AFGVF AI Coding Boosts Productivity 30% to 50%

On August 26, 2026, AFGVF disclosed on an earnings call that healthcare software developers were using AI in coding activities, increasing productivity on the relevant tasks by 30% to 50%. The company did not disclose the measurement baseline, developer coverage or R&D expense savings.[1]

How the AI coding assistant fits the business

AFGVF corresponds to the Agfa-Gevaert group, which provides diagnostic imaging and healthcare information technology solutions to hospitals and healthcare institutions. Its healthcare software manages imaging data and radiology workflows. The AI Software Coding Assistant is used by the company's healthcare software developers to write and maintain product code, with the goal of completing more development work with the same resources. It supports internal R&D rather than operating as a standalone product sold directly to hospitals.

The application has only one citable public disclosure, dated August 26, 2026, so there is no cross-period trajectory to compare. The company described it as a coding tool already in use and reported a task-level productivity range, but did not identify the product, the teams covered or the rollout pace. The evidence currently supports a pilot improving internal development, not deployment across all software R&D.

What the 30% to 50% range means

The 30% to 50% figure means that the productivity increase varies with the coding task handled by AI.[1] The range has no common disclosed baseline. The company also did not explain how completed work was measured, whether code quality changed at the same time, or whether rework, testing and maintenance time were included. The high end therefore cannot be treated as the improvement achieved by the entire development team.

The productivity gain could improve the output efficiency of R&D spending. If developers complete more reliable code with the same hours and budget, the company could advance more product work with the same investment, potentially lowering R&D cost per unit of software output. The earnings call did not translate the coding improvement into expense savings, staffing changes or faster product launches, however, and the R&D project mix and code complexity can also affect the final result.

AFGVF has provided a quantified return from AI coding on specific tasks, turning internal development efficiency from a general investment theme into a testable operating claim. The next evidence needed is the share of developers covered by the tool and the corresponding change in R&D expense or software output per unit. Until those figures are disclosed, the evidence confirms higher task productivity but not lower company costs.

Application assessment

• AI Software Coding Assistant | Business position: Support function | Deployment stage: Pilot | Scope: Single business unit | Value type: Cost reduction

Sources

[1] Drillr · AFGVF (AFGVF) · 2026-08-26 · Earnings call

Original: Then AI is not only an investment. It has a return and for instance today we are using AI for coding activities and here you have an immediate benefit because you are increasing productivity by 30 to 50% depending on what you do on AI. So actually it's not a cost, it's a boost for us. And indeed, we are integrating, we always have integrated AI for many years in the diagnosis part, in the solution part, in the image generation part. We have already solutions that are commercial today in AI. And the third impact where we are using AI is actually on what we call the workflow orchestration, because remember, we are not selling only a software, we are selling a full solution. where we are managing the workflow of the radiologist from the time he takes an appointment to the time the image is being stored and archived. Managing this workflow is leveraged today by AI.