*By Eronides Junior
The report "State of AI in 2024” pointed out that 72% of companies already adopt at least one solution Artificial intelligence (AI) in their processes. The number is impressive, but it should also be a warning: amid the euphoria of adopting these tools, many organizations move forward without being clear about what they are actually implementing — and, most importantly, whether they are prepared for it. To give you an idea, the research “Unlocking Enterprise AI: Opportunities and Strategies” revealed that only 22% of companies believe that their IT infrastructure is prepared to support these applications.
In this scenario, many companies, feeling the pressure to position themselves in the face of the new digital era, have sought simplified AI automation, created with just a few clicks via open source codes located on the internet. However, although this front has given autonomy to business areas to accelerate their productivity, it is essential not to make the mistake of ignoring a solid infrastructure, capable of providing governance and security for the data input into the solutions.
The middle market and innovation
This market movement occurs especially with a group that moves a large part of the economy: medium-sized companies, which are between giants and startups. With lean and specialized teams, these organizations have already overcome the initial stage of maturity, but they still face structural limitations that can impact operations.
This is because it is common to find IT teams focused on operational demands, such as legacy system maintenance, technical support and problem-solving. Innovation, although desired, ends up being constantly postponed. The challenge then arises: how to adopt AI, if there is a lack of priority and structure to make this movement viable?
The result is the hasty implementation of technological solutions on fragile foundations. This strategic error is common and, unfortunately, not only wastes resources, but can also undermine confidence in future projects.
The impact of data governance
Among the main obstacles to the effective adoption of AI is the accumulation of disintegrated technologies and non-standard data. In this context, data governance ceases to be a good practice and becomes a non-negotiable prerequisite.
Standardizing nomenclature, ensuring the integrity of information, defining clear access criteria and guaranteeing data quality are fundamental steps. This basis is necessary for models and technological solutions to deliver reliable results. Without this foundation, innovation becomes unstable, subject to errors, rework and wrong decisions.
IT as a strategic area
To transform AI into a competitive advantage, the time has come for the IT area to stop being just technical support and position itself as a leader in implementing solutions, testing tools and defining guidelines, building a mature process for advancing the use of technology in companies.
To make this possible, specialized consultancies and technological partners play an essential role in diagnosing systems, structuring data and building infrastructures suited to the reality of each company.
An external, experienced and impartial perspective helps to see what is invisible to those immersed in the day-to-day operations. It is this support that safely accelerates the path towards the conscious adoption of Artificial Intelligence.
More than choosing the tool of the moment, it is necessary to structure the terrain in which this innovation will develop. For companies that want to adopt AI in a strategic and lasting way, overcoming challenges consciously, the real question is not “which technology to use”, but rather “how to start the right way”. A critical and structured look inside is what defines who is truly ready to evolve digitally.
*Eronider Junior is Chief Revenue Officer at SoftwareOne in Brazil, a global provider and leader in end-to-end solutions for software and cloud technology.
Notice: The opinion presented in this article is the responsibility of its author and not of ABES - Brazilian Association of Software Companies
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