What It Takes to Scale Low-Code Efforts
With the rise of low-code solutions and the ongoing drought of developers, non-coding, non-designer workers are creating utilities and applications that power new business opportunities and efficiencies. Even pro developers are turning to low-code to speed up prototype app creation.
Low coders have done this for years with visual design tools, building apps and no-code services. But now, the addition of generative AI gives extra horsepower to help firms scale up — fast.
A new study found growing CIO recognition of low-code’s value, noting that professional developers (67%) and citizen developers (41%) are using it to create innovative solutions for business. In turn, that is driving interest among today’s startups and high-growth firms seeking to create new products faster.
By merging AI and low-code, the tools can deliver a solution simply by asking questions and instructing the AI, rather than learning how to design the solution.
There is a lot of potential left to uncover in this space. And as businesses pay more attention to these solutions and workers deliver new applications using a mix of low-code and AI power, questions arise: How will the ability to scale change strategies and operations? And how will organizations ensure compliance, security and data protection are maintained?
A New Low-Code Surge
Consider a bootstrapped startup with minimal staff launching today. Thanks to low code, they can plan, design and launch digital products or solve customer problems in hours or days, rather than months.
And at that size, they are probably sitting on modest cloud customer/supply data stores and services — all easy to monitor and secure.
For larger businesses, though, the proposal becomes more complex. While low-code platforms are designed to be scalable, supporting increases in users, data, activities and resources, they can create a problem for IT and compliance leaders. At a practical level, can businesses scale at the human, supply chain and financial level if sales rocket by huge volumes?
Business data, often managed by the IT department, is governed by rules, such as about which apps can access it, and guidelines to protect sensitive and proprietary information. Accessing or changing that data creates potential risks to the business and requires oversight. So, how would that work, particularly considering that different vendors have different cost structures that can impact adoption and scaling?
Tom Nielsen, founder of Saltcorn, a platform for building database web applications, said that “scalability is often cited as an obstacle to adoption in different ways across proprietary and open-source platforms. Proprietary platforms often tie their usage fees to resource consumption meaning that as an app scales, costs can amplify disproportionately.”
He highlights other issues that can include:
- Proprietary platforms changing their pricing structure with the consequence that many apps built without venture capital investment become unaffordable to run.
- Proving scalability across large multi-node deployments has not been a focus for most open-source platforms; they must demonstrate resilience in the face of load spikes and large data volumes.
- There is a certain scalability cost associated with adopting no/low code as opposed to traditional software engineering. Database queries, in particular, are likely not optimized, but most platforms should adequately serve those built for internal company use.
Related Article: Why Organizations Still Struggle With Deploying AI
Responsive Businesses Can Scale Low-Code
The key to building responsible and reliable low-code solutions is to create an oversight team to encourage responsible, cost-effective use while instilling an understanding of business requirements.
It may sound easier said than done, but by encouraging adopters to work within the established order of business, perhaps by creating incentive-based programs to improve performance or create new products, shadow apps are less likely to emerge. With financial or other incentives, workers can be taught low-code tools in a safe environment and shown the importance of data and compliance rules.
And, rather than just running with a smart new application, a brief handover period for testing by IT for security and data issues won’t stop the show, but it will help ensure there are no business-breaking risks in a new feature.
On the plus side, low code works both ways. It can support the automation of things like legal and regulatory compliance to unlock efficiencies and improve business performance. The key is using low code where it has the greatest impact for the organization.
“Choosing the right software is important, but more important is ensuring the correct people and processes are in place to support your technology,” said Anthony Abdulla, senior director of product marketing for intelligent automation at Pegasystems.
Learning Opportunities
He suggests a cross-functional team approach that clearly defines roles and responsibilities in building and maintaining applications, blending technology, analytics and business expertise. This approach, he said, places responsibility for building and maintaining applications on the department rather than on IT or individual builders, thereby reducing the burden on enterprise IT while eliminating the risk of unsanctioned projects or applications.
In his view, adopting such an approach creates scalability, greater efficiency and enhanced governance of low code while helping to ensure the organization can continue to grow and evolve.
Related Article: How Generative AI and Low-Code Can Work Together
A Rapid Evolution
As the availability of low-code tools within productivity apps continues to simplify the deployment process, adoption is expected to rise, and costs will come down. And as more users test tools and share knowledge, they will cut the time to deliver solutions, increase internal awareness and boost value.
Most IT and security leaders are well aware of the benefits and risks of low code, but it’s also important to have a handle on its evolution across the business, especially as proven use cases flood in.
Take, for instance, the case of aviationscouts GmbH, a German company that, after moving from Excel to a low-code solution, managed to triple its sales and the amount of data its team could handle. Or the case of Syneos Health, which used a low-code-powered automated clinical trial oversight system to manage its critical process and saved $750K doing so.
IDC’s “Scaling Low Code Success” report studied how organizations use low code for strategic projects, speeding up application and automation development. Companies are quickly embracing the potential, and Gartner predicts that by 2025, “70% of new applications developed by organizations will use low-code or no-code technologies, up from less than 25% in 2020.”
Meanwhile, vendors continue merging AI and low-code features. Larry Ellison at last fall’s Oracle Cloud World highlighted Oracle’s APEX Low-Code product, which he said addresses the issue of risk by delivering security and fault tolerance for enterprise-scale low-code initiatives.
And now, low-code solutions imbued with AI are emerging at a rapid pace. Take the just-launched version of Appian Platform for process automation for example with its AI Skill Designer. With some notes from the worker, AI can examine a document or process, extract the key data points or meta-data, mix it with other information to build an application and create a new or improved process. All in a business-friendly and secure manner.
The change is happening so fast that some experts and regulators are now asking for a pause to give everyone time to assess the impact of it all. The White House has also taken an interest in legal protections for those impacted by AI-powered services, and any future legislation could help tackle the considered risks around low-code — and other innovations.
All of this creates a volatile, ever-moving landscape where businesses that get it right can find themselves with a substantial competitive advantage. The risk, however, is getting it wrong.
About the Author
Geoff Spick is a Bournemouth, England-based tech writer with over 25 years of experience across Gartner, Infor and a host of startups and SMBs as a freelance marketing content creator. With fingers on the pulse of digital business, automation, no/low-code and productivity solutions, he is familiar with most bumps on the road to digital transformation.
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