Ethical AI Drives Higher ROI, Trust for Mexican Companies: IBM

Mexican organizations that allocate greater resources to ethical AI consistently report superior operational benefits, a better return on investment, and increased customer trust, reveals the IBM Institute for Business Value in collaboration with the Notre Dame–IBM Tech Ethics Lab.  These findings position ethics in the AI industry as a future top strategic differentiator with measurable financial returns.

 “AI ethics is a competitive differentiator. Integrating ethics into AI does not only reduce risks, but it generates tangible returns in profitability, operation, and customer trust,” says Mauricio Torres, President and General Manager, IBM Mexico. 

The company reports that 53% of Mexican executives surveyed confirm that adopting ethical AI practices has resulted in greater customer trust and better product quality. This evidence suggests that ethics is not an operating cost, but a strategic driver capable of producing quantifiable returns.

While AI implementation has historically centered on operational optimization and efficiency, the study argues that the robust integration of ethical frameworks serves as a value multiplier. The benefits reported by Mexican executives investing in ethical AI include greater trust (67%), a strengthened reputation (58%), and the mitigation of reputational risks (58%). These elements are critical in the contemporary business environment, where brand perception and customer loyalty are inherently linked to corporate responsibility practices.

Despite the clear benefits, the adoption of essential ethical AI tools remains limited. Only 36% of Mexican executives report using these tools. This figure indicates a deficit in the structuring of frameworks and organizational capacity necessary to manage increasingly complex AI systems. The gap between acknowledging the value of ethics and its practical implementation is a critical factor that corporations must address to fully capitalize on the opportunities that AI offers. Concerns about the growing autonomy of these systems are evident, with 64% of Mexican executives admitting they will have to significantly rethink their ethical AI frameworks to maintain operational consistency.

Projected Investment Increase and Financial Performance

IBM anticipates an acceleration in resource allocation toward ethical AI. Mexican executives plan to increase their spending in this area, moving from 5.3% of the total AI budget in 2023 to 10.7% in 2026, nearly doubling the investment.

Only 44% of Mexican organizations have integrated ethics into their overall AI strategy, a figure that requires review given the impending evolution of systems toward AI agents which, according to 71% of executives, will demand stricter ethical guidelines than systems currently in place. Torres says that the shift to agents makes ethical frameworks increasingly critical for responsible and sustainable innovation.

Internationally, companies in the top quartile of ethical AI spending have reported up to 30% more AI-attributable operational benefits than those in the bottom quartile in previous years, reports IBM. The correlation between ethical investment and financial outcomes establishes a clear precedent for budgetary prioritization. 

Identification of Strategic Barriers and Challenges

The transition to ethically responsible AI faces defined challenges in Mexico, which limit the potential value realization of these practices. Explainability, bias, and trust have been identified as key barriers to AI adoption by 49% of Mexican executives. An additional challenge manifests as the inherent tension between business objectives and ethical values, reported by 64% of Mexican executives.

In addition to conceptual and alignment barriers, operational challenges hinder investment in Mexico. These include:

• Talent Attraction Difficulty: Sixty-four percent of respondents state having difficulties finding qualified personnel in the ethical AI field.

• Training Scalability: Fifty-three percent report challenges in executing large-scale training programs within the corporation.

• Financial Resource Limitation: Sixty percent cite limited financial resources as an impediment to investing in ethical AI.

These obstacles indicate the necessity of developing a talent management strategy and resource allocation that supports the implementation of ethical frameworks. The arrival of more autonomous systems amplifies the urgency of addressing these deficiencies. Ethical AI must be conceived as a fundamental business strategy to reduce risks, unlock opportunities to generate more trust, drive innovation, and enable more sustainable returns in the long term.