As we look ahead to 2025, the digital transformation landscape continues to evolve, and two powerful forces are poised to redefine how organizations approach automation: Generative AI (GenAI) and the rise of citizen developers. Forrester’s latest predictions reveal that these trends will not only drive new opportunities but also bring challenges as businesses work to leverage these innovations effectively.
Citizen developers, empowered by no-code/low-code platforms, will take on an increasingly important role, creating GenAI-infused applications that streamline automation across industries. This partnership between human creativity and AI-driven technology offers a glimpse into the future of work, but it also demands careful consideration of how these tools are implemented.
GenAI and citizen developers
In this blog, we explore how GenAI and citizen developers will shape automation in 2025, the potential hurdles, and the key steps businesses must take to prepare for this transformation.
1. The Rise of GenAI in Automation
Automation has been a driving force in digital transformation for years, and as technology continues to advance, it is no longer limited to predefined tasks. Generative AI is set to push the boundaries of what’s possible by combining cognitive and physical automation. By 2025, one-quarter of robotics projects will integrate GenAI to enable robots and machines to learn, adapt, and respond to complex environments in real-time.
This shift marks a departure from the traditional approach, where robots followed preprogrammed rules and workflows. Instead, GenAI will allow robots to sense their surroundings, interpret data, and make decisions autonomously. Industries such as manufacturing, logistics, and even healthcare are expected to see significant benefits, as robots take on more nuanced tasks beyond high-volume, low-variance activities like assembly line work.
In addition, edge intelligence—a concept where data processing happens closer to where it is generated, such as within a machine or device—will further enhance automation by reducing latency and improving decision-making capabilities. This combination of GenAI and edge intelligence will be crucial for applications like autonomous vehicles, smart factories, and advanced robotics.
However, it’s important to note that the integration of GenAI into physical and cognitive automation is still in its early stages. While the technology offers exciting possibilities, it also brings challenges, including technical complexities and ethical considerations surrounding autonomous decision-making. For businesses, the key to success will be in identifying where GenAI can add value while ensuring that human oversight remains a priority.
2. Citizen Developers at the Forefront of Automation
One of the most exciting developments for 2025 is the role of citizen developers in driving GenAI-infused automation. Citizen developers—employees outside of traditional IT roles—have been gaining traction for several years, thanks to the rise of no-code and low-code platforms that make app development accessible to non-technical users. In 2025, these individuals will be responsible for delivering 30% of GenAI-driven automation applications, according to Forrester’s predictions.
What makes citizen developers so effective in this space? It’s their unique combination of domain expertise and creativity. Because they understand the specific needs and challenges of their industries or departments, they are well-positioned to imagine practical GenAI solutions. Additionally, they are increasingly adept at working with large language models (LLMs) like ChatGPT, using natural language prompts to generate code, automate processes, and build applications that address real-world problems.
This shift democratizes the development process, allowing businesses to scale GenAI experimentation and innovation without relying solely on IT departments. For example, a marketing team could use a low-code platform to build an AI-driven customer engagement app, or an HR department could develop a GenAI-powered tool to streamline employee onboarding.
Low-code and no-code platforms serve as the bridge between GenAI’s potential and practical implementation. These platforms allow citizen developers to integrate AI capabilities into their applications without needing to write complex code. This not only accelerates the development process but also ensures that AI-driven innovation is aligned with business needs.
However, with this growing reliance on citizen developers comes the need for robust governance frameworks. Businesses must establish clear guidelines to ensure that the apps created by citizen developers meet security, compliance, and data privacy standards. Empowering non-technical users to build GenAI-infused apps is a powerful strategy, but it must be done within a controlled environment to avoid potential risks.
3. Overcoming the Challenges of GenAI Implementation
While the potential of GenAI is vast, implementing it effectively is not without its challenges. One of the primary obstacles businesses will face in 2025 is the complexity of integrating GenAI into existing workflows and processes. Unlike traditional automation, which operates on well-defined rules and predictable outcomes, GenAI introduces new variables that can be difficult to manage.
For instance, many organizations will struggle with vague business objectives when implementing AI agents. Without a clear understanding of what the technology is expected to achieve, projects can quickly become mired in confusion and inefficiency. Additionally, determining the appropriate level of autonomy for AI systems is a delicate balance. Too much autonomy can introduce risks, while too little can limit the technology’s effectiveness.
Another challenge lies in the fragmented vendor landscape. As AI continues to gain traction, many vendors will rebrand their existing products to align with AI trends, often without adding meaningful new capabilities. This can make it difficult for decision-makers to select the right GenAI platform for their needs. Businesses must be discerning, looking beyond marketing buzzwords to identify solutions that truly offer value.
Additionally, data integration remains a critical hurdle. AI agents require access to vast amounts of enterprise and customer data to function effectively, but in many organizations, this data is siloed or inaccessible. Ensuring that AI systems have the necessary data—and that the data is accurate and up-to-date—will be essential for successful implementation.
4. GenAI’s Role in Business Processes: A Supporting Player
Despite the excitement surrounding GenAI, it’s important to recognize that it will not yet take over core business processes by 2025. According to Forrester, GenAI will orchestrate less than 1% of core business processes in the near term. While it will reduce the time needed for process design and development, deterministic automation platforms, such as robotic process automation (RPA), will continue to handle the bulk of long-running, rule-based tasks.
In this context, GenAI’s primary role will be to augment existing systems by providing insights and efficiencies in specific areas. For example, GenAI can help streamline certain workflows by generating forms or visualizing data, but it will not replace the core automation platforms that businesses rely on for mission-critical operations.
This means that businesses need to manage their expectations when it comes to GenAI. While it will undoubtedly play a role in improving efficiency and decision-making, it will not be the silver bullet for all automation challenges. Instead, organizations should focus on integrating GenAI in areas where it can deliver targeted improvements, while continuing to rely on established automation tools for the heavy lifting.
5. GenAI’s Success in Employee Support
One area where GenAI is expected to make a significant impact is in employee support applications. In 2025, over half of successful GenAI projects will be focused on improving internal processes and enhancing employee productivity. This is particularly true in industries such as finance and healthcare, where operational efficiency is critical.
AI agents will help automate routine tasks, such as data entry and reporting, freeing up employees to focus on higher-value activities. They will also assist in decision-making by analyzing large volumes of data and providing real-time insights. However, for these projects to succeed, businesses must invest in change management and ensure that employees are comfortable working with AI-powered tools.
Moreover, integrating AI agents with enterprise systems and ensuring access to the right data will be crucial for success. Organizations will need to break down data silos and create seamless connections between AI agents and the systems they need to interact with.
Conclusion
As we move towards 2025, the combination of Generative AI and citizen developers will play a transformative role in shaping the future of automation. By empowering non-technical users to build GenAI-infused applications, businesses can scale innovation and improve efficiency across a wide range of processes. However, realizing the full potential of these technologies will require careful planning, strong governance, and a focus on overcoming the challenges associated with implementation.
For organizations willing to invest in the right strategies, 2025 promises to be a year of unprecedented opportunities in automation. By embracing GenAI and fostering a culture of citizen development, businesses can position themselves at the forefront of this technological revolution.