Process automation is a key factor in competitiveness and will continue to be a relevant trend in 2026. However, it has evolved and is no longer limited to traditional RPA, but is part of intelligent automation, driven by its integration with AI, as well as process orchestration and mining.
Since the origins of software development, efforts have been made to optimize tasks and increase productivity through process improvement and automation. This approach responds to a permanent need: do more with less, reduce errors and free up time to dedicate it to higher value-added tasks. These objectives remain fully valid and, in 2026, a relevant part of business operations will continue to require automation.
In fact, according to the CGI Voice of Our Clients 2025 global report, prepared from interviews with more than 1,800 company executives from all sectors and geographies in which CGI operates, improving operational efficiency through automation and process optimization is positioned as the top business priority.
Likewise, analysts also foresee strong market growth associated with process automation. While IDC estimates that intelligent process automation software will continue to grow until reaching a volume of $65.3 billion in 2027, other consulting firms such as Grand View Research project accelerated growth for this market, around 44% annually, until 2030.
Along the same lines, Gartner points out in its predictions for 2026 that automation will be a transversal priority for organizations. For its part, Forrester identifies a turning point in this area, with a shift in the center of gravity towards automation models with more advanced capabilities, including agentic functions.
The expansion of this market is driven by a new challenge: it is no longer enough to automate, but it is essential to do so with a well-defined strategy, a solid governance model and a vision for the future. In this context, RPA is evolving towards intelligent automation, capable of transforming the operation, improving control and accelerating competitiveness, integrating with artificial intelligence (AI), process mining and generative models.
Automation as operational intelligence
At CGI we observe that the future of automation is articulated around three main axes: hyperautomation, the cloud environment and integration with generative models. Hyperautomation combines traditional robots with AI, Machine Learning and process mining to automate complex flows comprehensively; the cloud provides scalability and flexibility; and generative capabilities (LLM and SLM) enable more intelligent and adaptive systems, capable of interpreting context and responding effectively to variability.
These innovations, along with process discovery tools and advances in security and governance, drive significant cost reduction, greater operational agility, and the ability to create new business models. Automation stops being just a lever of efficiency and becomes operational intelligence. In an environment in which competitiveness is measured by speed and the ability to adapt, automation – evolved, governed and integrated – is consolidated as a decisive factor.
The debate, therefore, no longer focuses on whether to automate or not, but on how to do it from a strategic vision. In this sense, automation has established itself as a real factor of efficiency and competitiveness by providing tangible benefits, such as the reduction of human errors and greater consistency in the execution of critical tasks, with a significant return on investment, especially in environments with a high volume of manual operations.
Whether in the back office or in areas such as finance, human resources or customer service, where standardizable processes exist, automation generates an immediate impact. Maturity is reached when the organization stops addressing isolated initiatives and begins to manage them comprehensively, treating automation as a strategic asset aligned with business objectives.
Automation within digital transformation
Process automation acts as an enabler within organizations’ digital transformation roadmap. It does not compete with modernization initiatives, but rather complements them, as it accelerates existing processes and allows them to be redefined. In fact, experience shows us that transformation occurs when automation stops being an operational tool and becomes a mechanism for organizational design, agility and scalability. Relatedly, according to the global CGI Voice of Our Clients 2025 report, IT modernization and digital transformation are the top priority for IT managers, followed by improving operational efficiency and reducing costs.
One of the critical factors for success lies in the appropriate selection of the processes to automate. Typically, return on investment (ROI) is used as the main criterion and, without a doubt, it is logical to prioritize those processes that consume more manual hours and offer quick results. However, limiting this decision solely to ROI may prevent you from realizing the full true value. Aspects such as the strategic impact, the effect on the client, the criticality of the process and the level of acceptable risk must also be considered.
In CGI practice, an effective strategy begins with quick wins: simple processes, with high manual load and an immediate impact on efficiency. This approach allows you to demonstrate value in early phases, generate internal trust and build capabilities. As the organization becomes more mature in the use of these technologies, it can evolve towards the automation of more complex processes or those with greater variability, maximizing the overall value of automation and extending its reach to the entire company.
Beyond automation
In any case, traditional rules-based RPA—that is, if X happens, then execute Y—continues to be useful, but it is no longer sufficient on its own. The market is evolving towards intelligent automation models that combine RPA with process mining, AI, machine learning and generative models.
AI allows us to go beyond automation and enable analysis, understanding and decision-making capabilities. In fact, 2025 has been a turning point with the consolidation of agentic AI architectures, which facilitate the creation of intelligent processes that integrate process automation, AI and generative models, such as LLM or SLM specific for specific tasks. This convergence opens the door to automation scenarios that, until recently, required a much greater effort.
Governance and compliance, automate with control
Process automation also plays a key role in governance and regulatory compliance. In the case of critical processes, it ensures complete traceability, since each action is recorded systemically, which facilitates audits and ensures consistent compliance with both internal policies and external regulations.
One of the critical factors for success lies in the appropriate selection of the processes to be automated.
On the other hand, automating without an adequate governance framework can lead to risks, such as the proliferation of bots, the appearance of undocumented dependencies, or loss of visibility. Therefore, it is essential to define responsibilities, controls, metrics and reporting mechanisms, with dashboards that allow continuous monitoring and support informed decision-making.
Finally, it is worth highlighting that, as in any technological transformation process, automation can generate organizational resistance. To manage them effectively, it is essential to accompany their deployment with transparent communication, training programs and reskilling and, at all times, with a people-centered approach. This is an opportunity to increase the company’s productivity and reorient talent towards functions with greater added value, promoting innovation and competitiveness.
Sergio Postigo, Vice-President Consulting Delivery of CGI
