Process Automation has been around for a decade. How much has it evolved?

Since the rise of RPA, there have been a lot of improvements in process automation which has led to the reengineering of business processes to be more seamless and efficient thereby achieving better and greater output with lesser human input.

As we all know, RPA began with three products: IDE, Robot, and Controller. However, today, it has evolved significantly, with numerous capabilities added to the landscape, such as Intelligent Document Processing, AI/ML, Human-in-the-Loop, OCR, Computer Vision, Mining, CoPilots, and many more. This is so true with UiPath, with which I'm currently building bots for business.

Acredito que cada vez mais a evolução com automação e seus protocolos, irão tornando as indústrias cada vez mais competitivas e ágeis e dinâmica.

They are also catching up. Safety play major role for those industry. Concept of safety offers will definitly gate it more closer.

Organizations now recognize the value of automating entire sequences of tasks, orchestrating complex workflows, and integrating diverse systems and technologies. This broader approach to process automation has led to the development of sophisticated Business Process Management (BPM) platforms and tools, like CMW Platform. Modern process automation solutions offer capabilities far beyond basic task automation. They incorporate advanced technologies such as machine learning, artificial intelligence, natural language processing, and advanced analytics. These technologies enable organizations to automate decision-making processes, handle unstructured data, and adapt to dynamic business environments.

One of the major differences between Intelligent Automation in 2019 when I started working, and today (2024), is that Artificial Intelligence back then wasn't mature; the tasks that could be automated with it were specific, the requirements to implement a solution performing at high level were really strict, it required longer period of time to be implemented, and the cost related were extensive. Today AI is much more accessible and mature, user friendly solutions are available in the market at a lower cost, the quality granted by them is higher and continuously evolving to even better performances; the tasks can be implemented thanks to it are broader and allow more applications of this technology.

One thing I would add here is that many people are having this apprehension that RPA is gone aren't actually focussing on thr fact that it's not gone rather evolved into intelligent process automation. The uses cases that were earlier out of scope because of limitations of tool are now a feasible process for automation because of the amalgamation of AI with RPA tools

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The major accelerator for AI related automation is the easier access to generative AI compared to e.g. ML. Besides, LLMs can also take care about (smaller) programming work without any coding expertise, i.e. the number of "developers" has significantly grown with the introduction of LLMs and this should amplify the speed of automation significantly.

Process automation, particularly with Robotic Process Automation (RPA), has significantly evolved over the past decade. Initially, RPA was focused on automating rule-based, repetitive tasks. With advancements, it now incorporates Artificial Intelligence (AI) and Machine Learning (ML), enabling the handling of complex, decision-making processes, and adaptive learning capabilities. Modern RPA can process unstructured data, use natural language processing, and improve over time, marking a transformation from simple task automation to intelligent process automation.

Cloud adoption in process automation, amid Industry 4.0, offers scalability, agility, and global accessibility, driving its increasing use. Benefits include reduced infrastructure costs, enhanced collaboration, real-time data access, and seamless integration with emerging technologies like AI and IoT. This enables agile and efficient operations, fostering innovation and competitive advantage.

The use of cloud (aka offsite servers) is a helpful tool, as long as it remains secure from malicious attackers. Some municipalities refuse to take this step due to the vulnerability of such a problem.

The Cloud based solutions has definitely some advantages like cost savings , better collaboration , data loss prevention etc. At the same time challenges are there to secure it from the cyber attacks , protect data privacy, reducing system complexity etc. This can add up some unforeseen cost in the future to maintain the infrastructure secured.

The adoption of cloud computing in process automation has been steadily increasing due to several benefits it offers, such as scalability, flexibility, cost-effectiveness, and easier integration with other systems. By leveraging cloud services, organisations can streamline their automation processes, improve efficiency, and reduce operational costs. Cloud-based process automation also enables remote access and collaboration, making it easier for teams to work together regardless of their location.

The massive use of the cloud services is one of the most powerful benefits of the modern era of automation. In combination with the expansion of the IIoT concept, the cloud becomes an easy, safe and cheap way to store and share the process data worldwide with very low investments, using very simple devices like a smartphone.

The expansion of scope possible to automation is a direct consequence of the realization of the potential sitting behind automation. Resources have been invested to make automation technologies more user friendly and to enlarge more and more the scope for their utilization. Today those technologies are process, function and industry agnostic, therefore they can be used to automate a really broad variety of tasks changing the working paradigm of millions of workers. What is left to do is for people to continue understanding the power and possibilities arising thanks to these technologies, and find out new ways to implement it.

A fourth notable progression in process automation has been the expansion of its scope and applicability across various sectors, functions, and domains. Automation technologies have transcended traditional boundaries, finding utility in industries ranging from finance and healthcare to manufacturing and retail. Moreover, automation has extended beyond routine tasks to encompass complex decision-making processes, data analysis, and customer interactions. This broader adoption reflects the growing recognition of automation's transformative potential and its ability to drive efficiency, innovation, and competitive advantage across diverse business landscapes.

Para processos bem definidos em modelagem de processos, a automação tem se definido como altamente eficiente quando aplicada, mas com os recursos recentes e a aplicação de ferramentas de tomada de decisão e Aprendizado de máquina, a automação de processos tem se mostrado interessante, inclusive em processos interdepartamentais, onde a "passagem de bastão" é algo critico, e depende de uma análise específica, a realização de automação de processos combinadas com aprendizado de máquina pode ser uma solução interessante neste caso. Outro espaço é em ambientes com processos menos analíticos, com o uso da IA, processos de criação como ocorrem no marketing, podem ter seu tempo reduzido com inspirações (wireframes, esboço) pré-desenvolvidos por IA

Process automation has expanded beyond traditional tasks to include a wide range of processes across different departments. This expansion has led to the integration of automation into various business functions, such as customer service, finance, human resources, and manufacturing. Organizations are now automating complex, end-to-end processes, leading to greater efficiency and agility. The scope has also expanded from task-based automation to process orchestration, encompassing end-to-end process management.

Um dos exemplos de aplicação com sucesso da automação é na indústria , o controle e supervisão dos ativos de forma remota otimiza a operação de planta e agiliza o diagnóstico de qualquer evento de falha no processo. Esses fatores facilitam a tomada de decisão e reduzem os riscos de indisponibilidade no processo.

Despite its benefits, process automation has also brought about challenges. One of the key challenges is the need for skilled professionals to implement and manage automation tools. Additionally, organizations face challenges related to data security, compliance, and integration with existing systems. Overcoming these challenges is crucial for successful automation implementation. As process automation has matured, challenges such as managing change, ensuring security, scaling operations, and integrating with legacy systems have emerged. Companies must address these to fully capitalize on automation benefits. The need for skilled personnel to implement and maintain sophisticated automation systems has also become more pronounced.

integration of these technologies to streamline workflows, increase efficiency, reduce costs, and improve decision-making across various industries. Additionally, there will likely be a shift towards more autonomous and intelligent systems capable of self-learning and adapting to dynamic environments.

Every technology is an opportunity on side and a challenge on the other, for which RPA is not an exception. The most critical challenges being faced today are the agility (how flexible and quickly the code can meet the changing process changes), security (privacy related into), governance (how to regulate the Bots and audit trial), and back-up and remedial measures on account of BOT failures. However, the right information and stakeholder education on emerging automation tools and benefits would certainly create a automation mindset among the organisations and pave way for efficient adoption of RPA.

Capital investment against the manual production. Unavailability of skill manpower Also implementation time is more. If any changes in process there is always resistance from the bottom team. So management has fear to fail.

Still Process automation is coming with it's own difficulties and challanges,maintanance,availability of critical spares,hands of technical experts,bugs .because all these scenarios will create a difficult situation which directly affect the final output that we need, and for avoiding such cases our institutions,industries,suppliers and integrators have to work to find the optimal solutions.

I believe the RPA is going to make another revolution just like it did in the past because the industry leaders, RPA platforms and RPA developers all are building ,learning, implementing inculcating AI and ML capabilities to take up with the era challenges

Agreeing to some of the experts inputs, yes it simply started with bots and development.But with low code & No code development, it made organizations to embrace automation much faster because process are inherently ment to change and improve. Therefore managing changes equicky is vital . Intelligent process automation with Businsss process management capabilities such as human in the loop, low code forms , conversational ai has further enhanced the limites of what can be automated . As a finance and supply chain domain expert in IPA , Process mining and Document understanding are new additions I would personally rate as breakthroughs in IPA which will help organizations to enhance automation potentials.

In the banking sector, I can see RPA to likely evolve further by integrating advanced technologies like AI and machine learning more "accurately" leading to more intelligent automation solutions capable of handling complex tasks, improving efficiency, accuracy, and compliance. Thinking of RPA evolution in the wider financial sector would also suggest to me possible advancement in integrating RPA systems with other "emerging technologies" like NLP, predictive analytics to provide enhanced customer service, risk management, and decision-making capabilities to streamline processes across various banking functions.

In my opinion, the future of Automation relies on the collaboration with human. Technologies will be more and more efficient and profitable at performing both old and new tasks as part of continuous innovation; some of the cognitive tasks that were sole responsibility of human will be performed by automation, therefore it will be mandatory to deepen how to make them collaborate effectively. Human work will remain central in all jobs, and automation will give unique insights that elevate the decision making process and capabilities.

One area that I'm excited about moving forward is the evolution of Computer Vision. UiPath and Microsoft have both been increasing their computer vision capabilities. One of the main drawbacks of RPA has been that UI changes often require code changes, but Computer Vision could help to make processes more reliable, and expand the scope of what's possible to automate.

Automation solutions have become more integrated, scalable, and user-friendly, with a focus on cognitive capabilities and analytics-driven insights. Security and compliance features have also strengthened, enabling automation to span across departments and functions seamlessly.

When enterprises rapidly adopt Process Automation without thoroughly analyzing their processes, they risk substituting one form of inefficiency with another. This rush overlooks a critical opportunity that process automations presents not just to automate processes but to enhance and optimize them, thereby allowing the business to scale its automation efforts more effectively. Automating inefficient processes without prior analysis can lead to failure, underscoring the need for careful evaluation and improvement of processes before implementing the solution. Process Mining can be used for end-to-end process analysis, optimization which pinpoint non-compliant activities, inefficiencies, or bottlenecks and thus improvement opportunities.

Process automation has evolved significantly over the past decade. Advancements in technology, such as artificial intelligence, machine learning, and robotic process automation, have enabled more sophisticated and efficient automation solutions. These advancements have led to increased flexibility, scalability, and integration capabilities in automating various business processes across industries. Additionally, there's a growing emphasis on intelligent automation, which combines automation with cognitive technologies to make processes smarter and more adaptable to changing environments. Overall, the evolution of process automation has been substantial, with continuous improvements driving greater productivity and innovation.

In the last ten years, process automation has improved a lot thanks to better technology like AI, machine learning, and RPA. These upgrades have led to smarter automation tools that can handle complex tasks more efficiently and with fewer mistakes. Also, these tools can adapt to changes, making them even more helpful. Overall, this progress has helped businesses run smoother and focus on more important work.

03 dicas para iniciar com RPA 1. Identifique os processos adequados: Comece identificando os processos que são repetitivos, baseados em regras e consomem muito tempo. Esses são os candidatos ideais para a automação com RPA. 2. Envolva as partes interessadas: É importante envolver todas as partes interessadas no processo de implementação do RPA, desde os usuários finais até a equipe de TI, para garantir que todos estejam alinhados e apoiem a mudança. 3. Comece com projetos pequenos: Ao iniciar, é recomendável começar com projetos menores e escalonar gradualmente à medida que você ganha confiança e experiência com o RPA.