The 5 Obstacles SMEs Face In Implementing AI

The 5 Obstacles SMEs Face In Implementing AI

In recent years, society has faced several major changes, most of them related to technology. One of the great technological revolutions is Artificial Intelligence (AI), which allows making better decisions about sales, marketing, product or service development and other strategic areas and streamlining the company’s internal processes.

In this context, only large companies seem to be those that are taking advantage of this technology, which seems to be banned from SMEs. The study Artificial Intelligence Indicators in Spanish companies published by the Secretary of State for Digitalization and Artificial Intelligence, together with Red.es and Ontsi, reveals that only 7% of SMEs use AI in their processes, which places them at a clear disadvantage. For this reason, to bring all companies on the same page and improve their strategies and results, we outlines the real obstacles SMEs face when implementing AI in their processes and services.

High Cost Of The Resources Necessary For Its Implementation

It is a technology whose initial cost can be somewhat high, since it is still very young, and many SMEs think twice before investing in it. Technology is advancing by leaps and bounds and each advance and, mainly the cloud, means a drastic reduction in the price that must be paid for this type of technology. Currently, the main technology companies offer artificial intelligence platforms for use by third parties and, according to Ga r tner, in the year 2025 AI will lead the technology investment of companies. The benefits that the use of AI would bring will soon exceed its costs, providing great advantages to the organizations that use it, regardless of its size.

Absence Of The Required Data

Data is the fuel of artificial intelligence and many companies do not have a clear data strategy for obtaining and organizing information before they start experimenting with artificial intelligence and machine learning. It is the implementation of AI without having quality data to learn from. Therefore, when starting or implementing this technology, companies need to collect quality data and plan its use.

Difficulties In Applying AI

Companies lack understanding of what artificial intelligence is and what it is for, as well as the definition and validation of Use Cases, which results in its implementation being considerably delayed. This means that once organizations define a use case for AI, they still face an increasing timeframe – months or even years – to have a model developed for it and scaled to production, with the lack of control of the times to begin to obtain benefits from its use.

In addition, the complexity of the use cases is on an increasing trend, which means that companies do not decide when it comes to investing in AI. That is why it is important to start a learning process and develop internal AI competencies to create a culture of innovation that must be started from the top of the organization, among its leaders, and filtered to the rest of the employees.

Tech Talent Shortage

It is becoming increasingly difficult to find staff who can work and understand the value of AI, as the growing demand for specialized profiles increases the talent gap in this sector. Such is the problem that, faced with this scenario, the Government of Spain, in its National Artificial Intelligence Strategy , proposes to promote the creation of qualified employment, promoting training and education, stimulating Spanish talent and attracting global talent.

Ethical Issues

When talking about this type of technology, certain ethical issues also appear, such as the fear that AI relates to replacing human beings with machines. This causes many companies to continue with the doubt of implementing this technology, but the value of AI operates in the opposite direction, since it generates new opportunities for those companies that are adequately trained in order to be the leaders in their coordination and development, such as and as has happened with other previous revolutions.

such as the steam engine, the first robots on the assembly lines and even the appearance of television, which never did away with the radio. Education and training play a crucial role in preventing long-term unemployment and ensuring a skilled workforce adapted to new needs.

Also Read: Management And Artificial Intelligence: The Future Is Closer

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