Delivery capability

Process optimization through the targeted use of AI

Many companies are looking for ways to improve their processes in a targeted manner - using artificial intelligence (AI) as a lever for greater efficiency and cost optimization. But where to start? This is exactly where our support begins. With a structured approach from process analysis to prioritization and implementation, we help turn potential into concrete results. Our focus: using AI in processes in a way that quickly generates measurable benefits.

Process analysis creates the basis for the targeted use of AI

In the first step, we analyze the relevant business processes together: what processes exist, what goals do they pursue and what information flows in or out? This analysis creates a common understanding - and lays the foundation for deciding where process optimization through AI actually makes sense.

A prioritized backlog makes potential visible and tangible

An action backlog is created from the analysis: Requirements that can be solved with the help of AI are prioritized - according to impact, effort and feasibility. This creates a clear roadmap that shows where AI can have the greatest impact in terms of efficiency - with a clear focus on feasibility and impact.

Implementation is managed transparently - with the right approach

Implementation is iterative, adapted to the complexity and framework conditions. With suitable management models, we ensure clear responsibilities, transparent progress and flexible adjustment options. Where it makes sense, we work in iterative sprints - so AI in processes does not become a major project, but a targeted implementation process with fast feedback cycles.

The benefits of process optimization through AI are systematically made measurable

A key success factor in process optimization using AI is the ability to prove the effect - both quantitatively and qualitatively. Right at the start of the project, we define measurable targets together: for example, reduced throughput times, error rates, costs per process or processing volume per day. These KPIs make progress visible and create transparency for stakeholders. We also record qualitative effects - such as reducing the workload of teams or increasing customer satisfaction. In this way, AI not only makes efficiency tangible, but also verifiable.

A shared vision provides orientation and energy for change

Not every process is equally suitable for optimization using AI. The following are particularly relevant:

  • Document processing: e.g. automated extraction from forms or contracts.
  • Invoice verification and accounting: structured recording, checking and approval.
  • Customer support: e.g. through intelligent chatbots or email triage.
  • Logistics and planning: Forecasting demand, routes or stock levels.
  • Claims handling in the insurance industry: automatic checking and decision preparation for claims - with a high number of cases and recurring patterns, this is an ideal use case for AI.

    Our experience is that wherever processes are rule-based, data-driven and high-volume, process optimization through AI can create significant added value.
Next steps - start without obligation


Do you want to know what potential lies in your processes? In an initial workshop, we will analyze the initial situation together and identify specific areas for action. Get in touch now - we look forward to working with you.