G2 2026 AI Agent Builder Grid: OutSystems Named a Leader
Earlier this month, OutSystems CEO Woodson Martin made 10 predictions about where AI is headed and where it’s taking us in 2026. These predictions are part of discussions that are ongoing in the OutSystems C-suite and among our VPs. In this blog, our CPTO, CIO, VP of Product, AI & AppDev, and our VP of Developer Relations weigh in with their thoughts for the coming year.
Luis Blando, CPTO
An AI reality check is coming in 2026
The widely circulated promise that AI will fundamentally change everything has fueled unsustainable market hype. We are quickly moving past the speculative, trillion-dollar dreams built on fragile revenue streams. In 2026, real impact will come from agentic systems in production that improve customer operations, improve accuracy, eliminate repetitive tasks, or streamline data quality assurance processes.
AI will be focused, trained, and deployed specifically to solve existing, high-value business problems. Organizations that successfully operationalize AI to drive concrete efficiency and measurable application delivery gains will be the winners in 2026.
AI development will focus on specialization and solutions tailored for specific workloads and industries
In 2026, AI development will be all about specialization instead of general-purpose use cases. Solutions will focus on specific workloads that deliver faster, more accurate results for specific business functions. Expect the AI conversation to move away from hype about a single “best model” toward thoughtful selection and integration.
Part of that conversation will also be vertical AI, which uses models trained on industry-specific language, workflows, and data that can solve problems that generic AI struggles with. Companies that make sure these solutions are robust and can handle variations in real-world data relevant to their specific task are poised to succeed in 2026.
Tiago Azevedo, CIO
Software will fade away as agent-as-a-service delivers outcomes
The agent-as-a-service market is projected to expand from $5.1 billion in 2024 to $47.1 billion by 2030. In 2026, we’ll see more agent subscriptions and services that operate across multiple repositories and databases without discriminating between backend systems and fewer SaaS instances. This means that employees will command groups of AI agents that orchestrate workflows across systems instead of opening multiple tabs to use different software or SaaS platforms. Real, tangible outcomes that drive business forward will be the stars of the show, not the software that gets them there.
Enterprise AI infrastructure needs will change how data is stored, managed, used, and accessed by applications
Agentic AI and AI-driven workloads require reliable data storage, information streamed in real time, events organized by context, and the reuse of data for new models. Therefore, the data infrastructure to support them will be expected to include powerful compute (CPUs, GPUs, TPUs), high-performance networking, scalable storage, and robust security and governance measures.
That’s the reason why the enterprise AI data infrastructure market is headed to a $7 trillion valuation in 2030. To meet the surging demand, companies like Dell are enhancing their AI data platforms now so enterprises can convert distributed data into more reliable AI outcomes in 2026.
Agentic AI will rehumanize the enterprise
In 2026, the rate at which agentic AI automates mundane and repetitive tasks will grow exponentially as the technology matures and multiagent solutions become the norm. That will free up people to focus on creativity, strategy, and genuine human connection. Uniquely human soft skills like collaboration, adaptability, emotional intelligence, and judgment will be more valuable and in higher demand. For example, as the more mundane aspects of talent onboarding and management are handled by agents, HR leaders expect a productivity boost of 30% per employee. They also believe 23% will be shifted to entirely new positions that better leverage their human talents.
Gonçalo Borrega, VP of Product, AI and AppDev
Hybrid agentic systems will carve out a big space in enterprise application development and agentic systems
The next phase of AI will lean heavily on smarter orchestration and efficiency. A big bet for 2026 is that companies seeking higher margins while witnessing diminishing improvements in frontier models will increasingly favor hybrid agentic systems. These systems blend large language models (LLMs) with small language models (SLMs). Most organizations are unlikely to invest heavily in training or fine-tuning new models, as the integration of SLMs into these ecosystems will become their strongest asset.
Sufficiently powerful, inherently more suitable, and necessarily more economical for many agentic systems, SLMs are the evident future of effective agentic AI. In the years ahead, the hybrid orchestration of LLMs and SLMs is likely to define the practical architecture of intelligent enterprises.
The rise of hybrid agentic systems makes orchestration the new ROI battleground
As enterprises embrace both large and small models (LLMs and SLMs), the 2026 reality will be about "intelligent composition." This marks the rise of hybrid agentic systems, where AI models work like a specialized team. Think of them as "Lego bricks": a powerful LLM acts as the master-builder for complex reasoning, while dozens of specialized SLMs are the efficient, single-purpose bricks for specific tasks.
This hybrid approach creates a new technical challenge: orchestration. Orchestration is the critical process of managing this fleet — routing the right task to the right model, coordinating the complex workflow, and ensuring all the different "bricks" achieve a business goal in a reliable, cost-effective, secured and governed manner.
Miguel Baltazar, VP of Developer Relations
No-code development as we know it today will be gone
As AI continues to elevate development by suggesting architectures, optimizing integrations, and automating repetitive work, no-code as we know it isn’t necessary.
In fact, no-code platforms based on visual development and drag-and-drop interfaces are already on the decline. Some no-code vendors have already abandoned those aspects and are offering platforms that create applications from a simple functional description without using code layers. But what about low-code platforms? They’ll evolve in 2026, building orchestration, interfaces between humans and agents, and the RAG needed for agents to have accurate and current context to operate.
More than 75% of developers will be architecting, governing, and orchestrating instead of building applications
The developer role is going to be entirely different by the end of 2026. Many will transition into cognitive architects who orchestrate agents, a new role that will increase in value over the next 12 months. They'll break down complex business problems and design "blueprints of thought,” which detail how “AI thinking” should work. Others will become orchestrators, strategists, and collaborators. Their value will hinge on their abilities to solve, design, and inspire. Low-code developers, in particular, are well-positioned for this evolution.
Already operating at the intersection of technology and business, they can translate intent into workflows and logic without getting lost in the complexities of code. That proximity to business context and problem-solving gives them a natural advantage as AI systems evolve toward orchestration, composition, and reasoning. They will also be expected to focus on governance, from designing how multiple agents interact and integrate responsibly to ensuring their integrity, adherence to the highest ethical standards, and accuracy.
2026 will be the year AI ends developer burnout
A 2024 survey of over 600 engineers found that nearly 65% experience burnout, despite their organizations using AI in development. The reason is that despite freeing developers from repetitive, low-value work, the reliability of generative AI development tools is still uneven. Developer surveys report that software quality rates of about 60%. Addressing quality issues is an additional burden, as is integrating these tools effectively into existing workflows.
AI-powered low-code platforms bridge that gap by combining intelligent automation with built-in governance. As more enterprises turn to these platforms, their developers will feel empowered, engaged, and far less likely to burn out.
The agentic enterprise is taking shape
These predictions share a common thread. The agentic enterprise is taking shape now, and 2026 will separate organizations that experiment from those that operationalize. Want to go deeper? Join our upcoming webinar, “2026 AI Predictions: 3 shifts that will define the agentic enterprise.”
