Artificial Intelligence Race Boosts Paint and Industrial Coating Market
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Artificial Intelligence Race Boosts Paint and Industrial Coating Market

The growing need to build robust data centers to support artificial intelligence (AI) is stimulating an unconventional market segment: that of industrial paints and coatings. As giants like Microsoft, Google, and Amazon expand their computing infrastructures, protection material producers are observing an increase in demand, even if the product is predominantly gray.

PPG, headquartered in Pittsburgh (USA), predicts that sales of its paints specifically for data centers will triple this year compared to the previous period. This expectation significantly surpasses the company's overall growth, whose total sales reached US$ 4.5 billion (approximately R$ 24 billion) in the last quarter, representing a 7% increase.

Jenn Solcz, Vice President of the Protective and Marine Coatings division of PPG in the Americas, commented that she had never witnessed such expressive growth. PPG identified this opportunity about three years ago, after the launch of ChatGPT and the increased disclosure of new data centers and chip factories.

As a result, contractors, metal structure manufacturers, and equipment suppliers have begun competing for projects related to AI infrastructure expansion. The company implemented dedicated teams for the technology sector and started collaborations with architects, engineers, and construction companies even before the start of works, aiming to include its products in approved material lists from the initial project phases.

In April, the company launched a set of solutions focused on data centers. This offering includes coatings to protect steel structures against fire, primers to prevent corrosion, floors designed to reduce static electricity risks, and materials intended to prevent electrical interference.

Additionally, PPG supplies coatings for more than 75 types of components used in these facilities, including security camera housings and cooling equipment. The company reports that its products have already been applied in data centers located in Brazil and China. However, more than half of the commercial opportunities are concentrated in the United States, which hosts about 5,500 such installations, according to the Stanford University (USA) Artificial Intelligence Index report.

The sector also benefits rivals. Sherwin-Williams, PPG's main competitor, announced that its products are used in various parts of data centers, from metal beams to the structures housing servers. In July, Heidi Petz, the company's CEO, stated that sales of the protective and marine coatings division grew by double digits compared to the previous year, driven, among other factors, by the construction of these facilities.

Despite the complexity of the products, the visual aspect is usually subtle, as most coatings are sold in various shades of gray, applied over concrete and steel that have similar tones. This occurs because data centers are built primarily to house machinery, not to receive people, making internal aesthetics rarely a priority for owners, architects, and engineers.

Matthew Giddings, a specialist at the commercial real estate firm JLL, which deals with data center management, estimates that coatings can cost between US$ 3 million and US$ 8 million (equivalent to R$ 16 million to R$ 43 million) in a single building. Although this amount constitutes only a fraction of the total building cost, it helps measure the market generated by the expansion of AI infrastructure.

There are exceptions to the dominance of gray: chilled water piping may receive blue paint, while pipes connected to fire fighting systems are usually red, facilitating identification by maintenance teams. Furthermore, in response to pressure from local communities for developments with a less industrial appearance, some companies have begun incorporating colors on facades.

PPG, established in 1883 as Pittsburgh Plate Glass Company, originated as a glass manufacturer. Over time, it evolved to become one of the largest global coating corporations, serving sectors such as automotive, aerospace, and packaging. The company prefers to refer to its items as 'coatings' rather than merely paints, as its solutions can integrate a primer for adhesion to steel, a functional protective layer, and a final finish.

However, despite the optimistic prospects, the market advance faces obstacles. PPG mentioned that some data center projects are delayed awaiting power access. The scarcity of transformers and other electrical equipment is also extending construction schedules. Added to this is the challenge posed by resistance from local communities to the installation of new developments.

PPG assesses that coatings for data centers still represent a modest share of its sales, but maintains the expectation that this niche will grow much faster than other infrastructure segments. Thus, the expansion of AI not only drives model developers or chip manufacturers but also generates opportunities for suppliers of materials and components vital for the construction and operation of the vast buildings that sustain this technology.

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Using AI in Resumes and Candidate Screening: The Problem of Human Factor in the Hiring Process
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Using AI in Resumes and Candidate Screening: The Problem of Human Factor in the Hiring Process

Job applicants spend time improving their resumes, tailoring cover letters to job requirements, and matching their skills with company needs. After submitting documents, there is often a period of silence, after which they may try again or use artificial intelligence to enhance their application.

On the other hand, recruiters can use AI to analyze hundreds of resumes. Since candidates strive to stand out, and companies want to quickly find a suitable person, the use of the same technology is growing both in the application process and in hiring, turning this procedure into a machine versus machine competition.

AI is capable of simplifying the job search for applicants by helping write resumes, prepare applications, and practice for interviews. However, a rapid increase in the number of prepared applications does not guarantee an increase in their quality.

According to a September 2025 report, one applicant sent 87 applications in a month using AI. Errors were found in these documents, such as incorrect company and job titles. The report warns that AI-generated materials without verification can harm candidates.

When applicants apply for numerous vacancies, the volume of incoming applications for companies increases. Although automated screening seems useful for companies, the question arises as to which candidate will be paid attention to in this process.

Monitoring systems allow companies to organize resumes and find candidates whose experience matches the job requirements. Nevertheless, if the candidate's necessary competencies are described in words that the system does not recognize, they may be ignored.

A October 2025 report details how monitoring system tools match resumes with job requirements. The risk is not limited to missing keywords.

In May 2024, concern was raised that qualified candidates might be rejected by automated hiring systems, with the report emphasizing the need for human oversight.

If the rejection decision is made solely by software, a suitable candidate will never reach the recruiter, and the applicant will not know the reason for rejection.

This pressure is not limited to India. A BBC report mentioned a 22-year-old geography graduate from Medstone, UK. Before getting a restaurant manager position, he submitted over 200 applications. He noted that AI helped in processing applications, but the entire process was exhausting.

Business Insider reported that Google integrated AI tools, including Gemini, into some software development interviews. During these interviews, candidates' ability to understand code and work with AI was tested.

These examples show that applicants are using AI for job searching, while companies expect them to demonstrate AI-related skills. This raises the question: will the technology make the hiring process more efficient or add another level of competition?

Even after submitting an application, applicants may wait without knowing whether their application is being considered. According to a September 2026 report based on the Indeed hiring confidence index, 29% of Indian applicants reported that lack of response after applying is their biggest problem.

The study involved 1073 applicants and 735 employers from India. Simply speeding up screening will not solve this problem; candidates also need clear information and the ability to track the status of their application during the hiring process.

The task for applicants is not to send template applications when using AI and not to claim non-existent skills. The task for companies is not to consider recommendations from fully automated technologies as the final solution.

AI can help candidates better present their experience, and recruiters can manage workload. However, an attractive resume and quick screening do not guarantee that a suitable candidate matches the right job.

For a person waiting for a response after applying, the most useful change will not be a new tool to speed up applications, but a more transparent and impartial hiring process that can identify the person behind the resume.

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