Innovation at scale: A primer on leveraging low-code AI

Rapid technological advances, changing customer expectations, and ever-evolving competition and market demands make agility the most valuable strategic capability a business can have. That said, agility can be limited by high costs, extended timelines, and a dependency on specialised technical talent. From resource-intensive industries like construction to high-stakes sectors such as finance and healthcare, organisations are forced to respond swiftly to demands. Traditional coding models demand extensive budgets, highly specialised expertise, and lengthy development cycles, creating bottlenecks that make it difficult for businesses to keep up with evolving customer and market expectations.

Fortunately, the rise of low-code AI is rewriting this narrative by enabling companies of all sizes to innovate, adapt and launch products at the right time.

Low-code AI is a technology that reduces the need for extensive coding and enables non-technical users and developers alike to create AI-powered applications faster. This shift democratises innovation, empowering people across departments to become creators and problem solvers. As a result, companies can respond to changes in the market quickly, with streamlined workflows and automation that allow them to remain competitive.

Low-code AI’s impact stretches beyond just software development to transforming business operations and becoming essential in reshaping products, services, and processes. Low-code AI platforms offer a solution to challenges, providing an accessible way for businesses to reduce costs, speed up development, and create powerful, data-driven applications without waiting months or even years.

There are many success stories of companies that have leveraged low-code AI platforms such as Zoho, Mendix, Outsystems, Power Platform, etc., with big returns. One example is the story of BAM Infra, the Netherlands’ construction company, which employs over 27,000 people and generates annual revenues exceeding €7.4 billion. BAM’s case study showcases how low-code platforms can revolutionise even the traditional industries. Faced with rising competition and a rapidly changing landscape, BAM turned to low-code AI to transition from a disrupted company into a disruptor. For instance, when the Dutch government mandated the installation of smart metres across the country, BAM found itself competing against an established software vendor that lacked installation capabilities but had the technological edge. However, with the use of the Mendix platform, BAM was able to rapidly develop and offer an integrated software solution that managed the entire smart metre installation, resulting in securing a contract to install over one million smart metres.

Beyond this, BAM’s use of Mendix to develop solutions reportedly saved the company an estimated €160,000 annually in operational costs and freed up around 2,000 hours each year. One standout achievement is the development of a budget management application, CASH-U, which was prototyped in just a few days. This app provides real-time visibility into project budgets, enabling on-the-spot business decisions that reduce waste and improve efficiency. Through these innovations, BAM has fortified its position in the market and now attracts software development talents, further reinforcing its disruptive impact within the industry.

While low-code AI platforms present substantial benefits, there are challenges such as data quality and concerns over privacy and security that must be addressed to ensure that the solutions developed are effective and ethically compliant. For organisations adopting low-code AI, it is imperative to prioritise data governance, transparency and explainability, Implement robust data management practices, develop ethical guidelines to mitigate bias, conduct regular security assessments to identify vulnerabilities and so on.

More so, ensuring data privacy and regulatory compliance can pose difficulties, particularly for businesses operating across multiple jurisdictions. However, many low-code AI platforms offer built-in tools that support compliance across jurisdictions making it easier for organisations to meet data protection standards. This combination of built-in compliance and strategic governance makes it possible for businesses to leverage low-code AI with confidence while minimising potential ethical and legal risks.

Without a thought, low-code AI offers many advantages: including empowering companies to innovate faster, democratise development, and provide a pathway for continuous growth in a world of rapid change.

For companies ready to innovate, adapt, and scale faster and remain relevant, low-code AI provides the capabilities to keep up with the evolving change, shape the future and meet the demands of an unpredictable future with agility and resilience.

David Afolabi leads solutions architecture and engineering programmes, including cloud solutions, integration, intelligent automation, and analytics solutions at BMG.