The Age of Automation: How RPA and AI are Changing the Business Landscape
The history of automation dates back to the dawn of humanity’s invention of the first machines and the conceptualization of robots, which has ancient roots in myths such as Galatea and Talos. These old narratives already envisioned building artificial beings capable of performing specific tasks. Nowadays, automation has evolved towards using sophisticated software tools to minimize or eliminate the need to perform repetitive and tedious tasks, thus allowing workers to focus on higher value-added activities.
And it is precisely the ability to eliminate tedious tasks and simultaneously promote the creation of new jobs thanks to the emergence of innovative technologies that make these technologies so fascinating. The convergence between artificial intelligence technologies like ChatGPT-4 and RPA is particularly interesting. However, certain “progressive” and sensationalist press sectors tend to portray these technologies as catastrophic, using images and references to movies like Terminator to exaggerate their negative impact. While it is true that there are significant ethical challenges associated with automation (a topic I have always addressed in my speeches and publications), its main objective is to free workers from the most monotonous tasks, offering value in more relevant tasks while enabling adaptation to the new liberating jobs promoted by the rise of these technologies.
Some benefits of automation include Improved speed: Automation allows tasks to be performed more quickly and efficiently, improving response times and overall performance. Optimized customer service: With the help of AI, companies can provide efficient and personalized service, improving customer satisfaction. Increased employee morale: By leaving the most tedious and repetitive tasks in the hands of RPA software, employees can devote themselves to more stimulating and rewarding activities. Reduced errors: If an RPA program is well-designed, human errors are minimized, and more accurate and consistent work is ensured. Regulatory compliance: By implementing regulations directly into the RPA program, compliance with standards and corporate policies is ensured. Constant availability: Unlike humans, a program or robot does not need to rest or take vacations, allowing uninterrupted operation and increased productivity.
It is worth noting that this does not pose any risk. Most current jobs are not based on performing a simple task monotonously and repetitively but on the mix of many tasks that result in more complex and enriching activities. Another interesting point is that, as users, we need to be made aware of how automation of tasks has permeated our daily lives. For example, many tasks related to organization and time management, e.g., scheduling a recurring meeting in Google Calendar or Microsoft Teams, are performed without thinking that there is an automation algorithm behind these tasks. Below are other examples of personal automation tasks:
Reminders and alarms: Setting up reminders and alarms on mobile devices or in calendar apps is a basic form of automation that helps people remember important events, appointments, or pending tasks.
Email filters and labels: Creating filters and labels in email services allow the automatic organization of incoming messages based on specific criteria, such as the sender, subject, or keywords. This makes managing email easier and reduces the time spent manually sorting messages.
Synchronization and automatic backups: Many cloud applications and services offer synchronization and automatic backups of important files and data. This ensures that the information is always up-to-date and protected in case of device loss or damage.
Automating bills and payments: Scheduling automatic payments for bills and monthly subscriptions through banking apps or online payment platforms is a form of personal automation that helps avoid payment delays and reduces the need for manual transactions.
Virtual assistants and routines: Virtual assistants, such as Amazon Alexa, Google Assistant, or Siri, allowing users to automate tasks through voice commands and create personalized routines. For example, by saying “good morning,” the assistant could turn on the lights, read the news, and provide information about the weather and traffic.
These examples demonstrate that personal automation is already a part of many people’s daily lives, making routine tasks easier and improving organization and efficiency.
RPA Technology — A Definition for General Public Robotic Process Automation (or RPA) is technology allows the automation of repetitive tasks and processes primarily in businesses using software “robots.” These robots are not physical machines but computer programs designed to mimic how humans interact with digital applications and systems. In simple terms, RPA is like having a virtual assistant that can perform specific tasks without human intervention. These tasks usually follow fixed rules and require little or no creative decision-making. Some examples include data entry, report generation, updating records in different systems, and email classification.
RPA and the Cloud
The combination of RPA and cloud architectures (e.g., microservices) triggered by events represents a significant evolution in business process automation. In this approach, RPA is integrated with a cloud-based microservices architecture, where each service is responsible for a specific function and communicates with other services through events. This architecture allows for greater scalability, flexibility, and resilience than traditional monolithic systems. By adopting an event-triggered architecture, RPA robots can respond more agilely and efficiently to changing conditions and business needs. For example, an RPA robot could be automatically activated when a specific event is detected, such as the arrival of a new email, updating a record in a database, a file arriving in a bucket to generate a report, or an alert being generated in a monitoring system. In this way, automation becomes more dynamic and better adapts to fluctuations in workload demand.
Some RPA Tools
UiPath
It is one of the most popular and widely used RPA tools. It offers a comprehensive platform that enables businesses to design, develop, deploy, and manage software robots.
Pros: Intuitive graphical interface for designing workflows. Wide range of predefined activities and custom libraries. Integration with enterprise applications and cloud services. Active community and a large number of online resources available.
Automation Anywhere
It is another leading RPA solution that offers an enterprise platform for automating large-scale business processes.
Pros: Easy to use with a drag-and-drop-based design environment. Built-in artificial intelligence and analytics solutions. Centralized management of robots and real-time analytics. Strong security and cloud or on-premises deployment options.
Blue Prism
It is an RPA platform that provides businesses with scalable and secure automation solutions.
Pros: Visual design of processes and workflow. Solid exception handling and auditing capabilities. Scalable architecture and integration capability with AI solutions. Cloud, on-premises, and hybrid deployment options.
WorkFusion is an RPA platform combining process automation with artificial intelligence and machine learning.
Pros: Easy-to-use graphical user interface. Integrated AI and machine learning capabilities. Scalability and flexible deployment options. Support for cognitive process automation and data analytics.
Power Automate (formerly known as Microsoft Flow)
Is an RPA tool developed by Microsoft that allows users to automate processes and tasks across various applications and services.
Pros: Native integration with Microsoft applications and services, such as Office 365, Dynamics 365, and Azure. Predefined connectors for a large number of third-party applications and services. Drag-and-drop-based visual workflow design. Ability to create automated flows and event-triggered responses. Capability to deploy automation solutions both in the cloud and on-premises.
The Future of RPA in Tandem with the AI Revolution
This section alone could be a post, but I decided to leave it here and conduct a deeper investigation in the future and go with an extended post. However, given the emergence of technologies such as ChatGPT-4, MidJourney, and improvements in artificial intelligence algorithms, our imagination needs to be improved when it comes to what we could achieve using RPA and AI. In this sense, I dare to quote Günther Anders:
“We could call ourselves ‘inverted utopians’: while current utopians cannot actually produce what they can imagine, we cannot imagine what we are actually producing” — Anders, Günther (2019). “Theses for the Atomic Age.”
And any idea that occurs to us, no matter how much like science fiction it may seem, appears attainable when we talk about the mix of these technologies (obviously thanks to all the scientific advances behind technological developments). In any case, some interesting and more grounded ideas in this direction that are already happening/being developed are the following: Cognitive Automation: The incorporation of AI technologies such as natural language processing (NLP), machine learning, and computer vision will enable RPA robots to tackle more complex and cognitive tasks, such as understanding context, analyzing unstructured documents, and making decisions based on patterns and historical data. Adaptability and Self-learning: The RPA systems of the future could be capable of autonomously adapting and learning as they face new challenges and changes in processes. This would allow for greater flexibility and efficiency in automation, as robots could automatically adjust to modifications in applications or workflows. Automation of Creative Tasks: As AI advances, RPA robots could be capable of tackling more creative tasks, such as designing user interfaces, writing advertising copy, or composing music, based on parameters and influences defined by the user. Human-Robot Collaboration: The RPA robots of the future could collaborate more effectively with humans, providing real-time support and assistance in complex tasks and helping to improve decision-making and efficiency. Once again, hello, ChatGPT-4! Integration of Emerging Technologies: As new technologies emerge, such as virtual reality, the Internet of Things (IoT), or quantum computing, AI applied to RPA could integrate these innovations to address even more applications and use cases across a wide range of industries.
In closing, it is important to recognize the challenges and dangers of these technologies (like nuclear technologies in their time). Legislating to have good international standards for their use is extremely important. However, I believe it is just as or even more important to promote them and be aware of their use in research, innovation, democratization, and liberation that these types of technologies can bring.
References
- UiPath (2020). “RPA: The Ultimate Guide.” https://www.uipath.com/rpa/robotic-process-automation
- Automation Anywhere (2021). “What is Robotic Process Automation?” What is RPA? Robotic Process Automation | Automation Anywhere
- Blue Prism (2021). “Robotic Process Automation: Overview & Guide.” RPA 101 | SS&C Blue Prism
- Russell, S., & Norvig, P. (2021). “Artificial Intelligence: A Modern Approach” (4th ed.). Pearson.
- Brown, T. B., et al. (2020). “Language Models are Few-Shot Learners.” arXiv preprint arXiv:2005.14165. https://arxiv.org/abs/2005.14165
- Radford, A., et al. (2018). “Improving Language Understanding by Generative Pre-Training.” OpenAI. https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdf
- Vaswani, A., et al. (2017). “Attention is All You Need.” Advances in Neural Information Processing Systems 30, 5998–6008. https://arxiv.org/abs/1706.03762
