Industry Experts Discuss Low-Code, AI Integration at CIO.com Virtual Roundtable
By Lane F. Cooper, Editorial Director of BizTechReports and CIO.com Moderator
During a recent CIO.com virtual roundtable co-hosted with Tiago Azevedo, Chief Information Officer of OutSystems, technology leaders representing a broad swath of vertical industries -- from financial services and technology, to manufacturing and professional services -- gathered to explore how the integration of low-code and no-code platforms with AI governance may affect enterprise transformation strategies. The event highlighted the potential of Low-Code No-Code platforms to accelerate application development while ensuring governance and transparency. Below are key notes and observations captured in accordance with the Chatham House Rule convention that enabled candid and free-flowing discussion.
Tiago Azevedo, Chief Information Officer of OutSystems
Participants emphasized the importance of adopting a “think big, start small, scale fast” methodology. By starting with iterative pilots or MVPs, companies can learn and adapt before scaling their efforts to tackle complex, mission-critical applications. The importance of embracing decentralized data architectures for organizing data as domain-specific products — data meshes or digital fabrics — also emerged as a critical success factor for enabling seamless integration and scalability across diverse systems through standardized, interoperable protocols.
“By starting small, leveraging data fabrics, and prioritizing transparency, organizations can responsibly scale their efforts,” said Azevedo. This measured approach helps enterprises build a foundation for success while mitigating risks associated with rapid development tools and AI integration.
As the discussion turned to operational challenges, effective governance and control emerged as key priorities. Panelists stressed the need for proper testing, accountability, and adherence to best practices when using low-code, no-code, and generative AI tools. Transparency and auditability were identified as crucial to avoid “black box” solutions and maintain enterprise governance.
Tiago Azevedo highlighted importance of generating applications in an open by using, as an example, standard .NET code. “Many low-code tools operate in a ‘black box’ environment. This can create problems down the line. It is essential to allow for thorough inspection and extension of all output as needed,” he explained.
Shifting the focus to financial considerations, panelists explored how low-code and AI technologies can drive cost efficiencies in enterprise software development. Generative AI, for instance, offers the potential to accelerate development timelines, reducing time-to-market and associated costs. However, participants cautioned against large-scale implementations without proper planning.
“Starting with small, iterative pilots helps minimize financial risk while enabling continuous improvement,” said Azevedo. This strategy allows organizations to maximize return on investment by scaling successful initiatives incrementally.
The conversation then delved into technological advancements, particularly the integration of low-code platforms with existing enterprise systems and data sources. Panelists discussed the importance of establishing cohesive data fabrics or meshes to unify diverse data sources without relying on a single “golden record” of data.
“A data fabric or mesh enhances flexibility and consistency, allowing seamless integration with legacy systems through APIs,” Azevedo noted.
Low-code/no-code platforms enable a data fabric or mesh by providing tools to create APIs and connectors that integrate disparate data sources and legacy systems into a unified architecture, while embedding AI agents and generative AI capabilities within applications to enhance functionality and automate processes without requiring major overhauls to existing workflows. That is how, explained Acevdeo, OutSystems embeds AI agents directly into applications to offer generative AI capabilities that enhance functionality without disrupting existing workflows.
Generative AI’s role in accelerating software development was also a focal point, with participants emphasizing the need to integrate these tools into existing software development lifecycles. Proper governance ensures the reliability and accuracy of AI-generated code and content.
The roundtable underscored the transformative potential of low-code, no-code, and generative AI technologies when adopted strategically. By addressing strategic, operational, financial, and technological considerations, organizations can harness these tools to drive innovation and agility in enterprise systems.
“The insights shared at this event provide a roadmap for companies navigating the evolving landscape of AI and low-code development,” Azevedo concluded.