Low-code and no-code are no longer “a faster way to build dashboards.” They are becoming the operating layer for how organisations ship internal software, automate operations, and safely embed AI into workflows.
The next 5 years (2026–2030) are where the category continues to improve on its serious, governed software delivery.
Let’s anchor this in numbers.
1) The market is big, growing fast, and still fragmented
Different analysts measure different slices (pure low-code platforms vs low-code + digital process automation). That’s why ranges look wide.
Forrester frames the market more broadly, bundling low-code platforms with digital process automation (DPA). In that lens, it estimates the market was $13.2B by the end of 2023, with a base-case path to roughly $30B by 2028. Forrester also outlines an AI-fuelled upside scenario where the same combined market could reach around $50B by 2028.
Grand View Research narrows the definition to the low-code application development platform market specifically. Under that scope, it sizes the market at $6.78B in 2022 and forecasts growth to $35.22B by 2030, implying a 22.9% CAGR from 2023 to 2030.
Two takeaways for 2026–2030 planning:
- Even the conservative paths show sustained growth through 2028 and beyond.
- The category is converging with automation and AI, which is why “platform” matters more than “builder.”
2) What Will Actually Drive Adoption In Future
Driver A: AI becomes the default interface for building, but governance becomes the default requirement
Gartner’s forecast is blunt: by 2028, 75% of enterprise software engineers will use AI code assistants, up from <10% in early 2023 (and 63% of organisations were already piloting/deploying by Q3 2023).
That matters for low-code because it changes expectations:
- Stakeholders will ask, “Why can’t the platform generate the first draft?”
- Security teams will ask, “Where are the controls, audit trails, and approvals?”
Gartner is also blunt about the downside of ungoverned AI: over 40% of agentic AI projects will be cancelled by end of 2027 due to cost, unclear value, or inadequate risk controls.
Reuters coverage notes Gartner expects agentic AI to be in 33% of enterprise software by 2028 and to autonomously handle 15% of daily business decisions by 2028.
So the 2026–2030 era is not “AI everywhere.” It’s “AI in limited doses, with adult supervision.”
Driver B: Internal tools are where time (and money) quietly disappears
Internal software rarely fails loudly. It fails like a slow puncture: meeting-by-meeting, approval-by-approval, tool-by-tool. And newer research is finally putting numbers on that drag.
- Developers don’t spend most of their week coding. Atlassian’s State of Developer Experience Report 2025 (survey with Wakefield Research; 3,500 developers and managers) highlights that developers spend around 16% of their time coding, meaning the bottleneck is the other 84% of the week: discovery, coordination, access, approvals, compliance steps, and operational grind.
- Time lost is measurable and large. The same Atlassian research reports 50% of developers lose 10+ hours per week to non-coding work, and 90% lose 6+ hours or more, largely due to organizational inefficiencies (poor information access, fragmented tools, context switching).
- Independent time-allocation research shows a similar shape. A Microsoft Research study on developers’ “actual vs. ideal” weeks found that, in the actual week, developers spent ≈12% on communication & meetings, ≈11% on coding, ≈9% on debugging, etc., while their “ideal” week shifts significantly more time toward building (e.g., ≈20% coding). It’s a quantitative view of the same problem: engineers want to build, but the system taxes them first.
That’s the economic engine behind low-code and no-code: not “developers can’t code,” but organizations can’t afford to waste senior engineering time on internal glue work.
Between 2026 and 2030, the winners won’t just accelerate UI assembly. They’ll compress the non-coding 84% without creating governance debt: secure connectivity, auditability, approvals, role-based access, and safe reuse across teams.
Driver C: The definition of “enterprise low-code” is shifting under your feet
Gartner’s description of enterprise low-code application platforms (LCAPs) highlights that they now include:
- Full application lifecycle support across the stack (not just UI)
- Security/governance capabilities
- Increasingly AI-assisted development features
This is why “drag-and-drop” becomes table stakes. The differentiator becomes: can you build safely, integrate everywhere, ship repeatedly, and survive audits?
3) What Low-Code/No-Code Will Look Like Between 2026–2030 (Practical Forecast)
“Guardrails-first” becomes the buying criteria
- AI pilots get cut aggressively if they do not show measurable value or risk controls.
- Low-code platforms that behave like real software delivery systems (versioning, environments, approvals, auditability) get budget.
- Platforms that feel like “prototype toys” get squeezed.
Procurement questions you will hear more:
- Can we enforce RBAC and least privilege?
- Can we audit who changed what and which data was accessed?
- Can we keep data inside our VPC / self-hosted environment where needed?
- Can we integrate with our identity layer and SDLC?
AI-assisted building is expected, but “agent washing” gets punished
- AI code assistants become mainstream in engineering orgs.
- Agentic features show up inside enterprise software, but many projects fail if they are not grounded in workflow orchestration and controls.
Platforms that combine:
- workflow orchestration (clear steps, approvals, fallbacks), and
- AI augmentation (drafting, summarising, routing, extracting), will outperform “autonomous magic” platforms.
Platforms consolidate, and the winner is the one that “ships boringly well”
- By 2030, market projections still show strong growth in low-code platforms as a category.
- But the story shifts from “anyone can build” to “everyone can deliver safely.”
- This is where enterprise platforms with repeatable governance win the long game.
4) Why Retool, ToolJet and Appian Map Cleanly to This Future
Retool: “Internal tools tax reduction” with measurable developer-time framing
Retool’s research repeatedly quantifies the internal tooling burden (30% to 45% developer time, depending on company size). In a world where enterprises are trying to do more with smaller teams, that framing gets sharper, not weaker.
Why this matters:
- Internal tool demand does not go away; it grows as operations become more software-driven.
- The winners are the platforms that let teams build fast while staying governable.
ToolJet: “Control + Cost” for teams that want developer ergonomics along with business-user involvement
ToolJet positions itself as an open-source low-code platform focused on speed without sacrificing cost or control. The platform matches Retool feature by feature with a slight edge on AI capabilities.
ToolJet is trusted by companies like Orange, Swisscom, Toss, EDG, etc. These are enterprises that operate at scale and face demanding internal tooling requirements.
Why this matters:
- When AI + governance concerns rise, “control” becomes a first-class requirement, not a preference.
- Open-source and deployment flexibility can be a decisive advantage for regulated environments.
- AI is shaping the future, and ToolJet leads the way with a first-mover advantage in enterprise-grade AI integration.
Appian: “Process automation at enterprise depth” when workflows need to survive audits
Appian plays in the heavier end of the spectrum: process automation, orchestration, and enterprise governance.
Why this matters:
- As agentic AI gets embedded into business processes, controlled orchestration becomes the real differentiator (not just UI speed).
- Regulated industries tend to standardise on platforms that look and behave like enterprise systems, especially under audit pressure.
5) The Unsexy Checklist That Will Decide Winners in the Next 5 Years
Governance
RBAC, audit logs, approvals, environment separation, change history, and predictable release processes.
AI that is safe-by-design
Given Gartner’s forecast that 40%+ agentic AI projects get cancelled by end 2027, AI features need measurable value and risk controls.
Integration reality
Databases + internal APIs matter more than “lots of SaaS connectors.” Retool’s internal tools research repeatedly shows how internal data sources dominate internal tooling.
Developer experience, not just citizen dev
Because by 2028, the majority of enterprise engineers are expected to use AI assistants, platforms must support engineers who want speed and control.
Cost and deployment flexibility
As the market grows (and budgets get scrutinised), platforms that offer better control over deployment and long-term cost tend to win standardisation debates. This is where open-source options like ToolJet are naturally well-positioned.
Closing: The 2026–2030 Bet
The next wave of low-code is not about replacing engineers. It’s about making every workflow shipable with:
- AI assistance where it’s cheap and safe
- orchestration where risk lives
- governance everywhere
My bets are on:
- Retool for organisations trying to claw back the 30%–45% internal tools time sink with a platform built around internal software velocity.
- ToolJet for teams that want control, flexibility, enterprise-grade maturity, AI capabilities, and open-source leverage.
- Appian for enterprises where process, governance, and auditability are the product.
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