Hype to ROI: Pillars of an AI Strategy You Can Start Building Now

A few days ago, as they do every year, IBM leaders, clients and partners gathered in Boston for the annual Think conference, where the latest news on innovations, product launches and availability, and technology trends are shared with our community.

This year, the event opened with an important statement: The era of AI experimentation is over. The velocity with which artificial intelligence is evolving and implemented in most areas of business, as well as the incalculable use cases emerging from its adoption, might suggest that we are still in a phase that is shaping the ways in which AI will be used in the future. While this might be true in a broader sense, the message for companies is unmistakeable: It is time to design an AI strategy and put it to the test. The time is now.

Why Is ‘Now’ the Time? 

There are a couple of reasons that leaders need to consider. On the one hand, it is a prime time for companies to gather what they have learned from their experimental stage, mainly understanding the impact and results that their use cases have generated. Ideally, these use cases were designed to impact a core area of their business strategy, but even if they haven’t been designed that way, it is time to string their use cases together — discarding those that did not yield the expected results — to create a strategy that will consider the entirety of their operation, instead of only certain elements. Otherwise companies risk creating innovation silos within their organization that are not interconnected and that do not maximize impact or results. 

On the other hand, there is a bottom line for technological innovation for companies that are aiming for positive business results: knowing when to transition from the hype generated by a new technology  to its ROI.

It is noteworthy that, for companies that operate in Mexico, the dollar return on investment hasn’t been (at least not initially) the driving motivator to implement AI, but rather untraditional ROI measurements, such as making operations more time efficient, being able to innovate quicker in relation to competitors, and producing software faster. These are some examples of the goals Mexican leaders described as the ROI they measured in a recent study commissioned by IBM.

That being said, the return on investment that a company wishes to obtain from AI implementation can only be achieved if the AI strategy behind it is aligned with business objectives, and if it integrates certain aspects that cannot be left out when deploying AI capabilities within organizations. 

The Keys to Strategic AI

The first pillar of any AI strategy is data. In some ways, data is the pulse of your AI strategy. Some leaders tend to believe that the more data you have, the better. However, quality is paramount over quantity. Businesses must invest in refining their data collection and management systems to ensure they are generating accurate, diverse, and ethically sourced datasets. These datasets serve as the foundation for training generative AI models to produce reliable outputs that can drive business value.

In Mexico, where we have a growing digital economy, harnessing the power of data should be a top priority. Companies need to establish comprehensive data governance frameworks that ensure privacy, security, and compliance with local regulations while facilitating data accessibility for AI applications. The data strategy should include investments in data cleansing, integration, and standardization. 

The objective is to make your data AI-ready, instead of letting AI function in an environment that is not ready to leverage data for automation and productivity. 

The second key component of an AI strategy is automation. Generative AI doesn't just automate tasks, it intelligently automates, learning and adapting with each iteration. This means businesses can expect not only increased efficiency but also enhanced decision-making capabilities. 

Some people might think that automation means putting repetitive tasks under the purview of AI, and that is certainly a part of it; however, automation goes beyond this generalized view. Instead, it means being able to manage assets, optimization cycles, and resources in a streamlined way, avoiding setbacks and adjusting faster to meet market demands.

Similarly, generative AI has the potential to significantly boost productivity by providing predictive insights and enabling employees to focus on high-value activities. Moreover, AI-driven tools can work around the clock, accelerating project timelines and enabling faster response times to market changes.

This is where AI agents are also incredibly relevant for an AI strategy, since they allow the handling of tasks in a more efficient manner, increasing the speed and volume at which people can execute specific activities that are “delegated” to agentic AI.

Lastly — but certainly not less importantly — a successful AI strategy requires a robust infrastructure. This is not just about having the right hardware or software, it's about creating an environment that fosters experimentation, learning, and continuous improvement.

Mexican enterprises should invest in building a flexible, scalable, and secure IT infrastructure. This includes cloud capabilities for AI model training and deployment, robust cybersecurity measures to protect sensitive data, and a culture that embraces AI as a strategic asset.

Cloud computing, in particular, provides the scalability needed to handle varying AI workload demands. It also enables cost efficiency, as businesses only pay for the resources they use. Moreover, cloud platforms often come with built-in AI tools, making it easier for companies to start their AI journey.

Cybersecurity is non-negotiable in this digital age. As AI models often deal with sensitive data, robust security measures are essential to protect against breaches and unauthorized access.

Embracing the AI revolution 

The time to step from hype to ROI is now. It offers immense potential for Mexican businesses to drive innovation, improve operational efficiency, and unlock new sources of value. However, realizing these benefits requires a strategic approach, underpinned by strong data management practices, smart automation, a focus on productivity enhancement, and a robust infrastructure.

As we move forward, let's remember that AI is a tool, and its effectiveness hinges on how we wield it. By integrating these four pillars into their strategies, Mexican businesses can position themselves at the forefront of this exciting new frontier, translating cutting-edge technology into tangible business outcomes.

IBM Mexico remains committed to supporting local businesses in their AI journey, offering expert guidance, technology solutions, and a deep understanding of the Mexican market context. Together, we can navigate this transformation, ensuring Mexico thrives in the age of generative AI.

The time is now!