Scheduler

Transportation, Logistics, and Procurement

Significant Impact of AI on the Job

40.00%

level of automation

0%
100%

Our comments:

Schedulers play a crucial role in synchronizing and optimizing production activities. While specialized software can automate some tasks, such as planning based on predefined criteria, human judgment remains essential for handling unforeseen circumstances, coordinating with multiple departments, and making strategic decisions.

The relational aspect, related to coordination with various departments, is also challenging to automate. However, with the development of AI and predictive tools, some tasks could be further assisted or optimized, partially altering the traditional role of schedulers.

This section reviews the 3 main tasks associated with the job studied and assesses the potential level of automation induced by AI ('AI Automation Impact').
The modeling uses 8 criteria detailed on the 'Methodology' page.
Tasks AI Automation Impact
Plan and schedule production activities, taking into account resource constraints, deadlines, and costs. Moderate
Coordinate with various departments, such as production, purchasing, and sales, to ensure optimal synchronization of flows. Significant
Use and configure specialized scheduling software to optimize the production chain based on priorities and emergencies. High
Through our research, we have identified two pivotal categories of skills that will be impacted by AI-driven automation :
  • 'At-risk skills,' which are likely to become obsolete due to their susceptibility to automation
  • 'Future-proof skills', which are projected to retain their value and resist automation, thereby ensuring their relevance in the forthcoming job market.
Let's have a look at the future of your skills for this job :
At-risk Skills
Monitoring Company-Specified Activity Data With the advancement of AI and automated systems, the collection, analysis, and utilization of data are becoming increasingly automated. Advanced analytical and visualization tools can make this task more efficient, reducing the need for the scheduler to do it manually.
Qualifying Intervention Requests Advanced machine learning systems might be capable of analyzing and automatically qualifying a large majority of intervention requests based on predefined criteria, history of previous interventions, and real-time parameters. Only intervention requests that present anomalies or are outside the usual patterns would require human intervention for deeper qualification.
Future-proof Skills
Continuous Communication with Field Agents The ability to communicate effectively with field teams, understanding their needs, and responding promptly to their inquiries remains essential. AI cannot replace the human aspect of this interaction, especially in emergencies or unforeseen situations.
Defining and Identifying Agents' Skill Needs While AI can help identify skill gaps or areas of needed training, the ability to understand human needs and formulate recommendations for skill development will always be crucial.

How does AI impact this job type ?
Get the full analysis