The AI Horizon: Mapping Your Integration Strategy

The strategic adoption of AI tools has emerged as a crucial driver of competitiveness and efficiency, facilitating the digital transformation of enterprises. Nevertheless, the hasty integration of AI technology without the prior establishment of well-defined business objectives and a comprehensive assessment of compatibility, can pose significant risks to operational integrity and render substantial investments ineffective. A case in point is the potential incompatibility of inadequate IT infrastructure with AI tools, resulting in formidable challenges and elevated costs needed to correct the integration of these technologies into systems.

"Mexico ranks fifth among the 12 countries that make up the Latin American Artificial Intelligence Index, with a score of 48.55 against the regional average of 42.61. The country shows a good performance in research, although the need to strengthen its infrastructure is evident," says Carlos Marcel, Managing Director, Kyndryl Mexico. "Even though [Mexico’s] ranking is high up in the region, there are still many opportunities to grow and to strengthen the technological ecosystem to allow AI to really make a substantial difference in its competitiveness," he explained to MBN. 

Businesses looking to leverage AI-powered tools are constantly looking to enhance their operational efficiency. By harnessing this technology, organizations can effectively streamline internal processes, automate repetitive tasks, and optimize resource utilization. Furthermore, by customizing interactions, anticipating customer needs, and enhancing service quality through AI-driven insights, businesses can significantly improve customer’s experience and gain an advantage over competitors. 

“To ensure the successful integration of AI, companies must know with absolute certainty the state in which the company’s digital architecture is in before even beginning to plan to integrate enhancing tools,” says Diego Halffter, Chief Data and Analytics Officer, Justo. A company cannot start evaluating the integration of AI-powered tools and models if it does not have clear business objectives. “The key to a successful AI solution resides in its ability to address well-defined needs. Artificial intelligence by itself is destined for failure,” he added. To achieve this, he recommends breaking down each step of the integration phase as much as possible so that AI implementation and its scale is as seamless and organic as possible. 

“Nevertheless, conducting a comprehensive cost-benefit analysis and measuring the return on investment is indispensable to ensure that AI implementation aligns with an organization’s financial objectives and&or limitations,” says Marco Antonio Hernández, CDO, PROSA.  

“The comprehensive documentation of the organization's requirements, the reason for implementation—such as cost reduction and time efficiency—and a well-defined timeline for expected outcomes is imperative.," said Ignacio Madrid, Head of Data Management, Citibanamex. This approach ensures alignment with user requirements and expectations. The process, he elaborated, should be underpinned by robust data governance frameworks, wherein the Chief Data Officer ensures data quality and curation, while the Chief Analytics Officer identifies use cases that deliver tangible value through data-driven insights. This will ensure that investments are inextricably linked to the specific use cases, a strategy that promises a more accurate allocation of resources and a more optimal path to ensuring ROI.

“Maintaining a simple, yet clear approach to the case of use and business objectives for AI-powered tools is key for the most effective implementation of this technology,” said Pablo Guzzi, Chief Data and Analytics Officer, Ualá. Simplifying complex data into clear and unambiguous metrics allows for development of lucid and straightforward solutions that are valuable for the company. Furthermore, adopting a forward-thinking perspective, with an eye on large-scale deployment, prioritizes scalability from the inception of their AI journey. This approach, he suggested, not only fosters innovation but also paves the way for sustained competitiveness.

Another key factor to ensure successful AI implementation is the interconnectedness of the different areas within an organization. Alfredo Pequeño, Director of Payment Methods and Data, BanRegio, underscored the essential nature of collaboration and cohesion when integrating AI solutions. “It is useless if only the CDO or CAO are aware of what the analytic model is doing, because data and decision-making touch every single branch of an organization. No man is an island, so every person involved must have a clear idea of what the goal and expected results are.” 

In the future, when companies have successfully integrated these solutions into their processes, there will be a redefinition of organizational structures, according to Justo’s CDO. As businesses evolve with these types of technology, those who have the skills to carry this out will be the leaders. “Today's CDOs will be the CEOs of the future, as today's skills will be the skills needed for tomorrow's companies,” he concluded.