{"id":36630,"date":"2026-07-30T07:10:43","date_gmt":"2026-07-30T12:10:43","guid":{"rendered":"https:\/\/itdconsulting.com\/?p=36630"},"modified":"2026-07-30T07:10:43","modified_gmt":"2026-07-30T12:10:43","slug":"ia-empresas-productividad","status":"publish","type":"post","link":"https:\/\/itdconsulting.com\/en\/noticias\/ia-empresas-productividad\/","title":{"rendered":"AI Will Change Companies Forever, but Productivity Will Take Years to Take Off"},"content":{"rendered":"
Artificial intelligence has become one of the most influential and debated technologies of the 21st century. Since the emergence of models capable of generating texts, images, code, and complex analyses, numerous companies have begun a race to incorporate these tools into their operations. The general expectation is that AI will trigger a historic leap in productivity, allowing workers to complete more tasks in less time and enabling organizations to operate much more efficiently. However, the history of previous technological revolutions indicates that the economic impact of an innovation rarely appears immediately.<\/p>\n\n\n\n
The current enthusiasm recalls other moments of technological transformation in which initial expectations were very high. When personal computers began arriving in offices during the 1980s and 1990s, many experts expected companies to quickly experience significant increases in productivity. However, economic data took more than a decade to show the real benefits of that technological investment. The reason was that computers, by themselves, did not change the way people worked; companies had to modify their structures, processes, and internal organization in order to truly take advantage of their capabilities.<\/p>\n\n\n\n
Artificial intelligence could face a similar process, although with its own characteristics. The difference is that AI does not only automate repetitive tasks, but also participates in activities related to knowledge, creativity, and decision-making. This makes its integration a much more complex challenge because it directly affects the way millions of professionals carry out their work. The question is no longer only whether artificial intelligence will increase productivity, but how much time companies will need to fully adapt to it.<\/p>\n\n\n\n<\/figure>\n\n\n\n
AI Changes the Nature of Work<\/strong><\/h2>\n\n\n\n
One of the main differences between AI and previous technologies is that AI is not limited to executing previously defined instructions. Current AI systems can interpret information, generate content, identify patterns, and provide answers based on large amounts of data. This means that the influence of AI is not concentrated solely on administrative or repetitive tasks, but also on jobs traditionally considered intellectual, where AI can provide new capabilities.<\/p>\n\n\n\n
A designer can use AI to create initial concepts before developing a final proposal. A programmer can use AI to generate code snippets, detect errors, or accelerate development processes through AI tools. A researcher can analyze large volumes of information with AI in less time, and a financial professional can receive AI support to interpret complex trends. In all these cases, AI does not necessarily eliminate human involvement, but rather changes the relationship between people and their work tools, creating a collaboration between humans and AI.<\/p>\n\n\n\n
This characteristic makes AI adoption deeper than simply incorporating a new software program. Companies not only have to teach their employees how to use AI tools, but they must also redefine which tasks workers perform and which can be delegated to automated AI systems. The main value of AI can be found precisely in freeing up human time for activities that require critical thinking, creativity, strategy, or personal interaction, while taking advantage of AI capabilities.<\/p>\n\n\n\n
However, this AI-driven transformation also generates uncertainty. Many workers perceive AI as a threat because they fear that their roles may be partially or completely replaced by AI systems. This concern can become a significant barrier to AI adoption, especially if companies do not clearly explain how AI will be used and what role people will have within the new AI-based work model.<\/p>\n\n\n\n
The Human Factor: Resistance Can Slow Down the AI Revolution<\/strong><\/h2>\n\n\n\n
Technologies are not adopted solely because of their technical capabilities. User acceptance, trust, and the perception of benefits are fundamental factors in determining the success of any innovation. In the case of AI, this aspect becomes especially important because AI tools directly affect tasks that have defined entire professions for decades.<\/p>\n\n\n\n
When a company introduces an AI system, employees can react in different ways. Some see AI as an opportunity to reduce repetitive tasks and improve their performance, while others may view it as a risk to their job stability. If the organization does not properly manage this transition toward AI, resistance, rejection, or even limited use of AI technology may emerge.<\/p>\n\n\n\n
The fear of job replacement by AI is not a new phenomenon. During the Industrial Revolution, many workers opposed machines because they believed they could destroy traditional jobs. Over time, some professions disappeared, but new occupations related to emerging technologies also appeared. The current difference is that AI affects highly skilled sectors, which increases the sense of uncertainty about the impact of AI.<\/p>\n\n\n\n
This resistance can become a kind of involuntary \u201csabotage\u201d of productivity. It does not necessarily mean that workers are trying to harm the company, but rather that they may avoid using AI tools that they perceive as a threat. An AI technology that is not accepted by those who are expected to use it will hardly reach its full potential, regardless of how advanced its technical AI capabilities are.<\/p>\n\n\n\n
The Challenge of Transforming Companies from Within<\/strong><\/h2>\n\n\n\n
One of the biggest obstacles preventing AI from generating a significant increase in business productivity is that many organizations attempt to incorporate it without modifying their traditional structures. For decades, companies have built processes based on previous tools, with separate departments, defined hierarchies, and working methods that were not designed for an AI technology capable of automating and complementing cognitive tasks. Introducing AI into these systems without making deep changes can considerably limit the benefits of AI.<\/p>\n\n\n\n
Experience with other technologies shows that the companies that gain the greatest advantages are not necessarily the first ones to buy a new tool, but rather those that manage to adapt to it most effectively. In the case of computers, companies that simply replaced paper documents with digital files achieved small improvements, while those that reorganized their operations around digital information achieved much greater transformations. Something similar could happen with AI, as the true value of AI will depend on how organizations redesign their processes using AI.<\/p>\n\n\n\n
An example can be seen in the business and administrative sector. A company could use AI to draft reports more quickly, but the benefit will be limited if it maintains unnecessarily long procedures for reviewing, approving, and distributing them. In contrast, an organization that reorganizes its workflows to combine AI\u2019s analytical capabilities with human supervision can achieve much deeper improvements. The difference is not only having access to AI, but building an environment where AI can deliver its full potential.<\/p>\n\n\n\n
For this reason, many specialists believe that the next productivity revolution will not depend solely on the evolution of AI models, but on companies\u2019 ability to adapt to AI. Technical advances in AI can be extraordinary, but an unprepared organization may achieve modest results even when using the most advanced AI tools available. The technological transformation driven by AI has always also been a cultural transformation.<\/p>\n\n\n\n
The Adoption Curve: Why Could Benefits Take Longer to Appear?<\/strong><\/h2>\n\n\n\n
When a revolutionary technology such as AI emerges, there is often a gap between initial expectations and real results. During the first years, the media and investors tend to highlight the future possibilities of AI, while companies are still learning how to use it correctly. This period can create a sense of disappointment because AI appears not to fulfill the promises that were made. However, it is often simply a necessary phase before reaching mature AI adoption.<\/p>\n\n\n\n<\/figure>\n\n\n\n
AI is currently at a similar stage. Millions of people have started using tools based on generative AI models, but most companies are still experimenting with their most effective applications. Some organizations use AI to automate specific tasks, while others are developing broader strategies to integrate AI into their daily operations. The result is a transition scenario where the final economic impact of AI cannot yet be fully observed.<\/p>\n\n\n\n
The economist Erik Brynjolfsson and other researchers specializing in technological productivity have explained that major innovations often require complementary investments. It is not enough to simply buy a new AI technology; it is also necessary to develop new knowledge about AI, change internal processes, and create structures adapted to that innovation. These changes can take years to complete, but when they arrive they can produce significant increases in efficiency thanks to AI.<\/p>\n\n\n\n
This historical pattern helps explain why AI will not necessarily cause an immediate leap in global productivity statistics. Although some specific companies are already obtaining significant benefits through AI, the economy as a whole needs time to absorb a technology of this magnitude. The difference between a technological demonstration of AI and a complete economic transformation based on AI can be several years.<\/p>\n\n\n\n
The Risk of Misjudging the Impact of AI<\/strong><\/h2>\n\n\n\n
Another important issue is that AI tools can generate benefits that are difficult to measure using traditional methods. Productivity is usually calculated by comparing the amount of goods or services produced with the resources used to produce them. However, many AI-related improvements do not easily appear in these measurements because they affect qualitative aspects of the work performed with AI.<\/p>\n\n\n\n
For example, AI can help an employee prepare a document with greater clarity, reduce errors in a financial analysis, or find relevant information more quickly through AI systems. These improvements can have significant value for a company, but they do not always immediately translate into a visible increase in output. In some cases, the main advantage of AI will not be to do more work, but to allow professionals to dedicate more time to higher-value tasks thanks to AI support.<\/p>\n\n\n\n
Additionally, some positive effects of AI may appear indirectly. A company that uses AI to improve customer service may increase user satisfaction, even though this result is not immediately reflected in a traditional productivity metric. Similarly, a research team that uses AI to accelerate discoveries may generate benefits years after the initial implementation of AI technology.<\/p>\n\n\n\n
This difficulty in measuring results can create a false impression that AI is not working. In reality, it is possible that the effects of AI are occurring in areas that current economic evaluation systems do not fully capture. The history of business computing shows that many technologies first transform the way people work and only later become clearly visible in economic indicators, something that could also happen with AI.<\/p>\n\n\n\n
The Role of Training: Learning to Work with AI<\/strong><\/h2>\n\n\n\n
Education will be one of the most important factors in determining the economic impact of AI. An advanced AI tool can offer great possibilities, but its results depend on the people who use AI. Workers will need to develop new skills related to interacting with intelligent AI systems, evaluating AI-generated results, and making decisions based on information produced by machines.<\/p>\n\n\n\n
This does not mean that all professionals must become technical experts or AI programmers. In many cases, it will be more important to understand how to properly use these AI tools within each professional field. A doctor, lawyer, teacher, or designer does not need to create an AI model from scratch, but they do need to know how to take advantage of AI in a responsible and efficient way.<\/p>\n\n\n\n
Training will also be key to avoiding AI-related errors. AI systems can produce incorrect information, misinterpret data, or generate unreliable responses. For this reason, human judgment will continue to be essential for supervising AI results and making important decisions. Productivity will not increase simply because an AI-powered machine works faster, but because humans and AI systems collaborate more efficiently.<\/p>\n\n\n\n
Will AI Take Longer Than Computers to Show Its Benefits?<\/strong><\/h2>\n\n\n\n
Comparing AI with the arrival of computers helps explain why the current revolution may require patience. Computers took approximately a decade and a half to fully reflect their impact on productivity because companies needed time to learn how to use them effectively. AI could follow a similar path due to the complexity of the changes required for AI integration.<\/p>\n\n\n\n
However, there are also important differences. The current speed of AI adoption is much greater thanks to the internet, cloud computing, and the immediate availability of digital tools. Millions of people can experiment with AI from the very beginning, something that did not happen with previous technologies. This could accelerate some AI adaptation processes.<\/p>\n\n\n\n
At the same time, the depth of the change caused by AI may make the transformation more complicated. Computers mainly changed the way information was stored and processed, while AI is changing the way knowledge is produced. This affects more professional areas and requires broader changes in the organization of work with AI.<\/p>\n\n\n\n
The result will likely be a gradual transformation based on AI. Some companies and sectors will experience rapid improvements thanks to AI, while others will need years to fully integrate these AI tools. AI will not be an instant revolution, but rather a continuous process of technological, economic, and social adaptation driven by artificial intelligence.<\/p>\n\n\n\n<\/figure>\n\n\n\n
AI has the potential to become one of the most important technologies in modern history, but the impact of AI will not depend solely on the capabilities of algorithms. The experience of the personal computer demonstrates that major innovations need time to truly transform the economy. AI technology must be accompanied by organizational changes, AI training, and a new way of understanding work with AI systems.<\/p>\n\n\n\n
The greatest challenge will not be creating increasingly intelligent AI systems, but ensuring that people and companies learn to use AI correctly. Productivity will not automatically increase simply by incorporating AI, in the same way that having computers in an office did not guarantee an immediate improvement decades ago. The real change will appear when organizations redesign their processes around the new possibilities offered by AI and take advantage of collaboration between humans and AI.<\/p>\n\n\n\n
Human resistance, the lack of AI training, and the difficulty of measuring the benefits of AI may delay the arrival of a new stage of growth. However, these obstacles do not mean that the AI revolution will not happen; rather, they are part of the normal process of technological adaptation. History shows that the most important innovations need time before revealing their full potential, and AI will follow a similar process.<\/p>\n\n\n\n
AI will likely transform the economy and work, but it will not do so solely because machines become more capable. The transformation driven by AI will occur when people learn to work alongside AI systems and when companies understand that true innovation does not consist of adding a new AI tool, but of building a new way of doing things through technology.<\/p>\n\n\n\n
In this adaptation process, having the right support can make a difference. ITD Consulting helps organizations integrate AI solutions, digital transformation, process optimization, and the development of technology strategies adapted to their objectives. If your company wants to take advantage of the potential of AI in a practical and effective way, you can contact ITD Consulting by writing to <\/strong>info@itdconsulting.com<\/strong><\/a>.<\/strong><\/p>","protected":false},"excerpt":{"rendered":"
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