the forecasts by 2030 regarding the GDP

According to some forecasts, by 2030, the global spending on artificial intelligence (AI) could reach 3.5% of GDP, driving the digital transformation of companies but encountering obstacles in terms of regulation, security, and resources.

Let’s see all the details below. 

AI becomes crucial: the forecasts by 2030 regarding GDP

In recent years, artificial intelligence (AI) has become increasingly central in business strategies. From a niche technology, it is now a fundamental element to drive competitiveness and innovation in almost all sectors.

The forecasts of the recent IDC survey indicate that global spending on AI, including the supply chain, could represent as much as 3.5% of the world’s GDP by 2030.

This trend reflects the growing importance of AI not only as a growth engine, but also as a tool to tackle the challenges of the global market.

Not by chance, the pressure to innovate and adapt to technological change has driven many CEOs to intensify investments in AI. 

Many companies are indeed allocating dedicated budgets to artificial intelligence projects, recognizing the need to evolve to meet market demands.

The corporate initiatives regarding AI are not limited only to growth, but also aim to ensure a responsible implementation. 

More and more CEOs emphasize the ethical use of AI, highlighting aspects such as trust in systems, transparency in processes, and sustainability. 

This focus on “technological responsibility” is seen as a key element to maintain the trust of customers and stakeholders, who look with apprehension at the rischi associated with an unregulated use of AI.

Security and obstacles to digitalization: challenges for businesses

The integration of AI, however, also involves the increase in expenses dedicated to security, risk management, and compliance, issues that are becoming increasingly relevant for companies. 

C-level executives are therefore investing in security technologies and dedicating resources to cyber security to protect both company data and customer data. 

However, only a minority of businesses are fully digitalized. Although 41% claim to be “primarily digital,” in reality only 11% have achieved complete digitalization.

This discrepancy is attributable to various factors. On one hand, many companies are facing difficulties in the implementation of advanced digital technologies. 

On the other hand, the use of data and the automation of processes are not yet as widespread as one would expect. 

Technologies are not always up to expectations, and automation remains limited, hindering the potential of AI in terms of operational efficiency and competitiveness.

The increase in investments in artificial intelligence is also generating new macroeconomic and regulatory issues.

At a global level, governments and institutions are addressing the need to regulate AI, creating guidelines and regulations that ensure data protection and privacy. 

This regulation varies significantly from one country to another, creating a mosaic of rules that global companies must navigate carefully.

In addition to regulatory issues, the increase in demand for AI raises problems of sourcing raw materials. 

IDC predicts that the amount of data in the world will triple by 2028, and this increase will require critical resources such as neodymium to support the production of hardware and technological infrastructure. 

The shortage of such materials could limit the expansion of AI, slowing down digitalization projects and causing problems in the global supply chain. 

The challenge will therefore be to balance the increase in demand with sustainability, reducing the environmental impact and ensuring resources to support the expansion.

The future of AI: opportunities and risks to manage

The future of artificial intelligence in companies presents a landscape of opportunities unprecedented, but also challenges that require particular attention. 

AI could effectively transform the productivity and efficiency of key sectors, from industry to healthcare, from finance to logistics. 

However, to fully exploit this potential, it will be necessary to overcome the obstacles to digitalization and ensure that AI is adopted in a responsible and sustainable way.

A balanced and responsible approach requires companies to continue investing not only in technological innovation but also in the training and digital skills of their employees, as well as in security. 

An important role will be played by collaborations between sectors, governments, and institutions. These could facilitate the development of common standards and regulations that guide AI towards an ethical and sustainable use.