NEW RESEARCH ALERT: TRANSFORM FAILING AI STRATEGIES WITH HOST HOW HUMANS, OBJECTIVES, STRATEGY, AND TECHNOLOGY DRIVE MEASURABLE RESULTS Julie Ask Advisory and Analysis.Tech collaborated on this critical new research. This week's Low Down on Low-Code provides an introduction. The conversation focuses on the importance of integrating human factors into AI strategy development. It emphasizes that technology decisions should come after understanding the capabilities and readiness of the people who will use it. The discussion highlights the need for clear business objectives and evaluating use cases to ensure that AI is the right fit for organizational goals. Takeaways -Senior executives are pushing for AI strategies. -Technology decisions should prioritize human readiness. -Critical thinking skills are essential for AI use. -Understanding user comfort with technology is crucial. -Business objectives must guide AI implementation. -Evaluating use cases is key to effective AI strategy. -Training and iteration are necessary before AI deployment. -Human beings should be at the center of AI strategy. -AI should support clear business objectives. -The right technology must align with user capabilities.

In this episode of Lowdown on Low Code, host John Rymer and data expert Rick Greenwald delve into the complexities of data governance within the low code movement. They discuss the challenges posed by distributed data, the elusive quest for a single source of truth, and the importance of understanding data correctness in context. The conversation emphasizes the need for effective governance strategies that align with the realities of distributed data systems and the role of developers in maintaining data integrity. Takeaways -Rick Greenwald has over 40 years of experience in data. -Distributed data refers to data from multiple sources, not just geographical distribution. -The desire for a single uniform data pool is common but challenging to achieve. -Correctness of data is context-dependent and varies by use case. -Governance is essential but often overlooked in data management. -Developers play a role in data governance through their interactions with end users. -Many systems operate in silos, reducing the need for unified governance. -AI agents require access to diverse data but complicate governance. -Organizations must recognize that all data is governed, whether they acknowledge it or not. -Having too many versions of data is a sign of multiple use cases, not poor management.

In this episode, Rob Koplowitz and John Rymer engage with Alex Landis, a founding member of the FinOps Foundation, to explore the evolving landscape of FinOps and its integration with emerging technologies. The conversation delves into the definition of FinOps, its significance across various industries, the challenges of data management, and the impact of AI on financial operations. Alex shares insights on governance, best practices, and the future of FinOps, emphasizing the importance of making informed investments and leveraging technology for better communication and efficiency. Takeaways -FinOps is essential for managing cloud costs effectively. -Understanding platform operations is crucial for financial performance. -AI presents both opportunities and challenges for FinOps professionals. -Data management in FinOps is complex and requires sophisticated tools. -Governance in AI usage is critical to avoid unnecessary spending. -The role of FinOps is growing as companies invest more in technology. -Effective communication between finance and engineering is vital. -Automation can significantly improve forecasting processes. -Empowering teams to self-serve with data tools enhances efficiency. -The FinOps Foundation is a valuable resource for best practices.

In this episode of Lowdown on Lowcode, hosts Rob Koplowitz and Dave Marcus engage with Marshall Sied from Ashling Partners to explore the evolving landscape of low code, digital process automation, and AI. They discuss the importance of education, governance, and orchestration in automation projects, as well as the challenges and opportunities presented by new technologies. Marshall shares insights from his extensive experience in the consulting space, emphasizing the need for organizations to focus on value realization and continuous deployment methodologies. The conversation also touches on the significance of experimentation and the future of applications in a rapidly changing technological environment. Takeaways -Marshall Sied emphasizes the importance of education in automation. -Organizations are increasingly conflicted about AI and automation. -Value realization is crucial for successful automation projects. -Continuous deployment methodologies are essential for achieving value. -Governance is critical in managing automation technologies. -Experimentation is encouraged in the current automation landscape. -Orchestration is becoming a key focus for automation companies. -Capability mapping should precede tool mapping in technology selection. -Organizations need to be cautious with low-code and AI technologies. -The future of applications will involve more productization and composability.

In this episode of Low Down on Low-Code, hosts Rob Koplowitz and John Rymer engage with Kari Moeller to explore the intersection of process optimization and AI. They discuss the importance of documentation and modeling in managing changes brought by AI, the need to reimagine business processes, and the role of technology in achieving desired outcomes. Kari shares her insights on consulting, the challenges of data management, and how organizations can leverage AI as a digital assistant to enhance their operations. The conversation emphasizes the critical need for organizations to understand their technology landscape and align their strategies with clear outcomes. Takeaways -The intersection of process and technology is crucial for optimization. -Documentation and modeling are essential for managing AI changes. -AI should be viewed as a digital assistant, not a replacement for human roles. -Organizations must start with outcomes to drive effective change. -Understanding the technology landscape is vital for successful implementation. -Data quality is more important than quantity in decision-making. -Reimagining processes can lead to significant improvements in efficiency. -AI can amplify both good and bad processes, necessitating careful management. -Consulting practices should focus on empowering business users with data. -Future customers will be those who experience the processes firsthand.

In this episode of Lowdown on Low-Code, Rob Koplowitz and John Rymer engage with Nick Cawthon from Gauge to explore the evolving landscape of design and application development. They discuss Nick's journey into design, the current flux in the industry, the impact of AI on user experience, and the importance of understanding user needs in 2025. The conversation emphasizes the human element in design and the necessity for collaboration between designers and developers, highlighting tools like Figma that facilitate this relationship. Takeaways -Nick Cawthon's journey into design began with a childhood experience of flow state. -The design industry is currently experiencing significant changes and flux. -AI is reshaping user experience, making it more about emotions than interfaces. -Designers must focus on qualitative research to understand user emotions. -Efficiency in design must not compromise the effectiveness of user experience. -Understanding user experience in 2025 requires a holistic approach. -The relationship between designers and developers is evolving positively. -Tools like Figma are crucial for collaboration in design and development. -Mitigating risks in design is essential to avoid dead-on-arrival products. -The human element in design remains irreplaceable despite technological advancements.

In this episode of Lowdown on Low Code, hosts Dave Marcus and John Rymer engage with Massimo Pezzini, a veteran in the field of integration and orchestration. They discuss the evolution of orchestration as a foundational need for modern business applications, the challenges of data synchronization, and the convergence of integration and orchestration technologies. The conversation also touches on the importance of governance in distributed systems and the growing role of AI in enhancing business processes. Massimo shares insights on how organizations can effectively navigate these challenges and leverage technology for better outcomes. Takeaways: -Orchestration is broader than just workflow; it automates end-to-end business processes. -Integration and orchestration are increasingly becoming integrated disciplines. -Governance is essential for effective orchestration and cannot be an afterthought. -AI can significantly enhance business processes when integrated effectively. -Organizations should have a unified integration team to address various integration challenges. -Mid-size organizations tend to favor integrated platforms due to skill limitations. -The complexity of integration challenges varies, requiring different technological solutions. -Trust in AI is growing as organizations find well-defined use cases for its application. -Data integration and application integration are complementary and should be considered together. -The trend is towards platforms that offer a comprehensive suite of services for application development.