80% of organizations in Mexico are accelerating AI adoption without maintaining visibility into how, where, and by whom these systems are being deployed. IBM research reveals that governance gaps can increase operational, cybersecurity, compliance, and accountability risks as investments in AI continue to expand across the country.
AI adoption is progressing rapidly across Mexico, but governance mechanisms are not keeping up. According to IBM, only 20% of organizations in Mexico know exactly what AI capabilities are deployed across their operations and where those systems are running within their technology infrastructure. As companies increase spending on AI, limited visibility is emerging as a business risk.
As organizations deploy AI across multiple business functions without maintaining central oversight, gaps in adoption and governance are becoming more apparent. “Only 20% of Mexican respondents to this AI Governance Survey reported knowing exactly what AI capabilities are being implemented and where they are located within the company’s technology structure.” say Luis Felipe Guzman, Data and AI Leader, IBM Mexico.
The results of this survey are IBM Business Value Institute and Dubai Future Foundation. The study surveyed more than 1,000 senior executives across 21 industries and more than 20 countries.
Only 13% of respondents in Mexico manage inventory with AI systems. Such an inventory serves as a basic governance mechanism, allowing organizations to identify what models are in place, what data is being processed, what decisions can be influenced, and which parties are responsible in the event of an error.
of result This suggests that the adoption of AI is moving faster than the controls designed to manage it. More organizations are integrating generative AI, intelligent assistants, and autonomous agents into their daily operations, but many still lack a complete understanding of how these technologies interact with internal systems and sensitive information.
This challenge extends beyond formally approved applications. Employees can employ publicly available AI services on their own, connect them to business processes, and upload company information without permission from information technology teams. This creates a fragmented deployment that can operate outside of established security controls. As a result, organizations struggle to reconstruct the events that occurred after a data breach, compliance audit, operational failure, or dispute involving automated decision-making.
Governance challenges become more urgent as AI systems evolve from passive assistants to autonomous agents capable of taking actions, changing records, and interacting directly with enterprise workflows. According to IBM research, only 3% of organizations operate a centralized platform that can coordinate AI agents. Without these controls, businesses face increasing difficulty monitoring decisions, controlling costs, and managing exposure to risk.
Investment is increasing, but awareness is decreasing
Governance gaps are emerging as AI investments remain a strategic priority for Mexican companies. According to the first edition, KPMG’s Global AI Pulse StudyOrganizations in Mexico expect to invest an average of USD 171 million in AI over the next 12 months. The study, published by KPMG International, found that 74% of organizations in Mexico will continue to prioritize AI investments during the recession.
At the same time, 72% of organizations in Mexico report that AI is already creating meaningful business value, which is higher than the global average of 64%. However, the same study highlights challenges that are largely consistent with IBM’s findings. Companies report difficulty measuring AI-driven value, adapting governance models, managing data privacy, addressing cybersecurity risks, and overcoming employee resistance to adoption.
“The real value of AI lies not in how much an organization invests, but in how effectively it can be integrated into business operations.” say Gustavo Gómez, AI Lead Partner, KPMG Mexico
The contrast is striking. Although organizations are allocating significant capital to AI initiatives, many still lack visibility into the systems already running in their environments. This issue will become increasingly important as AI agents become widely adopted. KPMG reports that 31% of organizations in Mexico have already deployed and scaled AI agents, and 15% have reached a level of maturity where AI adoption creates measurable competitive advantage and business value.
Risk management has emerged as a critical factor separating high-performing organizations from the broader market. Globally, 75% of business leaders express concerns about data security, privacy, and AI-related risks.
AI is a business and security priority
Cybersecurity experts warn that these concerns will grow as AI capabilities expand. According to Kaspersky Lab’s 2026 predictions, AI will reshape both cyber defense and cyber crime. The company expects deepfakes, autonomous attack tools, synthetic voice fraud, and AI-generated social engineering campaigns to become increasingly sophisticated and accessible.
These developments increase risk for organizations that lack visibility into AI deployments. Kaspersky argues that governance can no longer be treated solely as a compliance requirement. Instead, organizations must integrate security and privacy-by-design principles throughout the AI lifecycle, from development and deployment to monitoring and decommissioning.
The company also recommends incorporating AI governance into enterprise risk frameworks, establishing clear internal policies, conducting impact assessments, implementing technical controls, and maintaining human oversight of critical business processes.
“Companies will be operating in an environment where they can no longer assume by default that information is authentic.” say Claudio Martinelli, General Manager, Americas, Kaspersky Lab. “Competitive advantage will increasingly depend on building resilient business models where the use of AI is aligned with risk management frameworks.”
For Mexican companies, the convergence of these findings points to broader strategic challenges. Deploying AI has produced measurable business results and is attracting significant investment. However, visibility, governance, and accountability remain underdeveloped in many organizations.
