Latest news with #lowcode
Tahawul Tech
6 days ago
- Business
- Tahawul Tech
Kissflow outlines the link between digital transformation and app development
Prasanna Rajendran, Vice President – EMEA, Kissflow, explains how low-code design methods are accelerating application software development and thus lifting up both citizen and professional IT developers in this exclusive article. Across the Middle East and Africa (MEA), governments and industries are busily equipping themselves for the digital future. IDC estimates that as much as 12% of business units' budgets is being allocated to digital business initiatives as organisations work to create compelling experiences for the employees and customers that demand them. To counter the threat to competition, shareholder pressure, regulatory requirements, shadow IT and more, they must do so at speed and scale. And because the regional IT talent shortage is a reality impacting organisations across the spectrum, many are now turning to low-code and no-code development platforms to maximise their existing resources beyond the IT department Low-code, high value To understand this shift better, we spoke to CIOs in the enterprise and shared what we learned in our Citizen Development Trends report. We found that a majority (62%) of organisations around the world believe citizen development programs can accelerate digital transformation. At the time of surveying, 86% of respondents had citizen development programs in place, with almost half (45%) having been in operation for more than a year. In MEA, earlier Kissflow research showed that a third (33%) of organisations were trying to address resource constraints in custom app development and faced the prospect of having to turn to expensive third-party developers. Some 80% of regional tech leaders see the refinement of the software development process as vital for effective digital transformation. To make citizen development programs work, business and IT teams must collaborate. This goes beyond just sharing updates—they have to work together as one team right from planning to execution. To bring shadow IT into the light, non-technical employees must find themselves in a permissive and supportive culture where IT is democratised, and upskilling is incentivised. Low-code brings this situation to reality by clearly highlighting the responsibilities and boundaries. All the business-oriented initiatives that technical staff find trivial can be handed over to business-trained employees to implement. Under the right governance, domain experts can skip requirements gathering and analysis and go straight to design. Since a lot of code is automatically generated, implementation times are reduced, and testing runs more smoothly. Through low-code, software development becomes much faster, going from timescales in months or years to weeks or days. Business innovators no longer need to join a queue. They can start building under the ever-watchful eye of the platform, which corrects errors, enforces governance standards, and suggests areas for improvement. Employees and customers receive enhancements to their experiences more frequently, leading to increased satisfaction levels among both groups. Bigger, better, faster When it comes to the regional skills gap, organisations that adopt low code solve three problems at once. First, they acquire the skills they need more quickly. Second, they increase talent retention rates by meaningfully fleshing out the daily routines of tech-savvy employees. And third, they increase the success rate of digital transformation because requirements are no longer lost in translation during the use-case analysis stages. Development backlogs are drastically reduced under low-code programs. When citizen developers are in play, bigger projects can still monopolise IT's attention, but with small windows dedicated to code reviews of citizens' work. Over time, reviews will become easier and faster, as signed-off solutions become reusable templates. Citizen developers will gradually build up libraries of these templates and create more ambitious applications as their experience grows. Not overnight, but certainly quite quickly, the business becomes scalable. Low-code tools are adaptable, so citizen developers can use them to manage changing requirements and demands. And as the business reaches new levels of scalability it also becomes more agile. That is important in MEA markets, which are home to youthful, tech-savvy populations hungry for the next digital experience. As the citizen developer experience-pool fills, low-code platforms offer the right functions to take the citizen vision further, but they also help IT teams work on larger projects. Many built-in features and integrations allow seasoned software professionals to accelerate their work. So, a single investment in the right low-code platform can benefit both citizen developers and IT. From A to Z It is not often one can point at a digital investment that benefits IT, DevOps, finance, human resources, warehousing, logistics, R&D, and everything in between. From the straightforward building of a self-service HR application to the integration of AI for predictive analytics in fraud prevention, low-code no-code development has something for every stakeholder. Image Credit: Kissflow
Khaleej Times
7 days ago
- Business
- Khaleej Times
AI-enhanced low-code platforms to fundamentally transform SMEs
AI-enhanced low-code platforms will fundamentally transform competitiveness of small and medium enterprises (SME) in the next three to five years by democratizing access to sophisticated technology, experts say. 'These tools will enable small businesses to rapidly develop custom applications, automate routine processes, and implement data-driven decision-making without specialized technical expertise or significant capital investment, effectively levelling the competitive landscape with larger enterprises,' Hyther Nizam, President Middle East and Africa (MEA) and Vice President of Products at Zoho, told Khaleej Times in an interview. The strategic advantage will shift from who can afford the most expensive technology to who can most creatively apply these accessible tools to solve business problems and enhance customer experiences. 'SMEs that embrace these platforms will benefit from accelerated innovation cycles, reduced operational costs, and the ability to quickly adapt to market changes — transforming from technology followers into agile market disruptors capable of identifying and capitalizing on new opportunities faster than their larger, less nimble competitors,' Nizam said. While SMEs adopt low-code platforms, operational challenges come first, with process automation leading the way. SMEs target repetitive, manual workflows like data entry, inventory management, and approval processes that drain resources and introduce errors. 'They also prioritize data consolidation and reporting solutions, breaking down siloed information across departments to create unified dashboards that provide real-time visibility into business performance without specialized technical skills,' Nizam said. On the customer-facing side, SMEs quickly implement customer management solutions that centralize communication histories and purchasing patterns, enabling more personalized service. They also develop self-service portals and mobile apps that allow customers to place orders, check status updates, or access information independently, reducing support costs while improving satisfaction through 24/7 accessibility and consistent experiences. The adoption of AI-driven low-code development varies significantly between SMEs and large enterprises due to differences in resources, priorities, and operational needs. 'SMEs typically prioritize rapid, cost-effective solutions that enable non-technical users to build and deploy applications quickly, helping them overcome skill shortages and accelerate digital transformation. Their focus is on agility, reducing development costs, and improving operational efficiency with minimal reliance on IT teams. However, they remain cautious about security and vendor lock-in risks due to limited resources,' Nizam said. In contrast, large enterprises use AI-driven low-code platforms to complement their existing IT and AI teams, aiming to accelerate development cycles while maintaining strict governance, security, and compliance standards. 'They focus on integrating low-code solutions with complex legacy systems and scaling innovation across multiple business units. While speed and ease of use remain important, their priorities emphasize managing complexity, ensuring enterprise-wide control, and enabling citizen developers within a robust framework. For enterprises, another common use case for low-code platforms is modernisation of their digital infrastructure. Thus, SMEs seek simplicity and speed, whereas large enterprises balance agility with control and scalability,' Nizam said. Professional services and retail/e-commerce sectors are leading AI-powered low-code adoption among SMEs, with professional services firms rapidly implementing client management systems and automated reporting tools that leverage AI for insights and document processing. Manufacturing and logistics companies are increasingly implementing solutions for supply chain visibility, predictive maintenance, and quality control applications that leverage AI to optimize operations and reduce costs, particularly as these sectors face intense pressure to digitize processes while addressing labor shortages and supply chain volatility. Retailers are embracing these platforms to create personalized shopping experiences, inventory optimization systems, and omnichannel customer engagement solutions without extensive development resources. Healthcare SMEs follow closely behind, adopting AI-powered low-code platforms to streamline patient scheduling, billing workflows, and regulatory compliance tracking while maintaining strict data security. Beyond app building, AI is helping SMEs optimize ongoing business processes by automating repetitive tasks, improving decision-making, and enabling rapid adaptation to market changes. 'For example, AI-powered chatbots handle customer service inquiries around the clock, reducing response times and freeing staff for more complex issues, while predictive analytics help businesses forecast demand, manage inventory, and personalize marketing campaigns-leading to increased efficiency, cost savings, and higher customer satisfaction. Platforms like Zoho Creator, with its new Co-Creator capabilities, make these benefits accessible to SMEs by integrating machine learning for predictions, object detection, and workflow automation without requiring coding expertise,' Nizam said. The Middle East, particularly Arabic-speaking markets, is experiencing accelerated low-code adoption driven by ambitious national digital transformation initiatives and diversification strategies. 'Government-backed programmes in UAE, Saudi Arabia, and Qatar are actively promoting digital skills and technology adoption among local SMEs, with particular emphasis on solutions that support Arabic language capabilities and regional business practices,' Nizam said. Financial services and retail sectors are leading adoption in the region, with a distinct focus on mobile-first applications that cater to the region's high smartphone penetration rates. A notable regional trend is the emphasis on platforms that seamlessly integrate with Islamic banking requirements and support Arabic-language customer interfaces. 'While adoption initially lagged behind global averages, growth rates now outpace many Western markets as Middle Eastern businesses leverage these technologies to overcome technical talent shortages and rapidly modernize legacy systems, with particular interest in solutions that combine AI capabilities with low-code development to accelerate their competitive positioning in global markets,' Nizam said.. Many SMEs mistakenly believe AI-powered low-code platforms require significant technical expertise to implement, when in reality these solutions are specifically designed for business users with domain knowledge rather than coding skills. Another misconception is that these platforms can only build simple applications, when the reality is that modern systems can create enterprise-grade solutions with complex workflows, integrations, and security features that rival custom development. 'SMEs often incorrectly assume adopting these platforms means replacing their existing systems entirely, when most are designed to integrate with and enhance current infrastructure. Perhaps most significantly, many small business leaders believe implementing AI-powered low-code solutions requires large upfront investments, not realizing many platforms offer scalable pricing models that allow starting small with focused applications that demonstrate quick ROI before expanding — making advanced technology accessible even with limited resources,' Nizam said.
Forbes
21-05-2025
- Business
- Forbes
Low-Code, No-Code And Robotics Are Reshaping Digital Transformation
Sanjoy Sarkar - SVP, Director - Application Development & Support, First Citizens Bank . getty Over the course of my decade in technology leadership, I've had the opportunity to guide numerous large-scale digital transformation initiatives across banking, consulting and enterprise technology. From merger-driven system integrations to enterprise-wide process reengineering, low-code/no-code (LCNC) platforms and intelligent automation have consistently played a pivotal role in my work. Whether we were empowering non-technical business users to prototype their own solutions or helping IT teams accelerate delivery cycles, LCNC has enabled us to deliver real impact fast. To me, LCNC and robotic process automation (RPA) aren't trends—they're essential pillars of modern enterprise strategy. They empower teams, reduce friction and enable agility in ways we couldn't have imagined a decade ago. This article is my attempt to demystify that journey. In my experience, choosing the right LCNC platform can make or break a digital transformation initiative. Over the years, I've evaluated and implemented several LCNC tools across different organizations, and I've learned that it's not just about flashy features or slick UI. It's about how well the platform scales, how easily it integrates into your existing tech stack and whether it can handle both simple use cases and enterprise-grade complexity. One lesson I've learned the hard way is that governance cannot be an afterthought. I've seen what happens when teams build freely without controls—and it often results in shadow IT, duplicated logic and compliance risk. That's why I always emphasize selecting platforms with built-in role-based access control (RBAC), version control and audit trails. These features allow business users to innovate, but within a framework that IT can trust. And don't forget to assess the vendor's track record, community ecosystem and support model—because the right partner matters just as much as the right platform. Security, Compliance And Best Practices As organizations expand their LCNC and RPA footprints, security and compliance must stay front and center. In regulated industries like finance and healthcare, this isn't optional—it's mission-critical. I always advocate for a zero-trust approach: strict authentication, encrypted data flows and well-defined access policies. LCNC tools often move fast—but security has to move faster. I've led programs where we embedded automated testing, code scans and centralized monitoring into our development lifecycle from day one, which made a huge difference in identifying risks early. And finally, none of this works without culture. Building a security-first mindset across teams—through training, awareness and ongoing engagement—has been one of the most effective ways I've seen to reduce risk while keeping innovation flowing. Lessons From The Field: Real-World Challenges And How To Avoid Them With RPA, one common misstep I've seen is jumping straight into bot deployment without first optimizing the process. I once inherited a set of bots that were automating a poorly designed workflow. The result? Constant bot failures and more rework than relief. We eventually paused the automation, reengineered the process with business SMEs and only then deployed bots—this time with long-term success. In one of my initial LCNC rollouts, I discovered collaboration is a must for LCNC. LCNC doesn't mean no IT—it means more intentional collaboration between business and IT. Metrics And ROI Considerations To make a compelling case for LCNC and robotics, organizations must measure the return on investment (ROI) and business impact of these technologies. Enterprises leveraging low-code platforms can reduce their application development time by over 50%, allowing them to respond faster to market demands. Additionally, automation through RPA and process orchestration has led to an average operational cost reduction of 30%. These platforms also enhance workforce productivity, with reports indicating that a majority of workers could save six hours a week with automation, allowing them to focus on higher-value strategic initiatives. Furthermore, companies implementing automated workflows have observed improvements in compliance and risk management, reducing regulatory penalties and operational errors. Enterprises that effectively embrace LCNC and robotics are positioned to gain a significant competitive advantage. This technological shift can enable businesses to launch new digital offerings faster, optimize operational costs, enhance compliance and governance and foster a culture of innovation. More importantly, this transformation is reshaping the future of work, empowering organizations to build resilient, high-performing and agile digital enterprises. The question is no longer about whether to adopt LCNC and robotics, but rather how fast enterprises can harness their potential to stay ahead in the digital race. These aren't just technologies to me. They're tools I've used to solve real problems, often under immense pressure. Whether it's during a crisis, a merger or a daily operations challenge, LCNC and RPA have consistently proven their value. More than that, they've changed the way people work—and how they feel about their work. That's why I remain passionate about driving this transformation forward. Disclaimer: The views and opinions expressed in this article are solely my own and do not reflect the views of my employer. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Forbes
16-05-2025
- Business
- Forbes
Beyond No-Code: Windsurf's SWE-1 And More
Logo of this company Winsurf It's only been a few months since developers started using the new term 'vibecoding,' but new LLM capabilities put the no-code/low-code movement into hyperdrive. Now we have brand new announcements of a frontier model by Windsurf, SWE-1, that advances beyond no-code into an overall model approach to software engineering. Let's look back a bit at how we got here, and what kind of research are going on in the world of software development. First of all, no-code refers to the use of AI models to generate the code needed for an application or given resource without humans writing that code themselves. But as experts point out, this is not the entirety of what software engineers or software developers do. There's a context to the code that could also conceivably be automated. Check out this language in an academic paper from 2024, maintained at the ACM Digital Library: 'The relevance of low-code / no-code development has grown substantially in research and practice over the years to allow nontechnical users to create applications and, therefore, democratize software development. One problem in this domain still persists: many platforms remain low-code as the underlying modeling layer still requires professionals to write/design a model, often using Domain Specific Languages (DSLs). With the rise of generative AI and Large Language Models (LLMs) and their capabilities, new possibilities emerge on how Low Code Development Platforms (LCDPs) can be improved.' What we have here is the hint or suggestion that automation systems can look beyond just the generation of code, and into the life cycle of writing or designing something. There's also some interesting coverage of this idea in a resource from the Software Engineering Institute at Carnegie Mellon that introduces the term 'model-driven engineering' (MDE). Authors write: 'In this report, we use the term MDE to refer descriptively to a software development approach that treats models as the primary artifacts created and used by software lifecycle processes. The enabling tools and technologies include a broad spectrum of capabilities that may provide value for developers, acquirers, and end users.' That broad spectrum of capabilities is what innovators are looking at in exploring how to broaden no-code into democratizing the entire software development life cycle. Now, this week, we hear that Windsurf, a company known for its code automation approach, has a new family of AI models that are looking to do this exact thing. 'Writing code is only a fraction of what engineers do,' said Varun Mohan, CEO and co-founder of Windsurf, in a press statement. 'To truly accelerate software development by 99%, we had to move beyond 'coding-capable' models and build software engineering-native models. SWE-1 is our first step in that direction, building a foundation for the future state.' In the SWE-1 suite, there's SWE-1, SWE-1-Lite, and SWE-1-Mini. In describing the utility of the tools, Windsurf Co-founder Anshul Ramachandran uses the term 'flow awareness.' (for context, see this interview I did with Ramachandran at Davos). 'Flow awareness lets us see exactly where models succeed or fail, down to the individual decision point,' Ramachandran explains. 'That feedback loop is our competitive edge.' Maybe if you're interested in this process and what SWE-1 brings to the table, you want a little more detail… Some of the background of this type of pioneering involves what programmers typically do during a project. They write code, yes, but they use a set of three important resource environments – the IDE, the terminal, and the browser. The IDE is the environment where programmers often write the code and analyze it. The terminal is where they run the code. Programmers may use browsers to test the code, or to get information on best practices from sites like Stackoverflow. In fact, many programmers, when asked about how they use AI, suggest that they're using Stackoverflow much less, because of code automation. In any event, a model that can traverse all three of these environments is going to be immensely valuable as a broad-based engineering tool. So that's a good place to start in researching where we are at with the NCLC movement. It seems like the goal is to keep pushing the ball forward in terms of what people can do without technical knowledge – how easy it can be to spin up an application or codebase with just a few prompts to an LLM. This is a space that many of us will be watching for a great deal of potential disruption.
