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Limitations

Although the HugAI methodology offers a robust framework, it is important to consider its limitations:

  • Dependence on the quality of AI models: The results and recommendations of the agents depend on the accuracy and updating of the underlying models.
  • Requires organizational maturity: Effective adoption demands teams willing to collaborate and adapt to new processes and technologies.
  • Does not replace expert judgment: AI is a complement, not a substitute for human knowledge and experience, especially in critical or ambiguous contexts.
  • Possible biases and errors: Agents may inherit data biases or make mistakes; therefore, human supervision is indispensable.
  • Implementation and maintenance costs: Integrating and maintaining AI agents may require investment in infrastructure, training, and continuous updating.
  • Regulatory and ethical compliance: The methodology must be adapted to the legal and ethical requirements of each industry or region.