Feature
Research Report
The State of the Digital Workplace
The evolution of low code/no code solutions such as Microsoft’s Power Platform, Kissflow and Pega over the last decade have led to the growth of citizen development initiatives to manage these solutions. These programs:
- Establish the governance, guardrails and processes required to check whether output from citizen developers causes any risk and sits comfortably with more traditional approaches to software development.
- Provide training and support resources for citizen developers, while also providing a community structure that encourages knowledge-sharing, learning and engagement.
With generative AI changing and extending the practice of coding, the concept of what citizen developers can do, the tools they use, what they need to know and the guardrails that need to be in place also changes. Here's how businesses are adapting.
The State of Citizen Development
Rather than replacing citizen development initiatives, generative AI appears to be shoring up formal support. Rework’s latest State of the Digital Workplace report found that 81% of organizations support citizen development, either with a formalized program with underlying governance (43%) or on an ad hoc basis with experimentation sanctioned through different departments (38%). Only 19% of businesses have no approach in place at all.
Other sources corroborate these numbers. Forrester’s 2025 Developer Survey reports that 89% of respondents are implementing or planning a strategy to support citizen developers. Similarly, a survey from Kissflow found 92% of tech leaders agreed that citizen development plays a “vital role” in supporting digital transformation.
The Value of Citizen Development Programs
Citizen development and accompanying programs are supported by tech leaders because they’re beneficial. By simultaneously managing risk, increasing adoption and training non-IT professionals, a citizen development program helps:
- Relieve the pressure on busy central software development teams, reducing the backlog of requests.
- Deliver solutions faster, which normally could take months, as well as quicker related updates, improving agility.
- Create opportunities for automation and innovation across the business which normally would not be carried out.
- Improve digital dexterity and related confidence across the workforce and encourage a spirit of innovation.
- Take advantage of the knowledge of domain experts who know local processes and working practices across lines of business, helping align output and business needs.
- Reduce development costs.
The Evolution of Citizen Development
Citizen development programs previously were scoped around low code/no code solutions that focus on workflows, automation and more defined outputs from a smaller groups of licensed users. Generative AI and the rise of “vibe coding” has extended the potential to create apps, workflows and automation beyond the communities of power users and more technically-savvy non-IT professionals who made up more traditional citizen development communities.
“AI tools are reshaping who gets to build solutions inside organizations, shifting creation from a small group of technical specialists to a much broader, more diverse set of contributors,” said citizen development specialist and AI strategist Michael McCullough. “The change isn’t just about efficiency, it’s about redistributing capability, authority and creativity across the workforce.” Employees now solve common workplace problems from the ground up without having to potentially rely on antiquated IT support processes, he said.
The Skills Citizen Developers Need Today
Generative AI’s redistribution of capability and authority and extension what employees can do requires new skills and approaches from previous citizen development strategies. Low code and no code solutions themselves are also evolving with generative AI’s capabilities, requiring a rethink on what citizen developers need to know.
“AI is widening who can build, but it’s also raising the bar,” said Kelly Goss, CEO and founder of Solvaa and a citizen development specialist. “It’s no longer just about creating a workflow; it’s more about framing the problem, using data responsibly and validating outputs.”
“Instead of manually assembling logic and connectors, citizen developers now guide systems that generate logic, interpret data and make decisions,” said McCullough. “This shift demands skills that go beyond traditional low‑code proficiency.”
Previously, citizen developers required process knowledge, comfort with visual builders and basic logic thinking, McCullough said. But today they require a deeper understanding of how AI behaves, how data flows and how to validate outputs that are not always the same.
“Prompting and tool knowledge are only part of it,” agreed Goss. “Citizen developers now need stronger judgment. They need to know when to use AI, how to validate outputs and how to handle data responsibly.”
New Approaches to Citizen Development Governance
While generative AI has changed the skills citizen developers need, it hasn't diminished the importance of governance. “AI has expanded what non‑technical builders can create, but it hasn’t eliminated the need for engineering discipline, statistical rigor or architectural oversight,” said McCullough. Organizations still need to draw boundaries between citizen developer work and professional developer or data science work by focusing on risk, complexity and impact.
But while generative AI has not changed the need for governance, its scope has.
“Traditional low‑code governance assumes humans write the logic, choose the connectors and follow defined review paths,” said McCullough. “AI breaks those assumptions by generating logic, chaining systems and acting with a degree of autonomy that low‑code programs were never built to oversee.” That means a governance gap organizations must close before growing AI-enabled citizen development.
“With traditional no-code/low-code, governance is mostly about access, security and control,” agreed Goss. “With AI, you’re also dealing with output quality, bias, hallucinations and whether people understand what they’re relying on.” This means citizen developer governance must change from purely technical oversight to also covering judgment, accountability and human review, she said.
Managing the Citizen Development Change
The change in focus in skills, governance and even culture that generative AI brings to citizen development may be a bumpy ride for existing programs that may have been running successfully for years.
“The biggest friction points show up where AI’s speed, autonomy and ambiguity collide with the guardrails, culture and expectations of a traditional citizen‑development program,” said McCullough, describing this tension as “organizational” rather than “technical.” This friction is growing fast as AI agents build, connect and modify things without the predictable boundaries low‑code teams are used to.
To avoid this friction, an evolving citizen development program must include change management. For example, when McCullough was implementing Amtrak’s low-code development program, the biggest challenge proved to be demystifying AI and educating the workforce on what AI could be used for, rather than structural or technical aspects.
Problems also emerge when citizen development programs fail to evolve, particularly considering how fast AI produces output. “The biggest issue is when AI gets added in, but nothing else changes,” said Goss. “Most citizen development programs were built around structured automation, whereas AI introduces ambiguity, risk and much faster iteration cycles.”
Design and engineering consultancy Arcadis evolved a citizen development program to take on generative AI. The program, which incorporates Microsoft Power Platform, was already advanced with a large, active Power Platform community, a self-serve citizen development “hub” that assesses needs and provides tailored solutions and an appointed Global Citizen Development Director in Freek Mattheij.
The program has now evolved to incorporate AI agents and Copilot Studio. Mattheij's title evolved as well. He is now Global Citizen Development & AI Director, with a mandate to train a 2,000-member citizen development community with AI capabilities.
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Avoiding Parallel Programs
Not all programs are as united as Arcadis's. Citizen development programs and some AI adoption initiatives may run in parallel, but overlap, managed by different teams each with a potentially different focus.
“When a citizen‑developer program and an AI initiative run in parallel, the biggest risk is that they evolve as two separate transformations, one focused on democratizing creation, the other on scaling intelligence without ever converging into a coherent operating model,” said McCullough. Organizations that succeed treat them as one capability with two entry points, he added
“Bring them together early,” agreed Goss. “If they evolve separately, you end up with conflicting standards, duplicated effort and very different attitudes to risk. A single framework with shared governance, language and priorities creates much more consistency and momentum.”
Citizen development is evolving to adopt generative AI, as low code/no code solutions also incorporate AI. Organizations that build on the early success of citizen development programs by evolving skills, governance and scope, driven by a unified rather than fragmented strategy, will help reduce risk and improve future success.
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