This research aims to evaluate the economic valuation of lead air pollution in the AA.HH. Virgen de Guadalupe, Callao, Peru. A survey was conducted with 182 residents, focusing on air quality, temporary exposure to pollution, aesthetic appreciation of the environment, willingness to accept (WTA) economic compensation, and willingness to pay (WTP) to mitigate lead air pollution. The data were analyzed using the logit model through STATA16 software. The results revealed that 62.09% of respondents were willing to accept economic compensation, while 56.04% expressed willingness to pay for reducing lead pollution. Furthermore, it was determined that the average monthly WTP is PEN 62.48 (USD 16.47), amounting to PEN 1,201,865.28 (USD 329,103.16) annually for the entire population of 1603 residents. In contrast, the average monthly WTA per resident is PEN 153.59 (USD 40.48), totaling PEN 2,954,457.24 (USD 809,010.16) annually due to lead air pollution. The study concluded that environmental perception, awareness, the desire to maximize present utility, and uncertainty about the future significantly influence the economic valuation of lead air pollution in this community.

Artificial intelligence (AI) is transforming the accounting function, but evidence from emerging economies still leaves a central question unresolved: whether the profession’s traditional strengths are sufficient to support this technological transition. This study examines this issue in Peru, where digital reform has advanced rapidly, but professional adaptation remains uneven. Using survey data from 424 accounting professionals and academics, a Covariance-Based Structural Equation Modeling (CB-SEM) approach was employed to test the relationships between Sustainability, Professional Challenges, IFAC Ethics, and AI Orientation. The construct previously described as AI adaptation is now defined more cautiously as AI Orientation, because its indicators capture a broad perceptual orientation toward AI, including perceived challenge, workflow impact, curricular integration, substitution concerns, and routine use, rather than verified adoption behavior. The results confirmed the strength of the traditional professional sequence: Sustainability significantly predicted Professional Challenges (β = 0.637; p < 0.001), and Professional Challenges strongly predicted adherence to IFAC Ethics (β = 0.972; p < 0.001). However, the direct path from Sustainability to IFAC Ethics was not significant (β = 0.200; p = 0.096). Regarding technological integration, the model revealed a structural disconnect. While Sustainability showed a weak direct effect on AI Orientation (β = 0.279; p = 0.045), neither Professional Challenges (β = 0.160; p = 0.510) nor IFAC Ethics (β = 0.037; p = 0.810) significantly predicted AI Orientation. These findings indicate that while the ethical and adaptive core of the Peruvian accounting profession remains highly resilient under pressure, its connection to AI is still fragmented, with algorithmic tools often perceived as external technological systems rather than integrated accounting competencies.