When Will AI Replace Classificateur et cubageur de grumes ?

The automation of log grading and scaling tasks is not a distant future; it's rapidly approaching. By 2029, approximately 35% of these jobs will be impacted by AI. Initial displacements for manual graders performing routine volume calculations and standard grade assignments are anticipated as early as 2026-2027. This early wave will primarily affect those working in controlled mill yard environments.

The mid-phase of this transformation will see further integration of AI technologies. As machine vision systems become more sophisticated, identifying defects and assigning grades will become faster and more accurate. This will lead to increased efficiency and reduced reliance on human intervention for standardized tasks within timber processing facilities.

While specific dates for the 'late' phase are not provided, the trend indicates a continuous increase in AI adoption. The industry's move towards automated grading systems, powered by technologies like LiDAR and computer vision, suggests a long-term shift in the nature of work for log graders and scalers. The $180 million industry is actively investing in these solutions.

Manual graders performing routine tasks such as volume calculations, standard grade assignments, and repetitive measurements in controlled mill yard settings face the highest risk of displacement. These are the roles most susceptible to automation by AI-powered systems that can perform these functions with speed and consistency.

Specialists, however, are likely to remain in demand. Those who handle non-standard species, complex defect assessment under variable lighting conditions, dispute resolution, and field scaling in remote harvest sites possess skills that are currently harder to automate. The report implies these roles may see increased value or even salary increases as the need for human expertise in complex scenarios grows.

To navigate the upcoming AI revolution, log graders and scalers need to adapt. Focusing on developing skills that complement AI, rather than compete with it, is crucial. This includes enhancing expertise in areas where human judgment remains superior, such as complex defect analysis and dispute resolution.

Embrace new technologies and consider upskilling in areas related to AI implementation and oversight. Familiarizing yourself with tools like SILVACOM and Timbeter, and understanding how machine vision systems work, can provide a competitive edge. Continuous learning and adaptability will be key to long-term career security in the evolving industry.