Introduction

Discover how the convergence of AI code generation and low-code platforms is reshaping the application development landscape. This article delves into the transformative effects of this synergy, offering expert insights that illuminate the future of tech and healthcare industries. Insightful analysis and commentary from leading professionals provide a deep dive into how these technologies are democratizing development and accelerating project timelines.

• Low-Code and AI: Complementary Technologies
• Game Changer for Tech and Healthcare
• AI Democratizes Low-Code Development
• Low-Code and AI Speed Up Projects
• AI Code Generation Revolutionizes App Development
• Convergence of Low-Code and AI

Low-Code and AI: Complementary Technologies

When I first encountered low-code platforms, I was amazed at how they empowered non-developers to shape their ideas into functional applications. But with AI-driven code generation emerging, I see a fascinating tension building between accessibility and automation. I recently worked with a team where the low-code tools enabled quick prototyping, but the AI-assisted coding tools outpaced them when we needed scalability. It was a reminder that these two technologies are complementary but can compete when it comes to specific use cases.

AI code generators shine in creating complex, customizable solutions far beyond the template-driven nature of low-code platforms. However, their learning curve and the need for technical expertise mean that low-code tools will remain invaluable to businesses prioritizing speed and ease of use. It’s not a battle of one replacing the other but rather a division of labor—AI for depth and low-code for breadth.

Moving forward, I see these worlds merging. Platforms might integrate AI for generating advanced code blocks, bridging the gap between simplicity and sophistication while giving end-users more control. This convergence could redefine how teams build, blending creativity with efficiency.

Alex Ginovski, Head of Product & Engineering, Enhancv

Game Changer for Tech and Healthcare

The combination of low-code application development and AI code generation will be a game changer, not just for the tech industry but also for sectors like healthcare, where efficient and customized solutions are needed. By using low-code platforms, you are making the development process more accessible to non-developers who touch and feel functional applications. AI code generation literally takes you one step further since these automated toolings allow you to automate repetitive code tasks and suggest real-time performant solutions.

For those who work in healthcare, it means they can expect their personalized tools to help with patient data management and communications driven by generative AI to be deployed faster and ensure simpler operations while supporting rigorous compliance requirements for the sector. We always preach about the power of what dead-end technologies can do to boost efficiency and this combination of low-code and AI is definitely a great example of that. The biggest challenge, however, will be to maintain these automated solutions as reliable, secure, and user-readable solutions over time.

Spencergarret Fernandez, SEO and SMO Specialist, Web Development, Founder & CEO, SEO Echelon

AI Democratizes Low-Code Development

In the world of low-code development, the rise of AI code generation is anticipated to further democratize the development process. For instance, tools that utilize AI for code suggestions and optimizations can significantly reduce the dependency on specialized coding skills, allowing more stakeholders to participate in app creation. This means businesses can expedite development timelines and innovate faster.

However, this integration will require robust collaboration between AI systems and human oversight to maintain code quality and security. It is essential for developers to adapt by enhancing their skill sets in AI tool utilization while advocating clear standards and practices.

Overall, this convergence could lead to more accessible and efficient software development, though it must be managed thoughtfully to avoid technical debt and maintain quality assurance.

Ben Miller, COO, Undetectable AI

Low-Code and AI Speed Up Projects

I see low-code and AI code generation working side by side to speed up projects. Routine tasks get done by machines. Skilled developers handle the tougher parts. My experience shows that human insight remains essential.

I recall a project where our team used an AI tool for simple coding. Our engineers reviewed every detail and solved hard problems. We met a tight deadline and delivered solid work. It confirmed my belief in the need for human oversight.

My advice is to keep your skills sharp and stay hands-on. Check all AI-produced code and solve problems with care. Learn continuously and think critically. A mix of smart tools and human expertise will lead to success.

Elmo Taddeo, CEO, Parachute

AI Code Generation Revolutionizes App Development

I recently experienced firsthand how switching from low-code platforms to AI code generation can transform the way we develop apps. We had a project that traditionally would have taken us six weeks to complete. With AI code generation, we built a working prototype in just two weeks. This not only boosted our efficiency and revenue but also allowed our subject matter experts to directly infuse their industry know-how into the product.

The beauty of AI code generation is its accessibility. It cuts through the layers of complexity that have long been a barrier in traditional app development. Instead of relying solely on extensive coding skills or being limited by low-code platforms, industry experts can now quickly turn their ideas into functional tools tailored to their specific needs.

My advice to fellow business leaders is to explore this innovative approach. Identify areas in your projects where speed and precision matter, and consider piloting AI-driven code generation. By doing so, you can empower your team, accelerate your development cycle, and create unique solutions that truly stand out in the market.

Candice DeVille, CEO, AI Copilot

Convergence of Low-Code and AI

The convergence of Low-Code Application Development and AI Code Generation represents a paradigm shift in how software is built, maintained, and deployed. Low-code platforms have traditionally empowered non-technical users and business analysts to create applications through visual interfaces, predefined logic, and reusable components. Meanwhile, AI-driven code generation enabled by advancements in large language models has the potential to automate the creation of complex logic, optimize performance, and even refactor existing codebases dynamically. As these two forces collide, we are witnessing an acceleration in software development cycles, reducing dependencies on manual coding while increasing accessibility for a broader range of users.

However, this evolution is not without its challenges. AI-generated code, while efficient, still requires human oversight to ensure correctness, maintainability, and security. Low-code platforms, by their very nature, abstract underlying complexities, which can lead to a lack of control over performance tuning, architectural decisions, and compliance requirements. The intersection of these technologies will likely lead to a hybrid development model where AI assists both low-code users and professional developers, offering code suggestions, detecting inefficiencies, and automating repetitive tasks while still relying on human expertise for governance and refinement.

In the long run, the biggest transformation will be in the role of developers. Rather than focusing on routine coding tasks, engineers will shift toward higher-level problem-solving, architecture design, and AI model tuning. Organizations will increasingly adopt AI-infused low-code platforms to build applications faster, but this will also necessitate new skill sets, specifically in AI governance, model interpretability, and strategic software engineering. Instead of replacing developers, AI-driven low-code solutions will augment their capabilities, much like how DevOps practices enhanced software delivery through automation without eliminating the need for skilled engineers.

Mohammad Haqqani, Founder, Seekario

AI Enhances Productivity for Engineers

The emergence of Large Language Models (LLMs) is reshaping the software development landscape, benefiting both software engineers and citizen developers, albeit in distinct ways. Software engineers are experiencing a paradigm shift where AI acts as an accelerant, automating routine coding tasks, debugging, and even architectural recommendations. This augmentation enhances productivity, allowing engineers to focus on higher-level problem-solving, system design, and optimization rather than getting bogged down by syntax-heavy implementation. However, while senior engineers benefit from AI-assisted development, junior developers may face a steeper challenge in proving their value, as many entry-level coding tasks are now automated by AI tools.

Conversely, LLMs significantly lower the technical barrier for citizen developers, democratizing software creation through natural language programming and low-code/no-code platforms. Business professionals, entrepreneurs, and non-technical users can now build applications, automate workflows, and query databases without deep programming knowledge. This shift empowers organizations to reduce IT bottlenecks and accelerate digital transformation, making software development more inclusive. However, while LLMs enhance accessibility, they do not replace the need for technical oversight-complex systems, scalability, and security considerations still require the expertise of software engineers.

Ultimately, the greatest beneficiaries of LLMs will be those who can integrate AI fluency with domain expertise. Software engineers who adapt to AI-driven development will transition into AI-augmented problem solvers, focusing on strategic thinking, system architecture, and AI governance. Meanwhile, citizen developers will leverage LLMs to build solutions without deep coding skills, but their reliance on AI-generated outputs means they will still require engineers to refine, validate, and scale their solutions. This evolving dynamic suggests that AI is not a zero-sum disruptor but rather a force multiplier, enhancing productivity across both technical and non-technical domains while shifting the nature of software development itself.

Mohammad Haqqani, Founder, Seekario

Both Engineers and Citizen Developers Gain

The rise of large language models (LLMs) is creating a fascinating shift in the software development landscape. It’s natural to wonder who will benefit most: seasoned software engineers or the increasingly empowered citizen developers. The truth is, both stand to gain, but in different ways. Engineers can leverage LLMs to automate repetitive tasks, accelerate coding, and even generate initial drafts of complex algorithms. This frees them to focus on higher-level design, architecture, and problem-solving, essentially supercharging their productivity and allowing them to tackle more ambitious projects.

On the other hand, citizen developers, those individuals with domain expertise but perhaps less coding experience, are seeing a new world of possibilities open up. LLMs can help them translate their ideas into functional applications with less reliance on traditional coding. Imagine a marketing manager being able to build a simple data analysis tool by describing what they need in plain language. This democratization of development could unlock a wave of innovation from those closest to the problems, leading to solutions we haven’t even imagined yet. It’s not about replacing engineers, but rather expanding the pool of those who can contribute to the creation of software.

Brandon Batchelor, Head of North American Sales and Strategic Partnerships, ReadyCloud 

Citizen Developers Benefit Most

Large Language Models (LLMs) are changing the game for both software engineers and citizen developers, but the biggest winners will be citizen developers. These AI-powered tools lower the barrier to entry, allowing non-technical users to build applications, automate tasks, and generate code without deep programming knowledge. Businesses can now train employees in no-code and low-code platforms, increasing efficiency and reducing dependency on traditional developers for routine tasks.

That said, software engineers will still have the edge when it comes to building, refining, and scaling AI-driven solutions. LLMs can generate code, but they still require human oversight to ensure accuracy, security, and efficiency. While citizen developers gain accessibility, software engineers who leverage AI for code generation, debugging, and automation will become even more valuable, focusing on high-level problem-solving rather than repetitive coding tasks.

Georgi Petrov, CMO, Entrepreneur, and Content Creator, AIG MARKETER

Introduction

Author: Niall McCarthy

Published: https://lordmatt.co.uk/technology/coding-and-development/the-most-significant-developments-in-web-development-for-professionals-and-why-it-isnt-ai/

“Will AI really kill the SaaS business application market, as Satya Nadella, CEO of Microsoft, has recently suggested? Or will the proportion of SaaS offerings dependent on AI simply grow?” Here is what 5 thought leaders have to say.

Interestingly, no-one fully agrees with Nadella…

AI Will Propel SaaS Forward

As the CEO of a cybersecurity firm, I’ve been closely watching the AI revolution unfold across various industries, including SaaS. Satya Nadella’s recent comments about AI potentially killing the SaaS market are certainly thought-provoking, but I believe the reality is more nuanced.

From my perspective in the cybersecurity world, I’ve seen how AI is reshaping our industry rather than replacing it entirely. We’re not seeing AI eliminate the need for cybersecurity solutions; instead, it’s becoming an integral part of them. I suspect the same will happen with SaaS.

AI isn’t the death knell for SaaS; it’s more like a supercharged engine that’s going to propel it into new territories.

In our own company, we’ve integrated AI into our threat detection systems, making them more efficient and accurate. But the core of what we do – protecting digital assets – remains unchanged. Similarly, I believe SaaS companies will incorporate AI to enhance their offerings rather than be replaced by it.

That said, the landscape is definitely shifting. Just last month, I attended a tech conference where several SaaS startups showcased AI-driven features that would have seemed like science fiction a few years ago. It’s clear that companies that don’t adapt to this AI wave might struggle to stay relevant.

However, it’s important to remember that AI, for all its power, still needs human oversight – especially in critical areas like cybersecurity. We’ve had instances where our AI systems flagged potential threats that turned out to be false positives, and it took human expertise to sort it out.

So, while I don’t see AI “killing” SaaS, I do think we’re moving toward a future where AI-powered SaaS becomes the norm. Companies that can successfully blend AI capabilities with their core services will likely thrive in this new ecosystem.

Ayush Trivedi, CEO, Cyber Chief

AI Enhances SaaS Platforms

I don’t believe AI will kill the SaaS business application market; rather, it will transform it. SaaS offerings will increasingly integrate AI, making them smarter and more adaptive to user needs. The proportion of AI-dependent SaaS solutions will undoubtedly grow, but that’s more of an evolution than an extinction.

In my experience, AI enhances SaaS platforms by automating workflows, delivering predictive analytics, and offering personalized user experiences. For example, we recently integrated AI into a customer management tool to predict churn rates and recommend proactive strategies. It didn’t replace the platform, it amplified its value.

Satya Nadella’s statement highlights a shift: companies that fail to adapt to AI will struggle, while those embracing it will lead the market. The key takeaway? AI isn’t killing SaaS, it’s making it indispensable. The future belongs to SaaS solutions that seamlessly combine AI with human-centric design to solve real business problems.

Nikita Sherbina, Co-Founder & CEO, AIScreen

AI Transforms SaaS Interaction

I don’t believe AI will wipe out the SaaS business application market, but it’s definitely going to change the way businesses interact with these platforms. SaaS will continue to grow, but it will evolve to heavily depend on AI to make services smarter and more intuitive. I’ve seen how AI already helps marketers make better decisions by analyzing data at a deeper level, which drives better results. I can only imagine how much further this will go.

For companies working with SaaS now, jumping on the AI train can’t be ignored. Don’t think of AI as a threat; think of it as a tool to enhance the service you’re already using. It will help optimize processes, improve customer experience, and scale efficiently. For any SaaS provider, AI isn’t just an option anymore—it’s part of staying relevant.

Natalia Lavrenenko, UGC manager/Marketing manager, Rathly

AI Reshapes SaaS Market

You know, I get why some folks think AI will “kill” the SaaS business app scene, but I’m not buying it. I see AI changing the game completely instead of taking it out. AI won’t wipe out SaaS, it’ll reshape it. Those who adjust and adapt will do well, and those who don’t? Well, they might just fall off.

We’re already seeing this in action. Take Microsoft 365 Copilot or Salesforce Einstein, for example. These tools use AI to make things smoother and give you insights in real time. Microsoft Word isn’t just about writing anymore; it can help you create proposals or reports in a smart way. And Salesforce? It’s not just a CRM tool anymore. It’s like having an AI buddy that understands customer behavior and helps with workflows. Sure, they’re still SaaS products, but AI is taking their usefulness up a notch.

What I think really matters here is the way people expect things to work. Customers won’t be happy with just tools that organize information anymore. They’ll want solutions that can act, analyze, and even make predictions. Picture a project management app that doesn’t just keep up with deadlines but suggests how to make timelines better. Or think about a marketing tool that can whip up entire campaigns based on what you want to achieve. SaaS companies that can’t keep up with this level of smartness might find themselves in trouble.

Business models are gonna change too. AI might push SaaS companies toward pricing based on performance. Instead of a flat monthly fee, users could pay based on the return they get from AI-driven suggestions or automations. This could open up access for smaller businesses and connect revenue to actual value delivered.

But let’s be real-AI is likely gonna consolidate the market. Big players like Microsoft and Google are gonna lead the way with their AI resources. Still, there’s definitely space for smaller SaaS solutions that tackle specific problems using AI. The trick will be staying flexible and willing to think outside the box.

For me, this isn’t the end of SaaS-it’s a whole new start. AI will be as important as cloud tech or mobile design, and the companies that jump on board will really stand out. The real question isn’t if AI will change SaaS; it’s whether the providers can keep up with all this change.

What do you think? Will AI make SaaS better, or are we just headed toward a market ruled by a couple of tech giants?

Carlos Palop, CEO, UniteSync

AI Deepens SaaS Integration

I doubt AI will “kill” the SaaS business application market. Instead, it’s more likely that SaaS providers will deepen their AI integrations to stay competitive. When we began using AI-driven analytics in our own quote-comparison software, it didn’t replace the platform, it enhanced it by offering faster insights and more targeted recommendations. If anything, that improvement boosted customer loyalty and positioned us for future growth. SaaS platforms that evolve with AI tend to discover new revenue streams and features that help users do their jobs more efficiently. While companies that ignore AI might get left behind, those that embrace it will probably see AI as a growth catalyst rather than a threat.

James Shaffer, Managing Director, Insurance Panda

OpenAI recently claimed that AI “singularity” is near. Is there truth to this claim? How does it make you feel?

Here is what 6 thought leaders have to say:

• Approach Singularity Claims Cautiously
• AI Advancements Are Rapid But Limited
• Singularity Claim Requires Skepticism
• AI Progress Sparks Cautious Optimism
• Singularity Concept Oversimplifies Intelligence
• AI Singularity Feels Like Hype

Approach Singularity Claims Cautiously

The idea of AI “singularity”-where AI surpasses human intelligence and becomes self-improving-has long been a topic of debate. While advancements in AI are progressing rapidly, claims that singularity is “near” should be approached cautiously and critically.

Current AI systems excel in specific tasks through vast data processing but lack the general reasoning, emotional intelligence, and adaptability of human cognition. The leap from advanced tools to autonomous, self-improving entities requires breakthroughs in understanding consciousness, ethics, and control mechanisms-challenges we’re far from solving comprehensively.

Personally, the prospect of singularity is both exciting and humbling. It inspires me to think about how we can responsibly design AI systems to enhance human life, not replace it. It also underscores the importance of creating ethical frameworks and collaboration between scientists, policymakers, and society to ensure AI development remains aligned with human values.

Rather than fearing singularity, I focus on how AI can complement human capabilities, solving complex problems in healthcare, education, and the environment. Whether or not singularity is near, it’s our responsibility to guide AI’s trajectory toward a future that prioritizes collaboration, safety, and inclusivity.

Marin Cristian-Ovidiu, CEO, Online Games

AI Advancements Are Rapid But Limited

The claim that AI ‘singularity’ is near is both intriguing and contentious. The concept of AI singularity, often associated with the idea that artificial intelligence will surpass human intelligence and become self-improving, has been a topic of debate for decades.

OpenAI’s statement reflects the rapid advancements in AI technology, particularly in areas like machine learning and natural language processing. However, whether we are truly on the verge of achieving singularity is still uncertain.

From my perspective, while AI has made tremendous strides, particularly in automation, data processing, and even creative tasks, the leap to true artificial general intelligence (AGI)—where AI can independently improve itself and surpass human cognitive abilities in every domain—feels like a far-off prospect. We’re still facing challenges with AI systems that require a lot of human oversight, training, and fine-tuning to perform at a high level.

The idea of singularity is exciting but also somewhat unnerving. If AI could truly become self-improving, it could bring about profound changes in society, both positive and negative. On one hand, it could accelerate innovation and help solve complex global challenges. On the other hand, there are concerns about the potential risks, including job displacement, loss of control, and ethical issues.

For me, the focus should be on using AI responsibly and ensuring that advancements are guided by thoughtful governance, transparency, and an understanding of the long-term impact on society.

The fear of singularity shouldn’t stop us from embracing the benefits AI offers, but it does serve as a reminder to approach these technologies with caution and a plan for managing potential consequences.

Georgi Petrov, CMO, Entrepreneur, and Content Creator, AIG MARKETER

Singularity Claim Requires Skepticism

The notion that the AI singularity is ‘near’ is a bold claim but should be approached with reasonable skepticism.

Though recent advancements like OpenAI’s progress with models such as the upcoming ‘o3 mini,’ reveal rapid strides in AI development, the so-called singularity – the point where AI surpasses human intelligence – is a speculative concept. There’s still major technical, ethical, and philosophical challenges to grapple with before we can confidently predict its arrival.

Devan Leos, co-founder & CCO, Undetectable AI

AI Progress Sparks Cautious Optimism

The claim that AI “singularity” is near sparks both intrigue and skepticism. While advancements in AI have been undeniably rapid, with models capable of generating sophisticated outputs and solving complex problems, we’re still far from a system that can truly mimic or surpass human general intelligence across all domains.

For one, AI systems remain highly specialized and reliant on vast amounts of pre-existing data, lacking the nuanced creativity, emotional intelligence, and moral reasoning inherent to humans. Plus, the singularity concept tends to oversimplify the complexity of intelligence itself—equating raw computational power to the multifaceted nature of human cognition.

As for how it makes me feel, it’s a mix of curiosity and cautious optimism. AI’s potential to revolutionize industries, improve lives, and solve pressing global challenges excites me. But it also highlights the importance of ethical guardrails, transparency, and collaboration in AI development to ensure it aligns with humanity’s best interests. Whether or not singularity is near, the journey toward increasingly advanced AI will shape our future profoundly, and that’s where the focus should be.

Hubertus Von Aulock, Editor in Chief, Config Craft

Singularity Concept Oversimplifies Intelligence

The idea of AI “singularity”—where AI surpasses human intelligence—is fascinating, but it’s also loaded with hype. While AI is making crazy leaps, we’re still far from a system that can fully replicate human intuition, creativity, and emotional understanding. Claims like this often oversimplify the complexities of both AI development and human intelligence. As for how it feels? A mix of excitement and caution. The tech has massive potential, but it also needs guardrails to make sure we’re steering it in a way that benefits everyone, not just a select few.

Justin Belmont, Founder & CEO, Prose

AI Singularity Feels Like Hype

The idea of AI “singularity” being near is fascinating but feels more like hype than reality right now. While AI is advancing rapidly and transforming industries, we’re still far from creating machines with true human-like intelligence or self-awareness. As a business owner, I see AI as a tool, not a threat—it’s all about how we use it. Honestly, it motivates me to stay adaptable and think creatively about leveraging these advancements to grow and innovate, rather than worrying about doomsday scenarios.

Tomasz Lewandowski, Business Owner | Web Designer, 2D Figure Painting