Streamlined Processes, Maximized Impact: The Future of SME Automation

As the world progresses into an innovative era of the 21^st Century, new technologies are being made available for companies to strengthen their business operations. With the fast-paced changes, two automation technologies, Robotic Process Automation (RPA) and Artificial Intelligence (AI), have revolutionized business operations.

RPA is the use of software to streamline repetitive, rule-based tasks, which acts as a digital workforce that mimics human actions to allow human workers to focus on more important tasks. It is especially beneficial for handling processes like invoices and data migration. AI simulates human intelligence, bringing more advanced problem-solving, data analytics, and decision-making capabilities to the table. Together, these technologies represent a new era of intelligent automation and give companies the opportunity to innovate, improve their efficiency, and adapt to a constantly evolving economy.

Their benefits and limitations are numerous, and these can be difficult to comprehend. Thus, questions can arise over what technology is better for you and your company.

For example, with AI progressing faster and making its way into many different facets of life, including new technology like ChatGPT, has RPA become redundant? How distinct are these two processes, and in what situations can you use them? This article will explore those questions and help share some insights into the world of automation. 

What is RPA?

Starting with a definition for Robotic Process Automation, RPA is a software technology that builds, deploys, and manages software robots that mimic human interactions to process data and work on digital systems. These robots are capable of navigating computer drives, extracting data, and more, while additionally being more consistent than human workers.

The foundations of RPA, back in the 1990s, came from early forms of automation tech like screen scraping and workflow automation tools. This tech involves extracting data from user interfaces and enabling very basic automation of repetitive tasks. It was very limited in its functionality, but it laid the groundwork for what we know as RPA today. More modern RPA evolved around the 2010s, when early RPA platforms emerged as a blend of screen scraping, business process management, and artificial intelligence to automate processes in a rule-based routine, using the existing IT infrastructure available to companies. Companies like Fortra, Blue Prism, UiPath, and Automation Anywhere pioneered these modern RPA solutions. These robots could interact with computers very similarly to humans, they could interact with existing applications, clicking, typing, and copying data, and more.

The COVID-19 pandemic also saw a massive spike in RPA adoption in numerous businesses, as there was a need to reduce dependency on human labour due to the lack of freedom that the virus brought to the world. Since then, SmartTechNXT has helped multiple companies land on their feet after the pandemic, and RPA has become a significant driver of their economic production.

RPA is used in numerous ways in the world, and most people are unaware of how common these robots are within everyday processes. For starters, resetting your password is done with RPA. Before these bots, when a request came in to reset a password, an employee would need to find the time to manually reset it while trying to juggle other tasks. Now, a robot intercepts the request, recognizing the rule-based tasks involved, and resets the password for you quickly and easily. Another example involves the delivery status of your online purchases. Robots now automatically track drivers and packages to allow you to see your shipment status whenever you like and receive updates in real time.

RPA’s benefits are countless. They streamline workflows, increase employee satisfaction, engagement, productivity by removing mundane tasks. Moreover, one of the greatest benefits is that it can make your company more profitable by eliminating wasted time on repetitive tasks. Your employees can then have the freedom to work on more important ideas, focus on innovation, and interact with other employees and customers. RPA is non-invasive and can quickly be put in place to advance your company’s digital transformation. While these bots are ideal for automating workflows that involve big data, virtual desktop infrastructures, and database access, RPA is incredibly versatile and can be applied to many different sectors.

In short, RPA follow the rules set by you to streamline routine tasks and enhance efficiency across digital systems. After evolving significantly in the past few decades, RPA now plays a crucial role in transforming workflows, boosting productivity, and freeing employees to focus on more creative and important pursuits.

What is AI?

Artificial Intelligence (AI) is essentially about teaching machines to think and act in ways that mimic human intelligence. It’s the technology that powers some of the most exciting advancements we see today—helping machines understand language, recognize patterns, solve problems, and make decisions. At its core, AI relies on data and algorithms to learn, adapt, and get smarter over time. In other words, it’s what allows systems to not just perform tasks but also improve at them as they process more information.

AI isn’t just one thing—it’s a huge field with different areas that serve different purposes. For instance, Machine Learning (ML) is a branch of AI that focuses on enabling machines to learn from data without needing to be explicitly programmed. Think about how Netflix recommends your next binge-worthy series—it’s analysing your preferences and learning what you’ll enjoy. Then, there’s Natural Language Processing (NLP), which is all about helping machines understand and respond to human language. That’s what makes tools like Siri, chatbots, or even those spam filters in your email so effective. Other types of AI include Computer Vision, which helps machines “see” and analyse visual information (like facial recognition or checking product quality in factories), and Deep Learning, which uses neural networks to tackle more complex tasks like real-time language translation or creating hyper-personalized experiences.

In the business world, AI has become a game changer. It’s helping companies work smarter, not harder, by analysing mountains of data, spotting trends, and making predictions that would take humans forever to figure out. For instance, AI-driven tools are being used for things like financial forecasting, risk assessment, and even supply chain optimization. AI also transforms how businesses interact with customers—whether it’s through personalized shopping recommendations, virtual assistants, or chatbots that answer questions at lightning speed. Essentially, AI is taking care of the heavy lifting behind the scenes so teams can focus on creativity and innovation.

That said, AI isn’t perfect. Building and implementing these systems can get pretty complicated—and expensive. You need skilled developers and high-quality data to make it work, which can be a challenge for smaller organizations. Plus, there’s the ethical side of things to consider. AI can inherit biases from the data it’s trained on, and if that data isn’t diverse or accurate, the results can be skewed. For instance, an AI-powered hiring tool might unintentionally favour certain candidates over others, which is a big problem.

Still, the potential of AI is incredible. It’s not just a tool—it’s a partner in transforming how businesses operate. From streamlining operations to delivering jaw-droppingly accurate insights, AI isn’t just the future—it’s here, and it’s changing the game in ways we’re just beginning to grasp fully.

This text was generated by ChatGPT, a newly functioning AI site that has taken the world by storm. While the site is still in its beginning phase and there are kinks and bugs to work out, AI technology such as this is becoming more advanced at a very fast rate.

Since the 1990s, AI shifted from rule-based systems to machine learning, where they learned patterns from data rather than following predefined rules, like RPA does. The development of technology in this time and the increasing availability of computational power and data helped AI systems become more flexible and capable of handling complex problems. In 1997, IBM’s Deep Blue AI system famously defeated the world chess champion Garry Kasparov, which showed how AI was becoming tremendously more powerful in problem-solving.

Today, AI is a frequently brought up topic and is becoming a central part of the technological landscape. Self-driving cars, content generation, and chatbots have all been showcased in various sectors of life, especially in social media and the economic industry. However, concerns over AI have not diminished. Since its invention, AI has been a popular theme in pop culture, especially in films where it has been portrayed as both a powerful ally and a terrifying enemy. AI is seen as a tool that is entirely capable of making its own choices, which could lead to it turning on humanity. Pop culture has certainly painted a very dramatic picture of AI, but these are over-exaggerated storylines designed to capture audiences. While these stories do highlight important issues like the risks of misaligned objectives and unintended consequences, today’s AI systems are highly specialized tools which serve more benefits to your company and do not have the self-awareness to “turn on” humanity.

Synergy between AI and RPA

Intelligent Automation (IA) uses AI and technologies like RPA and ML to reimagine how your business operates. Combining AI’s brainpower with RPA’s ability to transform complex processes allows Intelligent Automation to succeed in end-to-end automation capabilities. The benefits of using IA are numerous; these resources reduce costs by augmenting your company’s workforce and improving both productivity and accuracy. Your business can enjoy higher quality service, giving consistent and faster responses to data, market research, and enhance your customers’ experience.

RPA and AI can work together as complimentary technologies. The rule-based, repetitive tasks by RPA can work in conjunction with the learning and decision-making of AI. RPA alone struggles with unstructured data, like emails, handwritten documents, or images, which AI can extract and classify, making it actionable for RPA workflows. It also allows bots to comprehend speech patterns and conversations, transforming chatbots into more easily accessible tools.  AI-powered systems will also learn over time from historical data and user interactions to continuously optimize its processes over time. This adaptability makes RPA more effective in dynamic environments and can be scaled across functions to analyse patterns in multiple sectors and identify inefficiencies.

As AI continues to become more prevalent, accessibility to these technological resources for all becomes more important. Businesses, particularly larger corporations, are already benefitting from introducing AI into their operations, and smaller businesses (SMEs) and local communities can also benefit from these advancements. A lower entry barrier to use these tools can help level the playing field against large corporations.

Many RPA and AI tools are now available as Software-as-a-Service (SaaS) platforms, which means businesses can implement them without costly upfront investments. Additionally, while these technologies are often seen as a replacement for human labour, their implementation can also foster new roles in local communities. Local tech consultants and service providers can specialize in helping businesses with the education and resources needed to get them started with AI and RPA.

Conclusion

In conclusion, as we move into the more innovative landscape of the 21^st century, integrating RPA and AI is not just reshaping business operations; it’s redefining how we work and how businesses compete. These technologies that inject cognitive capabilities into everyday practices empower companies of all sizes to drive efficiency, innovate, and stay agile in a fast-paced economic market.

Of course, more ethical questions can be asked about intelligent automation’s usage. Such as, If AI can replace human workers, will unemployment become a more widespread issue? What will happen to those whose jobs are replaced? This impact on labour markets can also spread to more overarching issues. As workers are losing their jobs and AI-related expertise is in higher demand, higher salaries and education are focused on a limited number of positions, widening the skill gap for those without access to education or resources to develop these skills.

This is why the thoughtful implementation of intelligent automation paves the way for a more inclusive future. Regulating and managing intelligent automation ensures that human values guide its development. While these ethical concerns remain, by investing in reskilling and fostering collaboration between humans and machines, organizations can ensure that the benefits of automation extend far beyond your company. By including automation across the board, we can fuel local economies, create new job opportunities, and build a future where technology serves as a partner in progress for everyone.