Mexico’s AI Adoption Struggles to Deliver Business Value

Mexican companies face a growing gap between investment in AI and measurable business transformation, as organizations struggle to redesign processes, prepare employees and move beyond isolated technology projects.

The challenge companies adopting AI in Mexico face is no longer whether they can access the technology. It is whether they can turn that access into measurable business value. As AI becomes embedded across business operations, organizations risk entering what specialists call the “dead zone”: a stage in which companies invest in software, infrastructure, and digital tools without changing the processes, skills, or organizational structures needed to generate returns.

For Cecilia Lozano, Director of Devices for AI, Cloud, and Cybersecurity, IBM Guadalajara, the starting point is not the technology itself. “In IBM we have understood that as a business owner you have to take a step back, observe your company and not think about technology first, but your company first,” says Lozano. Her argument points to a broader challenge for businesses: AI adoption can produce limited results when companies treat it as an isolated technology initiative instead of as part of a broader transformation of the organization.

The Gap Between AI Investment and Transformation

The “dead zone” (or dead capital) describes the gap between technological investment and business value. Roberto Álvarez, Director of Advisory, KTSA, says companies can fall into this gap when they acquire new software, infrastructure or other technologies without adapting their processes or preparing their people for the changes that follow.

The risk is particularly relevant as companies expand their use of AI. Deploying a new tool does not automatically change how employees make decisions, how processes are designed or how organizations measure productivity.

According to Boston Consulting Group, 70% of digital transformation projects fail, highlighting the organizational challenge behind technology adoption. For companies, this means that the business case for AI cannot stop at implementation. The value of an AI deployment depends on whether it changes an operation, addresses a specific business problem or enables employees to perform tasks differently.

Lozano says organizations should first identify what could have a meaningful impact on the business and then determine which technology can support that objective. This approach also changes the role of employees in AI adoption. Rather than treating technology as a replacement for existing expertise, organizations need to use their internal knowledge to determine how AI should be applied to business processes.

Lozano says the existing workforce is one of the most valuable assets for training AI models because experienced employees understand which information matters, how processes operate, and what the technology needs to process. That places talent at the center of the transformation challenge.

AI is Exposing a Workforce Readiness Gap

The adoption of AI is creating a second disconnect: employees may be prepared to use the technology, but organizations do not necessarily appear equally prepared to develop those capabilities.

According to IBM’s AI Productivity Survey 2025, 91% of employees in Mexico say they are ready for AI, while only 70% believe their company is doing something to develop those skills. The difference suggests that technology adoption is advancing alongside a skills challenge. Companies may have access to AI tools, but employees still need training, new processes and organizational support to integrate them into daily operations.

Álvarez says the challenge is not only the number of people with technological skills but also the type of capabilities organizations need. AI is increasing demand for skills such as analytical thinking, problem design, continuous learning and ethical decision-making.

For businesses, this means AI transformation extends beyond technical training. Employees need to understand how to identify problems that AI can address, evaluate its outputs and incorporate the technology into processes without losing the business context behind those decisions.

The responsibility also extends beyond individual companies. Álvarez says public policy, the private sector and educational institutions need to work together to develop the talent base required for competitiveness. The issue becomes more significant as companies compete for investment and specialized capabilities.

The transformation of the workforce is also changing the role of technology hubs such as Guadalajara. Yanai Rezende, General Manager, HP Guadalajara, says the case for attracting technology investment is increasingly based on innovation, talent and speed of execution rather than cost alone.

HP Guadalajara has almost 2,800 employees and is one of eight global core hubs for the company, alongside centers in the United States, Asia, and the European Union. Rezende says younger generations are looking for flexible, agile and human work environments, while companies have a responsibility to provide employees with the technology required to work effectively.

That shift gives the AI transformation challenge a broader dimension. For companies operating in Mexico, the objective is not only to acquire advanced technology but to build organizations capable of using it effectively.

The same principle applies to cybersecurity. Lozano says Mexico has become a digital economy, with 80% of the population having internet access and 60% of small and medium-sized enterprises selling online. As organizations become more connected, however, their exposure also extends beyond their own infrastructure.