The Future of Software Delivery Starts with Process
20 July 2026
The promise and the reality
The idea that anyone can describe an application in plain English and instantly generate production-ready software has become one of the dominant narratives surrounding AI.
It’s an appealing vision. Explain what you want, press a button and watch an application appear.
The reality is more complicated.
Natural language is inherently ambiguous. Software is not. Applications require defined processes, data structures, permissions, integrations, governance and compliance controls. Translating intent into working software still requires a level of structure between the idea and the application itself.
This is where application generation (AppGen) is beginning to reshape software delivery.
Rather than replacing the software development lifecycle (SDLC), AppGen is compressing parts of it – reducing the effort required to move from understanding a business problem to delivering a working solution.
Why software delivery has always struggled with translation
Most delivery challenges occur long before a developer writes a line of code.
Requirements are gathered. Workshops are held. Documentation is created. Handoffs occur between business teams, analysts, architects and developers. At every stage, information is interpreted, translated and refined.
The challenge is that organisations are often attempting to build solutions from descriptions of work rather than from an accurate understanding of how work actually happens. When that understanding is incomplete, applications risk reflecting assumptions rather than operational reality.
Process is becoming the new starting point
As AI capabilities mature, organisations are increasingly using them to understand and model business processes before development begins.
Instead of starting with requirements documents, teams can begin with a shared view of the process itself – identifying activities, decisions, responsibilities and exceptions before moving into application design. The process becomes the source of truth that connects business intent with technical delivery.
Tools like Liberty Spark make this practical – ingesting existing documentation, SOPs and diagrams to generate a clear, editable process map that teams can validate before a line of application logic is written.
From process understanding to application generation
The real opportunity is not generating code directly from a prompt. It is generating applications from validated process models.
Once a process has been understood and agreed, AI can help translate that understanding into application structures, workflows, data models and user experiences far more quickly than traditional approaches. This is where process intelligence and application generation connect in practice – Liberty Spark mapping and validating the process, Liberty Create scaffolding it into a working application.
Activities that previously required weeks of analysis, specification and configuration can be completed in hours, while still maintaining governance and oversight. The focus shifts from manually constructing every component to reviewing, refining and validating generated outputs.
Democratising delivery without removing expertise
AppGen does not eliminate the need for developers, architects or process specialists. It changes where expertise is applied.
Business teams can contribute more directly to solution design because the process is easier to visualise and validate. Technology teams spend less time building common application foundations and more time focusing on integration, security, architecture and user experience.
Crucially, the process remains the source of truth throughout. When policies or workflows change, the application can be updated from the same foundation – keeping documentation and implementation in sync. This addresses one of the most persistent failure points in traditional delivery.
Why platform consolidation matters
Years of departmental purchases and tactical projects have left many organisations supporting hundreds of disconnected applications and workflows. AppGen is most effective when it operates within a governed platform environment where security, integration, data management and compliance are already established, allowing organisations to accelerate delivery without increasing operational complexity.
AI is accelerating delivery, not replacing governance
The discussion around AI in software development often focuses on speed. Speed matters, but it is not the primary challenge facing most organisations.
The greater challenge is ensuring that applications remain aligned with business processes, policies and regulatory requirements as they evolve. Assistants that operate inside a governed platform – respecting data boundaries and working within established controls – behave very differently from ungoverned tools connected to a codebase. The former accelerates delivery safely. The latter introduces risk that often only becomes visible later.
The most successful approaches combine AI acceleration with strong governance rather than treating them as opposing priorities.
The future starts with understanding the process
The SDLC is not disappearing. It is becoming shorter, more collaborative and increasingly driven by operational insight rather than documentation.
AppGen is now recognised as a distinct software category, with Netcall included among 40 notable vendors in Forrester Research’s newly published report, “The AppGen And Low-Code Platforms Landscape, Q2 2026,” which sets out a broad view of the application generation (AppGen) and low-code platforms market.
The organisations best placed to benefit will be those that have already connected process understanding to application delivery.
About the author
Richard Farrell
Chief Innovation Officer
Richard began his career in contact centres in the mid-1990s, building his expertise in customer contact management. Today, Richard is Netcall’s long-serving Chief Innovation Officer, having been with the company for an impressive 23+ years and serving as the company’s CTO for several years prior. He currently focuses on researching, innovating and delivering solutions that meet the needs and challenges that Netcall’s clients face.