Resource management (RM) is an essential task in IT services and consulting companies. Larger companies employ resource managers who take care of scheduling employees and assigning them to projects. RM has largely been spared from AI automation so far.
AI will change RM in two steps:
1. Resource managers will be replaced by AI agents
2. AI will be incorporated into project staffing
The first step is clear. As a back-office function, RM is an ideal candidate for automation by AI agents.
The second step sounds like hybrid teams of humans and AI agents – AI colleagues in the project team. We are not quite there yet. In practice, it is a matter of systematically driving the use of AI. Otherwise, it is up to employees to decide whether and for what purposes they use AI. RM can identify tasks that AI can take over and take this into account in project staffing.
AI also makes it possible to cover skills that employees do not have.
Example: Cobol skills are required for a legacy transformation project. No one has them. But with AI support, a developer can translate Cobol into a modern programming language. However, not every AI tool can handle Cobol. Google Gemini, for example, cannot. And the developer must have experience with AI-supported software development and the functional requirements. Thanks to AI, resource management has additional options for the Cobol Developer position. The search becomes more complex and impractical without AI support (step 1).
Even the best AI is useless without suitable data. RM requires skills and availability of resources, both human and artificial. AI is always available and knows its own skills. Reliable data on employee skills and availability is more difficult to obtain. This requires an integrated solution for skill and resource management.
The pressure to automate with AI is high, especially for IT services and consulting companies. Customers are not willing to pay daily rates for work that AI can do just as well. This inevitably has an impact on resource management.
How can companies prepare?
Define responsibilities between sales and delivery
Resource managers are a kind of gatekeeper between sales and delivery.
If this role is replaced by AI, the responsibilities between sales and delivery must be clearly defined. Who decides which employees are assigned to which customers? Sales, project managers, team leaders?
What can sales do on their own, and where does delivery need to give its approval?
Define global resource management processes
Before automating processes, they should be optimized. In large companies, resource management usually varies from country to country. Responsibilities are defined locally, visibility on resources is limited, and cross-border project staffing is cumbersome.
Uniform, lean processes can increase efficiency even without AI.
Systematically record resource requirements
To manage the use of AI across the board, companies must be able to evaluate all resource demands. In addition to the CRM and ERP, requirements are often found in Excel sheets or email inquiries. To capture such informally recorded resource requirements, suitable software tools are needed. Usability plays a decisive role here; if it is not easier than Excel, it will not be used.
Integrate skill and resource management
Skill management and resource management are separate processes in most companies. Both must be merged, not only to enable staffing decisions to be made. This also has a significant impact on employee development. In the future, domain knowledge and problem-solving skills will become more important than detailed technical knowledge. The latter is provided by the AI colleague.