Predictions for the Future of Low-Code Automation

Print Friendly, PDF & Email

As automation adoption and usage become table stakes of the modern enterprise, an increasingly tech-savvy generation of workers is emerging to supply the accompanying IT support. These individuals not only want powerful software tools; they need them to succeed in their roles, to be more engaged and agile as they move through their responsibilities, and drive results for their organization. Low-code technology is positioned as the solution for sustaining that technical appetite. 

While some organizations may already be familiar with low code, the low code of a few years ago is quickly evolving to become even more accessible. As businesses plan their IT investments and consider if the innovation is a fit for their needs, here’s what they can look forward to: 

Low code will become more prevalent across all business functions—not just IT

Traditionally, automation usage and application development has been reserved to those in IT and engineering. While this ownership makes sense given those individuals’ expertise, it also creates a bottleneck for the wider organization when it comes to innovation. With limited bandwidth, IT teams are often unable to service every one of their colleagues’ requests in a timely manner, which can hinder larger workflows if a technical issue is keeping an employee from executing his or her responsibilities. 

With low code, workers outside of IT can take software development into their own hands: all they need is a foundational understanding of how to use a computer. Low-code automation requires—as the name insists—little to no coding to design and launch, making it an intuitive tool for bringing workers across industries and technical experience into the folds of innovation. When users across the business can build simple and even complex automations themselves, IT professionals can focus on more strategic projects that demand their expertise. As a result, the business at large is able to solve more problems, pursue new objectives or opportunities and better compete in the market.

Even more democratizing is the emergence of no-code automation—though the lack of coding may come across as conceptually confusing to new users. This knowledge gap underscores the need for more accessible automation education in order to unlock no and low code’s potential at scale. Specialized training programs can help employees better understand how to leverage these technologies to execute their everyday responsibilities more efficiently. 

Whereas individuals outside of IT and engineering roles may not understand coding, they do understand business processes, which is where employers will need to focus when they introduce low code and no code and accompanying training programs to their organizations. Regardless of the industry or area of business they are working within, employees can leverage low code’s versatility to support the routine processes essential to their roles. 

To this end, low code not only makes workers’ jobs more efficient—it also has the potential to make them more effective. A low-code interface allows users to link systems to pull information from so that they can easily make business decisions rooted in data. For example, low-code applications can be configured to auto-populate routine forms using information from financial or CRM systems so that employees can spend more time analyzing it rather than sourcing it. 

Low-code advancements will make the technology even more accessible

In order for workers with less formal technology training to leverage low-code tools and create their own automations, these technologies need to be intuitive. In response to this need, a wave of advancements in low-code platforms is making this ease-of-use a reality, including:

  • More visual artificial intelligence (AI) deployments. Even with low code to assist with data collection, analyzing crowded forms and spreadsheets can be a tedious task. With AI integrations into low-code platforms, these systems will be able to compile data into easier-to-understand visualizations, which cuts down on the time needed to make smart business decisions. AI will be able to do this in short order—enabling visually rich applications to be developed by just pointing automation systems to underlying data and allowing it to make the right connections. Moreover, AI can recognize patterns within that data to guide users toward decisions. In a retail environment, for example, automation can collect historical pricing, sales, and inventory information. Leveraging market trends, seasonality of products, and even social sentiment, AI can predict the price of any item in a store. Low-code apps can then visually present this data and recommended prices and quantities to retail stores, thereby maximizing profits and optimizing for inventory.  
  • Natural language processing (NLP) and other types of AI. Low-code platforms are evolving beyond drag-and-drop interfaces to incorporate NLP to help users design their ideal apps. Users unsure of which steps to take to build their envisioned function can instruct the system on what they want to create, and it will leverage AI to reference its existing knowledge base to achieve that vision. Because NLP understands context instead of just key words, users also don’t need to worry about being precise or technical with their language to achieve their desired outcome. For instance, a user could instruct the platform to “create a red button that says ‘Cancel’” to add to an online form they’re drafting, and the program will design that based on its understanding of red buttons. 

The increasing ubiquity of automation within modern enterprises is paving the way for a new, technology-infused world of work. However, to capitalize on that trend and become fully automated enterprises, organizations need to supply employees, even the non-technical ones, with the tools and training needed to ensure automation is at the fingertips of every person. Fortunately, the future of low code is an accessible one, meaning more workers across verticals and job functions can put the technology’s power to use to make more agile and informed decisions—and drive their businesses forward as a result.

About the Author

Palak Kadakia is VP of Product Management at UiPath with a passion for building innovative products and teams. Focused on building designing intuitive customer experiences, Palak leads the engagement platform for RPA which includes a low-code app development platform, human in the loop, conversational AI and data services. Prior to UiPath, Palak was a product management leader at Microsoft.

Sign up for the free insideBIGDATA newsletter.

Join us on Twitter: @InsideBigData1 – https://twitter.com/InsideBigData1

Speak Your Mind

*