As the world emerges from the pandemic, the global business landscape continues to be shaped by persistent uncertainty. This volatility is pushing organizations to embrace business agility as a core capability rather than a temporary response.
As technology becomes integral to day-to-day operations, IT must move at the pace of market change and act as a key enabler of business innovation. Building a flexible application portfolio and accelerating application development are now critical success factors for achieving both speed and agility. In this context, the composable enterprise model, low-code, and generative AI (gen AI) together form a powerful trio to advance this strategic goal.
Everything is up in the air: global uncertainty and the race for speed
2023 has been a particularly challenging year for the global economy, marked by a prolonged recession, unforeseen catastrophic losses, and rising political tensions. In this climate of current and potential market uncertainty, many international organizations have adopted a pessimistic outlook. According to a PwC survey [1], 45% of corporate leaders fear for their companies’ financial health over the next ten years if they stay on their current trajectory, up from 39% just a year earlier. While the specific reasons for this lack of confidence differ by organization, global corporate leaders consistently highlight changes in technology, customer preference, and regulations as the three most pressing challenges to address in the next five years.
As markets move faster and in less predictable ways, speed and agility have become critical sources of competitive advantage. A Harvard Business Review study [2] concludes that companies which prioritize speed tend to achieve stronger financial performance because they are quicker at understanding and delivering what customers need. The study found that organizations with the most robust five-year compound annual growth rate (CAGR) and margin expansion, such as Tesla and Amazon, are more likely to have developed core capabilities that accelerate operational speed.
What is the composable enterprise model and how does it enable speed at scale?
The composable enterprise is a Gartner-defined model in which business functions are broken down into modular, Lego-like packaged business capabilities (PBCs) that can be rapidly assembled via APIs and event streams to form applications. This approach is designed to help large organizations move at the pace of market change while still operating at scale.
To stay afloat in a fast-changing environment, companies need to move at least as fast as the markets they serve. Yet size is often negatively correlated with speed, which means large organizations typically struggle to make changes quickly. The composable enterprise model addresses this challenge by offering a Lego-like way of viewing corporate operations.
In this model, business functions are decomposed into packaged business capabilities (PBCs). These are stand-alone, fully autonomous components that are recognized and consumed as complete units by business users, such as systems that manage supply orders or production lines. Connected through APIs and event streams, PBCs can be assembled and reassembled to create applications tailored to specific individual and business needs.
This modular architecture ensures that the application portfolio remains flexible. Applications can be assembled, reassembled, and extended to align with changing corporate strategies, which in turn enhances overall business agility and adaptability.
As enterprises move toward composable architectures, IT must step out of a traditional back-office role and become an active enabler of business innovation. However, the conventional IT approach does not support the composable enterprise model well, primarily because it is too inflexible. Corporate application portfolios are often limited, closely tied to past strategies, and lack the ability to evolve at the pace of market change.
A survey by OutSystems [4] shows that most companies take 3–6 months to develop web and mobile applications, as reported by 61% and 60% of respondents, respectively. Half a year may not sound excessive, but in make-or-break moments such as the pandemic, such delays in application development can easily threaten a company’s survival.
For IT to truly operate at the pace of market change, it is essential to build an application portfolio that is composable, flexible, and tailored to evolving needs. Yet that alone is not enough. Organizations must also be able to develop individual applications in a matter of weeks rather than months. In this context, low-code and generative AI are emerging as key drivers for achieving rapid application delivery.
Double the force with low-code
The popularity of low-code has increased exponentially in recent years, with up to 70% of surveyed organizations now considering low-code a core part of their business [5]. Against that backdrop, three benefits of low-code stand out:
Speed up the software development process
Low-code platforms provide drag-and-drop capabilities that allow developers to place components onto a visual canvas. Users can design applications through simple, visual logic instead of hand-coding thousands of lines. They can also reuse and combine pre-built functions to create customized applications without starting from scratch. According to a Statista survey, 29% of respondents report a 40% to 60% reduction in development time when using low-code platforms compared with traditional development approaches [6].
Lower time-to-market
The ability to reuse components also reduces the amount of testing required and, in turn, lowers time-to-market. Reusable components are tested in advance, so new applications built on top of them do not need to go through the entire testing process again. Reflecting this advantage, 84% of surveyed enterprises cite faster speed-to-market and reduced IT constraints as key reasons for incorporating low-code into their operations [7].
Better resource allocation
By leveraging low-code, businesses can make better use of their human resources, as citizen developers (developers outside formal IT departments) can be more actively involved in building business applications. With forecasts that 70% of new applications developed by enterprises will use low-code platforms, the role of citizen developers is becoming increasingly prominent, especially in the context of ongoing IT talent shortages [8].
Gen AI: Accelerating the already fast
Both AI and low-code have been praised for reducing the effort required to build applications, but they approach this goal in very different ways. AI accelerates development by generating code directly from natural language prompts, while low-code provides a visual environment where users drag and drop pre-built components and configure workflows.
These two approaches, however, come with distinct strengths and limitations that can hinder effective application development if used in isolation. The key differences between AI-generated code and low-code platforms can be summarized as follows:
| Aspect | AI-generated code | Low-code platforms |
|---|---|---|
| Development approach | Generates raw code from natural language prompts. | Offers a visual interface with drag-and-drop, pre-coded elements. |
| Customization and function range | Highly customizable, with virtually unlimited functions. | Functions are constrained by the available pre-built components. |
| Who can use it effectively | Requires users with sufficient coding knowledge to interpret and refine the generated code. | Accessible to users with limited coding expertise, who can still understand and use visual outputs. |
| Main limitation | Produces raw code that must be reviewed, adjusted, and maintained by someone with programming skills. | Limited flexibility and lower levels of customization because outputs depend heavily on pre-coded elements. |
In other words, AI offers depth of customization but assumes a relatively high level of technical fluency, whereas low-code prioritizes accessibility and clarity but trades away some flexibility and functional breadth.
When combined, low-code and generative AI form a highly complementary pairing. Their respective strengths and weaknesses align in ways that can unlock a new level of speed and customization in application development. Integrating gen AI into low-code platforms can significantly expand customization options while still shielding users from the complexity of raw code.
AI-powered low-code platforms do more than simply accelerate development; they accelerate an already fast process. Traditional low-code tools enable users to assemble applications by dragging and dropping components and designing workflows. Platforms infused with gen AI, such as Microsoft Power Platform, go a step further by removing much of this manual configuration and replacing it with natural language prompts.
In practice, this means a user can describe desired functions or business problems in everyday language, and the platform can generate an application based on those descriptions. This shift turns the visual building experience into a prompt-driven one, lowering the barrier even further while increasing what can be built.
This is only one example of the possibilities emerging from the convergence of low-code and AI. With leading low-code vendors such as OutSystems and Mendix actively exploring how to embed AI into their platforms, a wave of new, more capable applications is very likely on the horizon.
Despite the urgency, defining a feasible and optimized roadmap for adopting low-code and generative AI can be overwhelming, especially given the wide range of AI-powered low-code platforms available on the market. To address this challenge, partnering with an experienced, end-to-end IT service provider is often the most effective approach.
With more than 25 years of experience and an extensive ecosystem of low-code partners, including OutSystems, PowerApps, Pega, and Mendix, FPT is trusted by leading organizations to accelerate their low-code transformation journeys. Learn more about FPT’s low-code/no-code solutions here.
Conclusion
In an era where disruption has become the norm rather than the exception, long-term resilience now hinges on how quickly a business can sense change and respond with new digital capabilities. The composable enterprise model offers the structural agility to do exactly that, breaking monolithic operations into reusable, API-connected building blocks that can be rapidly reshaped as strategies evolve. At the same time, low-code dramatically accelerates how those capabilities are delivered, while gen AI turns this speed into true scale by adding natural-language-driven customization and automation. Ultimately, the winning move is not just adopting tools, but charting a thoughtful roadmap—often with experienced partners like FPT —to turn this trio into a sustained engine of innovation and growth.
