clear that the first step in the adoption of AI is not technological, but strategic and cultural. Leading organizations are approaching AI not as an isolated project, but as a comprehensive plan. Irene del Mar Muñoz Gil explained the methodical approach of Renfe: “During 2025 we have established the AI strategy plan that has been based on different levers, the first was to establish an AI laboratory” to design solutions with the approval of compliance and business. This lab was followed by workshops with users and an internal project competition to launch rapid proofs of concept, lasting no more than six weeks, to validate their feasibility before scaling. Similarly, the Madrid City Councilaccording to Jose Miguel González Aguileracreated a “cross-cutting framework” with a digital office for data governance and a technological unit, managing to compile up to 85 ideas from all areas of the organization and estimating annual savings of 5 to 6 million euros in approved projects.
However, technology alone is not enough. Jacobo Arizaof Endesastressed that the real challenge is not in technical adoption, but in the cultural change that accompanies it. “AI does not replace human talent, it amplifies it. It is about automating what is repetitive to leave the management of exceptions to people, which is where they really add value,” he stated. Along these lines, he proposed humanizing artificial intelligence through personalized co-pilots for each employee: “Having an assistant adapted to the interests, objectives and context of each person is an effective way to break down barriers of fear, improve productivity and make the value of AI tangible on a daily basis.” This vision was shared by José Ramón Reboredo of Pinero Groupwho stated emphatically that “Generative AI projects are people projects” and that the focus should be on democratization and training to expand the capabilities of the teams, not on substitution.
From data to end-to-end process
If governance sets the map, the fuel is data and processes. According to attendees, the obsession with AI has forced companies to confront a fundamental weakness: widespread ignorance of their own operational processes. Carlos Ranz of Santalucia Insurance offered one of the keys of the day: “Companies have often had to start from scratch without realizing that we have to start by analyzing the data and not with interviews with people.” He explained how process mining revealed that operational reality “has absolutely nothing to do” with what users describe. Applying AI to a poorly understood process is simply “wasting money.”
This view was endorsed by David Gomez of Appian: “We believe that AI without processes is not AI either.” Appian positions itself as a “fundamental piece of orchestration,” the glue that unites the different tools to transform work in a coherent way. The idea is not just to automate, but to do it intelligently. In that same line, Jacobo Arizaof Endesawarned of the risk of artificial intelligence becoming a “black box” if organizations do not capture and share the knowledge generated by their digital interactions. “Automation must allow human talent to focus on the exception, on everything that is not regular, but it must also help us understand how we arrive at each decision,” he noted. For Ariza, the real value is in converting each digital interaction into learning, so that AI not only executes, but documents, explains and continually improves processes. For Sara de la Rúa of Airbusthis is a critical issue: in an environment where reliability is at its highest, hyperautomation cannot create “a network that turns into a tangle,” and it is imperative to maintain the explainability of why the AI makes a decision. “When you make a decision with AI you have to be very aware of how it was reached,” he insisted.
ROI and business transformation
Once the foundations are laid, the objective is to generate tangible value. The discussion showed a range of use cases ranging from immediate efficiency to strategic reinvention. In the area of direct ROI, Xavi Godoy of HBX Group presented a case of resounding success. Thanks to the LLMs, the classification of customer service cases went from a 70% success rate with previous technologies to “99% or higher” on par with a human agent. Furthermore, thanks to an artificial intelligence translation tool, they managed to translate 1.5 million hotel descriptions into 18 languages at a cost of thousands of euros, a project whose traditional cost would have been millions of euros using translation agencies. For its part, José Ramón Reboredo explained how in Pinero Group They use AI to analyze “hundreds of thousands of customer reviews, extracting issues and sentiments to generate summaries that hotel managers receive something impossible to process manually.”
Beyond efficiency, AI is transforming the core of the business. Carlos Ranz He related how in Saint Luciaa seemingly trivial problem like locating experts during a DANA was solved with data. “Now we have them monitored and we know where they are to rationalize and optimize visits” also ensuring that incidents in unpopulated areas are not left unattended. In Renfeas pointed out Irene del Mar Muñoz GilAI is key to facing a double existential challenge: “collecting all that tacit knowledge of those people who are going to retire and also collecting that knowledge of customer experience that has been complicated due to the liberalization of transport.”
An inevitable revolution
The crossroads of hyperautomation and AI defines the new competitive battlefield. As was evident in the debate, the leaders of tomorrow will not be those who acquire the most advanced technology, but rather those who achieve comprehensive mastery of strategy. Carlos Ranz He summarized it as “the most important challenge in recent years, but not because of the sophistication of the technology, but because of its transversal nature,” since it impacts from the client to the board of directors, including finance, regulation and security.
The panel’s final conclusion was unanimous: AI is an enabler for growth, not a replacement tool. It is, as stated José Ramón Reboredoof “doing more with the people you already have. Generative AI turns us into Robocop: we go from agents with human limitations to entities powered by technology. “It’s about expanding.” The goal is for people to provide maximum value and for technology to do low-value tasks. But this revolution cannot ignore security and privacy challenges. For this, as pointed out Angel Nebrera of Appianit is essential to have platforms that guarantee “private AI”, where customer data always remains under your control, a critical factor for trust and regulatory compliance that was also present in the debate. Sara de la Rúa He closed with an eloquent metaphor: AI is a “toolbox,” and the mission of leaders is to teach the organization to “use the most appropriate tools for what we need.” Organizations that understand this new reality, that invest in culture, that analyze their processes honestly, and that approach AI as a tool to empower their teams, will not only survive the disruption, but will be in a privileged position to lead the next decade.
