Enterprises face growing pressure to deliver digital capabilities faster while operating under persistent constraints related to skills, security, cost, and governance. Traditional application development approaches—characterized by long cycles and limited developer capacity—are no longer sufficient. As a result, organizations are rethinking who builds software, how it is built, and the platforms required to support safe, scalable delivery across the enterprise.
Low-code and no-code (LCNC) solutions are increasingly central to modern development strategies, enabling business users—often referred to as citizen developers—to create applications that directly address workflow and productivity challenges. When combined with professional development and platform engineering practices, LCNC tools help organizations accelerate time-to-market while maintaining architectural integrity, security, and governance. AI-powered development further enhances this model by enabling intent-based development through natural language interfaces and intelligent automation.
In this market brief, Enabling Enterprise Agility with Low-Code/No-Code, AI, and Platforms developed in collaboration with IBM, Futurum Research examines how enterprises can enable agility at scale by combining LCNC, AI-powered development, and platform-centric architectures. The report outlines IBM’s approach to enterprise-grade agility, highlighting the importance of hybrid cloud, built-in governance, platform engineering, and integrated automation to ensure that speed of innovation translates into production-ready, secure, and resilient outcomes. Download the report to learn how organizations can balance development velocity with operational control.
In this brief, you will learn:
Low-code and no-code (LCNC) solutions are increasingly central to modern development strategies, enabling business users—often referred to as citizen developers—to create applications that directly address workflow and productivity challenges. When combined with professional development and platform engineering practices, LCNC tools help organizations accelerate time-to-market while maintaining architectural integrity, security, and governance. AI-powered development further enhances this model by enabling intent-based development through natural language interfaces and intelligent automation.
In this market brief, Enabling Enterprise Agility with Low-Code/No-Code, AI, and Platforms developed in collaboration with IBM, Futurum Research examines how enterprises can enable agility at scale by combining LCNC, AI-powered development, and platform-centric architectures. The report outlines IBM’s approach to enterprise-grade agility, highlighting the importance of hybrid cloud, built-in governance, platform engineering, and integrated automation to ensure that speed of innovation translates into production-ready, secure, and resilient outcomes. Download the report to learn how organizations can balance development velocity with operational control.
In this brief, you will learn:
- Why LCNC and professional development are increasingly complementary—not competing—approaches
- How citizen developers and AI-powered tools are reshaping enterprise software creation
- The role of platform engineering in ensuring security, governance, and production readiness
- Why hybrid cloud and infrastructure-as-code are foundational to scalable LCNC strategies
- How IBM’s platform-driven approach helps enterprises move faster without sacrificing control
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Author Information
Mitch Ashley is VP and Practice Lead for the CIO & Technology Buyers and Software Lifecycle Engineering practices at The Futurum Group. A multi-time CIO and CTO with 30+ years leading technical organizations, Mitch built and operated production systems spanning cybersecurity for the U.S. Department of Defense, PKI services for the broadband and 5G industries, SaaS platforms, large-scale telecom and banking systems, and a national broadband network. His work with AI began early, developing expert systems that diagnosed and repaired complex mainframe environments. That operator foundation grounds his analysis in operational consequence, covering the technology buyer's world of software engineering, cybersecurity, DevOps, cloud, and AI.
