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Artificial Intelligence at Brazilian companies: the importance of experimentation before implementation

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The use of artificial intelligence at Brazilian companies may appear to be  challenging, but it can be achieved. The effort pays off. The enormous quantity of data available and the advanced computing capacity allow precise analyses and more agile decision making.

But there are still few companies in Brazil that have taken the right steps towards this solution. Most do not even understand how it can be applied to their reality.

No more time should be lost with mistaken notions. Your business can benefit from artificial intelligence, as long as you understand the main challenges and risks involved in its implementation.

A tip: experimentation is a key step in facilitating the process and lowering costs.

Risks and challenges for implementing an AI project

Many of the main challenges for implementation of Artificial Intelligence solutions at Brazilian companies are related to the data needed for the system to achieve its objective.

We will highlight a few important factors.

Human accompaniment

AI systems are complex and involve different technologies and methodologies. Although computing advances allow the creation of increasingly automated systems, the fact is that in most cases artificial intelligence requires care in the preparation and analysis of data under the supervision of specialists.

This supervision guarantees that the training of the artificial intelligence algorithms is a well-controlled experiment, which allows constant correction of the direction and definition of new strategies for your business.

Unorganized and non-standardized data

The organization, labeling and structuring of data is essential to the implantation of AI at a company. Many corporations still do not have the data needed, or when they do, it is not cataloged as it should be.

Without identification, it is not possible to obtain information or make decisions based on tidbits of data that are out of context. Proper organization is a minimum requirement for artificial intelligence solutions to be able perform their function.

If an artificial intelligence system reads the information incorrectly, it can create erroneous standards and interpret the data improperly, which creates disorganization in the entire chain.  

Organization is only the first step towards the implantation of artificial intelligence at Brazilian companies. Another step that must be completed is the standardization of collected data so that they can be shared and reused without problems.

According to the study “State of AI in the Enterprise”, conducted by Deloitte, 16% of corporate leaders indicate problems related to data (privacy, access, integration etc.) as their main challenge for implantation of AI.

Read more: Intelligence of data: measurement and calibration for decision making

 

Insufficient competence

The implementation of artificial intelligence involves a series of technical challenges that many companies are not prepared to face. One of the reasons for this is that in most cases, companies still do not have the professionals needed and creating a staff with this expertise from scratch can be costly. In certain cases, the company culture impedes understanding, which an outside perspective can help to correct.

The truth is, however, that not all companies are able to conduct these processes internally, particularly due to the lack of knowledge and competence to work with the technology.

Integration

In addition to the integrity and quality of data, another essential challenge faced by companies is with integrating it with systems that they already use, such as CRM and ERP, so that they can finally gain access to all the information they need.

Once companies have a solid base of data and all the integrations are made, AI systems can be used to improve company processes.

Lack of knowledge

The artificial intelligence market is developing rapidly, particularly in emerging countries such as Brazil. Therefore, it is natural that machines are also changing and are therefore not prepared to respond to any demand. Moreover, it is not enough to generate data, it is necessary to understand it.

Lack of planning

Artificial intelligence has become a fashionable term. There are many media reports and publications on the internet that emphasize the importance of this technology for the future of companies and their survival in the market.

However, the implantation of artificial intelligence systems at Brazilian companies depends on a series of factors and characteristics specific to each business. If there is no planning about the objectives that the company intends to attain with the AI solutions, and even more importantly about the data that it needs to collect and generate, the investment does not make sense and can fail.

Therefore, companies must recognize that it is essential to understand their own needs and analyze how AI can benefit their business. This involves conducting detailed market research and evaluating the pros and cons of the technology.

It is also important to invest in research and development to generate data that are relevant to the business and organize the structure needed to improve the technology and adapt it to the goals of the business.

The risks that accompany artificial intelligence must also be considered. After all, since its use is relatively new in the business world, it is natural that some aspects are still not clear to most people. For this reason, let us examine some of the risks involved in the implantation of artificial intelligence at Brazilian companies.

Problems with data

To have an idea, the Deloitte study indicates that 16% of the company leaders indicate they are insecure about making decisions based on data. One of the greatest risks in the use of AI is the large volume of unorganized data that is generated by sources like the internet and social media. Thus, if the system is not well prepared, it becomes easy to fall into traps that lead to improper handling of the data that feed them.

Security breaches

The study also shows that 23% of corporate leaders are concerned with security and vulnerability problems that AI systems can present. It is inevitable that intelligent and connected systems may have security breaches. Among the most common targets are companies in the finance and health sectors.

Nevertheless, over time there has been a refinement in virtual attacks and a constant evolution of the security mechanisms against cybernetic attacks provided by AI solutions.

Unsuitable Models

As we mentioned, machines need to be taught so that they can generate information that is relevant to the business. To do so, one of the greatest risks of artificial intelligence at Brazilian companies is directly related to one of the greatest challenges: the creation of the models that feed the systems.

If the models have problems, the results can be partial or imprecise. For this reason, it is important to have people trained in the creation and implantation of these solutions.

Read more: Inovação corporativa: por que a inovação é importante para sua empresa

Why you should experiment before implementation

It is thus clear that the implementation of artificial intelligence at Brazilian companies requires a considerable investment.

Moreover, good planning is needed to understand what AI can do for a company and how it can use already available data to make the best use of the solution.

Experimentation is therefore an essential step. In this phase, by using prototyping, a company can identify and test the opportunities for application of artificial intelligence techniques and understand their complete potential.

With lower investment risk, companies can test solutions generated from their own ideas and applicable to the situation in which it is inserted. This allows determining how a company responds to its main challenges and how it can avoid the main risks faced in the implementation of an AI project.

Once an experiment is validated, the company can integrate the solutions that it explored to its processes. In this sense, the knowledge acquired during the experimentation phase helps in the creation of a model that is easily replicable in other spheres of innovation at the company. 

Read more: Improvement of industrial processes to improve competitiveness of a business

Are you interested in innovation but not sure where to begin? Contact the CERTI Foundation and see how we can help!

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