Evaluating the effectiveness of AI implementation requires moving beyond qualitative employee feedback to objective metrics. Companies should analyze historical data, such as average ticket resolution time, while ensuring that periods compared are consistent in terms of workload and request types.
Once efficiency gains are identified, they must be converted into business value based on company strategy. If the business is stable, labor costs can be optimized. If the business is growing, AI allows handling increased volume without proportional hiring. Alternatively, freed-up resources can be reallocated to other tasks.
AI can also help manage peak loads, reducing the dependency between business growth and headcount. When calculating the financial viability, companies must determine the Total Cost of Ownership (TCO), which includes tokens, infrastructure, maintenance, and development costs.
Infrastructure investments should be amortized across multiple projects to ensure accurate economic modeling. If a project is not currently profitable, companies may present a long-term forecast, such as a three-year horizon, provided it is supported by clear assumptions about future business growth and potential ROI.
