AI Adoption: The Challenge of Generating Real Value
AI Adoption: The Challenge of Generating Real Value
48% of companies are already executing at least one generative artificial intelligence project, according to Ingenia's Technological Evolution Report.
Although there is still a feeling that companies are moving slowly in the adoption of artificial intelligence (AI), the figures show something different. According to the Technological Evolution Report prepared by Ingenia, this technology is reaching a medium degree of maturity, with several outstanding data points: 48% of companies are executing at least one generative AI project, and in some large corporations, this number reaches 6 ongoing projects. Following the trend, Telecommunications, Banking/Finance, and Energy stand out as the industries with the greatest development.
But although adoption is high today, the impact is not always so. Many organizations incorporate AI tools for minor tasks without a clear strategy that connects them to business objectives. In other words, the problem is no longer using artificial intelligence, but doing it with purpose and implementing it with a strategy that generates real value.
In many organizations, the implementation of artificial intelligence remains reactive. Specific tools or solutions are incorporated because they are fashionable or because a competitor uses them, but without a strategic vision that articulates them with business objectives. This generates a superficial adoption: tasks are automated, chatbots or virtual assistants are added, but without measuring the real impact on productivity, efficiency, or customer experience.
In this sense, companies that truly manage to adopt artificial intelligence and generate a tangible impact on the business remain few. Globally, only 37% of organizations have a clear AI adoption strategy. This data marks an important difference from other moments of technological change: historically, the incorporation of new knowledge or tools started from strategy. First came planning, then the technology was enabled, and finally, it was adopted.
With artificial intelligence, it happened the other way around. Companies began to use it, to test what happened and, only then, to think about how to govern it so that it truly generates value and does not imply a waste of resources. This inversion of the process reveals the main problem: the lack of experience.
AI has existed for more than four decades, but the arrival of generative AI, the protagonist of this revolution, is recent. Even engineers specialized in generative AI have, on average, less than three years of experience. This novelty explains why so many organizations are learning on the go: as they begin to generate value, they discover that they need to define a solid strategy to sustain it. And when talking about this technology, the strategy cannot be limited to the digital plane. It is not a separate path, but the business strategy itself. AI today forces a rethinking of business models, in the same way that the industrial revolution or the internet revolution did in their time.
For this reason, organizations need to update their strategy to incorporate artificial intelligence as a central part of the business. Those who do not do so run the risk of falling behind in a scenario where companies have already been born that will be valued at billions of dollars, with fewer than ten employees, and whose operation relies largely on AI agents. Competing with these companies, which were born with artificial intelligence, will be increasingly challenging for those who do not adopt this change of model.
On the other hand, another of the great challenges facing adoption in companies is not technological, but human. The fear of replacement remains one of the main barriers. Many business owners wonder how to get their teams to incorporate artificial intelligence without fear of losing their jobs. The answer lies in understanding that this transformation, like every technological revolution, generates fears, but also new opportunities.
The reality is that AI, in its current state, is still far from completely replacing people. What can happen, and in fact is already happening, is that those who do not learn to use it will be replaced by those who do. Adapting is key. History proves that every technological revolution changed the ways of working, but also created new professions. The same will happen now. Adopting AI "head-on" is an opportunity to boost skills, acquire new knowledge, and develop competencies that are essential today. Because, at the end of the day, there is something that this technology cannot replicate: the empathy, judgment, and conscience that make up leadership and decision-making.
Another myth worth dismantling is that artificial intelligence necessarily implies large investments or is reserved only for large companies. Reality shows the opposite: today AI is at a very low cost; in fact, it democratizes the use of technologies in general. In this sense, the sectors that are moving forward most in its integration are banking, insurance, and retail. These industries have been aligning their strategy in a sustained manner, driven by the need to improve the customer experience, automate processes, and optimize decisions in real-time.
Faced with this scenario and with current global investment and the expectation that central banks will reduce rates, it is likely that a large part of the surplus resources will be directed toward artificial intelligence, renewable energies, and datacenters. This trend opens the door to a near future in which the adoption of AI will be practically generalized. We will all be able to build our intelligent agents without depending on specialized engineers, and technology will stop being a barrier to become a daily tool that boosts productivity and results.
However, what is most concerning is the lack of action from governments. While the private sector advances, many public policies still do not address AI with the necessary seriousness. For technology to generate a real and sustained impact, it is fundamental to incorporate it from the base: education. If governments focus on policies that encourage the learning of AI starting from high school, a new generation will be formed that is prepared to face the challenges and opportunities of this technological revolution.
The invitation is twofold. For companies: leave fear behind, adopt artificial intelligence fully and, above all, integrate it into the business model strategy, not just in isolated initiatives. For governments: take measures that allow enabling the technology, establish clear policies, and foster education as a driver of future growth. Only then can the full potential of AI be harnessed in an efficient, ethical, and sustainable manner.
