Consulting for AI-supported Software Engineering

The challenge

Against the backdrop of the growing importance of artificial intelligence, the company had already gained some initial experience with AI-supported development approaches. The key challenge, however, was to integrate the potential of AI into the entire software development process not just on an ad hoc basis, but systematically, across all sites and with measurable added value.

As part of the analysis of the existing development process, various opportunities were identified for the targeted use of modern AI technologies to enhance the efficiency, quality and scalability of software development. Particular attention was paid to optimising key process steps throughout the entire development cycle, from requirements gathering through quality assurance and compliance to collaborative software development.

The aim was to systematically examine existing development workflows for opportunities to utilise AI support and to create a robust foundation for the productive and measurable use of artificial intelligence in day-to-day development work.

How we helped

XITASO supported Grenzebach in developing a strategic roadmap for the use of artificial intelligence in software development. The starting point was a structured analysis of the existing development processes, the technical framework and the current level of AI maturity.

On this basis, XITASO worked with the relevant stakeholders to identify specific potential applications throughout the entire software development cycle. The various use cases were assessed and prioritised in terms of their business value, technical feasibility and expected benefits.

For the prioritised areas of action, XITASO subsequently developed concrete solution approaches, including a target vision, technical classification, effort estimation and success criteria. The result was a robust roadmap with clearly prioritised pilot initiatives and measurable objectives for the phased introduction of AI-supported development processes.

Result

• Transparent assessment of AI potential throughout the entire software development process
• A prioritised roadmap with concrete pilot initiatives that can be implemented in the short term
• A sound basis for decision-making regarding the future AI strategy and investment planning
• Empowerment of the development organisation to make systematic and sustainable use of AI tools

In doing so, Grenzebach laid the foundations for integrating artificial intelligence into software development in a targeted and scalable manner and for making its benefits measurable using clearly defined key performance indicators.

Technologies & Methods