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At 8:03 a.m., Elena opens her email full of invoices, documents, and attachments. She used to spend her mornings copying data. Today, a robot sorts, extracts, and validates; she reviews exceptions and talks to customers. That shift is the best clue as to where RPA is headed.

A market that is accelerating

RPA (Robotic Process Automation) is no longer a promise: it is an everyday tool for many companies. In simple terms, reports put the global market at around €3 billion in 2023 and anticipate growth of close to 14% per year until 2033. What does this mean for day-to-day operations? More organizations using software robots to take repetitive tasks off their hands and devote that time to customers and cases that require human judgment.

Why is it growing so much?

  • Pressure to save time and costs. RPA does the “hard graft”: copying data, cross-referencing information, creating records, and preparing documents without getting tired or distracted.
  • Improvements in AI (Artificial Intelligence) and ML (Machine Learning). Previously, bots followed fixed rules; now they also understand documents, classify emails, and make business-driven decisions.
  • Visible results. When a team sees that a process takes minutes instead of hours, they ask to automate the next one. This is how the “snowball effect” is born.

For people who work in front of a screen, the impact is direct: less typing, fewer corrections, and more focus on what matters. For example, in a real estate agency, a bot can read invoices and deeds in PDF format, upload the data to the ERP, and notify if any documents are missing. In insurance companies, a robot prepares claims files with key information ready for the adjuster. In a law firm, it classifies notifications and marks deadlines in the case calendar. In an administrative agency, it handles telematic filings and reconciliations en masse and without delays.

Looking ahead to the next decade, this trend will increase because there is more and more data in emails, forms, and portals; RPA combined with AI helps to read them and convert them into actions.

In summary: RPA is entering a more mature and accessible stage. If you manage real estate promotions, insurance policies, legal files, or tax campaigns in an agency, the time to start (or expand) is not in three years: it is now, with specific cases that give your team back time from the very first month.

Trends that will shape the decade

1) AI agents, useful from day one
RPA no longer just pushes buttons. Combining it with language models allows it to read emails, suggest responses, enrich records, and decide on the next action based on business rules. Think of an “agent” that converses, consults a database, and launches an RPA flow when necessary.

2) Ecosystem automation
RPA does not work alone: it connects with different tools to make everything flow better. Bots perform repetitive tasks such as copying data or moving files. APIs (Application Programming Interfaces) are bridges that allow different programs to talk to each other, such as when the accounting system connects to the bank. BPM (Business Process Management) helps organize the order of steps in a complete process. And process mining observes how work is actually done to detect where automation is appropriate.

To coordinate everything, there is a central management layer that acts like an orchestra conductor: it assigns tasks to a robot, avoiding duplication and ensuring that each part of the process has the right executor.

3) AI at the service of people
Technology supports the team, it does not replace it. RPA handles repetitive work; people focus on customer service, negotiation, and judgment. This model reduces downtime and improves the end-user experience.

4) Government and security as the backbone
Scaling requires clear rules: who publishes a robot, how it is versioned, what is audited, how credentials and data are safeguarded. Current “governors” already include traceability, segregation of duties, and real-time alerts.

5) Intelligent process mapping
Process mining and task mining tools map the process as it actually occurs. With this real-life snapshot, short automations are prioritized, bottlenecks are detected, and unnecessary steps are avoided.

6) Central management enhanced with AI
Automatic assignment of work between “digital workers” and human teams; the system learns from volumes, seasonality, and results to adjust queues and SLAs without manual intervention.

7) From data to results
Documents, emails, and chats contain valuable information. With RPA + generative AI, fields are extracted, validated against internal systems, and fed into dashboards that help you make quick decisions.

What it means for your industry

Real estate

  • Entering invoices and simple notes: capturing data from PDFs and validating it against ERP and CRM.
  • Managing guarantees and certificates: checking expiry dates and sending automatic notifications to developers and banks.
  • Customer service: responding to frequently asked questions about file status or key handover.

Insurance companies

  • Claims processing: reading reports, checking against policies, and preparing files for the expert.
  • Collections and recoveries: bank reconciliation and generating reminders with the appropriate tone and channel.
  • Mediators: product registration and mass issuances without repetitive typing.

Legal

  • Document management: classification of claims, contracts, and notifications; extraction of key data.
  • Deadline control: live agenda that creates tasks, notifies the team, and records actions in the office manager.
  • Billing by case and provisions: automatic calculation based on order sheets and times.

Administrative agency

  • Online submissions: bulk sending of forms and uploading of supporting documents.
  • Payroll and social security: generation, verification, and filing by client.
  • Client registration: creation of files and permissions on each portal.

¿And what about Devol?

At Devol, we work with RPA, low code, and AI to put these lines into practice. We have ready-made solutions for common cases, such as Devol 4 Invoices (supplier invoices), DocMind (data in unstructured documents), SQLMind (database queries in natural language), and Process 360 (complete automation lifecycle management). All with clear governance, traceability, and support.