Technology label

Global real estate investment
Facu
3 August, 2026

Data centers capture a growing share of global real estate investment

The expansion of artificial intelligence, the growth of data processing and the demand for digital infrastructure drive a new stage for the real estate market.

Data centers concentrate capital, change location criteria and generate opportunities for developers, investors and emerging markets.

Digital infrastructure is at the heart of the investment agenda

The real estate market is undergoing a transformation driven by the digital economy. The expansion of generative artificial intelligence, the growth of cloud computing and the multiplication of data-based applications increase the need for global technological infrastructure.

In this context, data centers are consolidated as one of the most demanded assets by institutional investors, infrastructure funds and specialized developers. Several international reports from PwC, Urban Land Institute and large investment firms place these assets among the main opportunities in the real estate sector for the coming years.

The demand comes from technology companies, cloud operators, streaming platforms, telecommunications companies and organizations that require increasing processing and storage capabilities.

The growth of digital traffic makes data centers an essential component for the functioning of the contemporary economy.

Energy availability becomes a strategic variable

The location of a real estate asset remains relevant, although the selection criteria evolve rapidly.

The ability to access reliable, scalable and competitive energy is of crucial importance for the development of new projects.

Large operators seek regions that can ensure stable power supply, high-capacity connectivity and favourable regulatory conditions for long-term investments.

This scenario drives a new logic of soil recovery. Land that historically had limited appeal for traditional developments begins to attract interest when they offer adequate energy infrastructure.

Urban and energy planning is beginning to have a direct impact on the real estate competitiveness of cities and regions.

Capital flows migrate to assets linked to the digital economy

Global real estate markets go through a more rigorous selection stage by investors.

The high interest rates in recent years have led to a thorough review of the criteria for capital allocation. The funds seek assets with structural demand, long-term contracts and prospects for sustained growth.

Data centers have much of these characteristics.

The expansion of artificial intelligence expands the need for computer capacity, as companies accelerate the digitization of processes, services and operations.

This dynamic generates a constant flow of demand that strengthens the financial attractiveness of these developments to other traditional market segments.

The consequence is visible: an increasing share of global real estate capital is directed towards technological infrastructure.

Latin America begins to win the role of the regional map

The region has conditions that begin to attract the attention of international operators.

Brazil, Mexico, Chile and Colombia concentrate much of the projects announced in recent years. The combination of digital growth, expansion of the consumption of technological services and the need for regional infrastructure drives new investments.

The Latin American market still has levels of development below those observed in the United States, Europe and Asia, which expands the long-term growth potential.

Cities that manage to strengthen their energy infrastructure, improve connectivity and provide predictable regulatory frameworks can capture a significant part of this expansion process.

For real estate developers, funds and infrastructure-related actors, the evolution of this segment represents a relevant opportunity to diversify portfolios and access markets with strong growth potential.

New challenges for developers and real estate investors

The development of data centers requires different capacities than conventional real estate assets.

The risk assessment incorporates energy, technological, regulatory and operational variables. Investment processes require a deeper understanding of digital infrastructure and the technological trends that drive demand.

The relationship between real estate, energy and technology is becoming increasingly integrated.

This convergence expands the need for strategic planning to identify competitive locations, understand demand developments and prioritize long-term vision investment opportunities.

Decisions made over the next few years will have a direct impact on the ability to capture value in one of the most growing segments within the global real estate market.

The technological infrastructure drives a new stage for the real estate

Data centers represent one of the most visible expressions of the convergence between digital economy and real estate investment.

The expansion of artificial intelligence, exponential data growth and the need for critical infrastructure strengthen the attractiveness of these assets for institutional investors and specialized developers.

The evolution of the sector opens up new opportunities for markets that can provide energy, connectivity and stability for large-scale projects.

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Real Estate Tokenization
Facu
3 June, 2026

The digitization of the real estate accelerates the adoption of IA, tokenization and data-based management

The technological transformation of the real estate is going through a new stage of maturity.

The sector is beginning to incorporate artificial intelligence, automation and predictive analysis as central tools for improving operational efficiency, marketing and decision-making.

The growth of the PropTech ecosystem in Latin America drives investments in smart management platforms, digital investment models and market analysis tools. Technological developments change the competitive logic of the sector and increase the importance of analytical capacity over real estate assets.

Recent reports from international consultants and industry-related organizations show an acceleration in the adoption of data-based solutions, especially in corporate, logistical, multi-family and commercial segments.

Artificial intelligence gains space in valuation, pricing and demand analysis

Artificial intelligence begins to play an increasingly relevant role in the operational structure of the real estate. Industry companies use predictive models to analyse demand behaviour, absorption speed, price evolution and vacuum risks.

The availability of market data, combined with machine learning tools, makes it possible to build more accurate business projections and improve the segmentation of buyers and investors.

The use of IA also impacts on:

  • Automation of commercial processes.
  • Generation of qualified leaders.
  • Optimization of campaigns.
  • User behavior analysis.
  • Asset management.

The commercial response speed begins to become a central competitive variable for developers, brokers and real estate operators.

The market also incorporates dynamic pricing solutions to adjust income and marketing values according to demand, location, timing and rotation.

This logic already has a strong presence in hospital and multifamily in the United States and Europe, and it begins to expand to Latin American markets with more operational professionalism.

Tokenization drives new real estate investment models

The tokenization of real estate assets gains visibility as a mechanism to expand access to investment and generate greater liquidity on traditionally illiquid assets.

The advance of lockchain and fractional investment platforms enables new schemes of participation on commercial properties, residential income and specific developments.

Interest in these models is particularly growing in:

  • Young investors.
  • Digital profiles.
  • Markets with access to credit restrictions.
  • Regional structures for diversified investment.

Tokenization also begins to be observed by funds and institutional investors as a tool for expanding capital base and improving placement speed.

Regulatory development still has significant differences between countries. However, the financial and technological ecosystem maintains a sustained expansion trend.

The evolution of the model will depend on:

  • Legal security.
  • Financial regulation.
  • Asset traceability.
  • Operational transparency.
  • Institutional trust.

The data becomes a strategic asset of the real estate business

The digitization of the sector increases the strategic value of operational and commercial data.

Real estate companies start using integrated dashboards to monitor:

  • Behavior of demand.
  • Commercial conversion.
  • Procurement costs.
  • Occupation levels.
  • Profitability by segment.
  • Asset performance.

The ability to interpret information in real time begins to influence expansion, pricing, investment and portfolio development decisions.

This development also affects the relationship between commercial, marketing and operation. The integration of areas gains relevance in structures that seek predictability and sustained growth.

The market is beginning to differentiate between operators with consolidated analytical capacity and structures with low technological integration.

Smart assets raise competitive pressure on developers and operators

The incorporation of technology into real estate assets also advances rapidly.

Corporate buildings, industrial parks and premium developments include:

  • IoT sensors.
  • Intelligent energy consumption systems.
  • Operational monitoring.
  • Maintenance automation.
  • Experience platforms for users and tenants.

Energy efficiency and smart management capacity begin to influence recovery, operational costs and attractiveness for institutional investors.

The ESG criteria also gain weight in asset financing and assessment decisions, especially in international markets.

The ability to build technologically prepared assets becomes a positioning factor for developers and funds.

Latin America accelerates its PropTech ecosystem

The Latin American PropTech ecosystem maintains a process of expansion driven by technological investment, urban growth and operational professionalism.

Brazil and Mexico concentrate much of the regional activity, although there are also relevant developments in Argentina, Colombia and Chile.

The region presents opportunities related to:

  • Digitization of fragmented processes.
  • Low historical technological penetration.
  • Growth of the multifamily segment.
  • Logistics expansion.
  • The need for greater trade efficiency.

Technological progress also changes the competitive dynamics between traditional actors and new digital operators.

Companies with the greatest technological adaptation capacity begin to capture advantages in:

  • Trade speed.
  • Quality of experience.
  • Operational efficiency.
  • Access to capital.
  • Demand construction.

The trade structure is beginning to depend on analytical capacity and predictability

The digital transformation of the real estate changes the business management logic of the sector.

Growth is increasingly dependent on:

  • Data quality.
  • Commercial traceability.
  • Process automation.
  • portfolio segmentation.
  • Technological integration.
  • Predictive capacity.

Operational professionalism is of relevance to more competitive markets and more demanding financial cycles.

The ability to build commercial predictability becomes a strategic differential for developers, operators and real estate funds.

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Cybersecurity and technology
Facu
22 May, 2026

Cybersecurity becomes a structural axis of digital business

The expansion of artificial intelligence, automation and connected platforms is changing the risk structure of technology companies and all digital production sectors.

Cybersecurity began to be central to strategic decisions linked to operational continuity, corporate reputation and financial predictability.

The global market is going through a stage where digitization advances on critical operations, industrial infrastructure, commercial management and supply chains. This process extends the area of exposure to computer attacks, data theft, operational interruptions and systemic vulnerabilities.

The evolution of the digital business is driving a change of criterion in directories and executive teams: computer security went from a technical function to a structural variable of the business.

Automation Expands Business Operational Risk

The accelerated incorporation of artificial intelligence and automation generated a massive expansion of connected devices, platforms and processes. This dynamic increases access points and operational complexity.

Attacks on logistics chains, financial platforms, industrial systems and SaaS companies began to show a growing economic impact on income, reputation and operational continuity.

According to recent reports from Deloitte and international agencies specialized in cybersecurity, threats related to generative IA, Ransomware and automated attacks are increasing speed and sophistication in global markets.

The situation is becoming more sensitive in Latin America, where many companies maintain fragmented technological structures, low level of integration and reactive security policies.

The exposure increases especially in companies that grew rapidly during digitization and commercial expansion processes without consolidating a robust protection and monitoring architecture.

The economic cost of a digital interruption gains scale

The growing dependence on digital platforms is raising the financial impact of any operational interruption.

A fall in infrastructure, an attack on sensitive data or a vulnerability in critical systems can simultaneously affect:

  • Facturing.
  • Logistics.
  • Customer service.
  • Corporate reputation.
  • Regulatory compliance.
  • Relationship with investors and partners.

The problem ceased to focus only on technical recovery. The current impact involves a deterioration of confidence, loss of contracts and increased operating cost.

The sectors with distributed operations and high digitization show greater sensitivity:

  • Logistics.
  • Energy.
  • Retail.
  • Financial services.
  • Cheers.
  • Industrial manufacturing.
  • Technology platforms B2B.

In these markets, operational continuity became part of the competitive positioning.

Artificial intelligence accelerates threat sophistication

The evolution of generative artificial intelligence is also changing the global cybersecurity scenario.

The new models make it possible to automate attacks, develop more precise phishing campaigns and increase the capacity to escape traditional protection systems.

In parallel, companies are using IA for predictive monitoring, early threat detection and automated vulnerability analysis.

The technological market is beginning to consolidate a new competitive career linked to self-security and real-time response capacity.

Large global technology companies are increasing investment in security infrastructure, cloud protection platforms and IA-driven defence systems. The strategic priority is focused on operational resilience and protection of critical digital assets.

Regulation begins to raise business standards

Regulatory pressure also began to intensify.

The United States, Europe and different Asian markets are making progress in regulatory frameworks linked to data protection, critical infrastructure and corporate responsibility for digital incidents.

Regulatory requirements begin to impact on:

  • Corporate reporting.
  • Technology audits.
  • Data management.
  • Operational traceability.
  • Relationship with technology providers.

This dynamic creates additional pressure on medium-sized enterprises and organizations with decentralized technological processes.

Cybersecurity is beginning to be integrated into decisions related to compliance, financing, corporate insurance and investment risk assessment.

Digital predictability becomes a competitive advantage

Technology companies and digitalization-intensive sectors face a new competitive demand: to sustain resilient and predictable operations in high digital exposure environments.

The ability to anticipate risks, monitor vulnerabilities and respond quickly to incidents begins to influence:

  • Profitability.
  • Trade stability.
  • Reputation.
  • Expansion capacity.
  • Market value.

The market begins to award organizations with integrated technological structures, clear protocols and strategic digital risk management capacity.

The evolution of the sector shows a growing convergence between technology, operational continuity and corporate strategy.

Cybersecurity is now directly associated with business sustainability and long-term competitiveness.

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Facu
18 May, 2026

Logistics automation moves towards self-contained models with operational IA

The global logistics goes through an accelerated transformation phase driven by artificial intelligence, automation and predictive analysis.

The sector incorporates systems that can make real-time operational decisions, optimize dynamically routes, anticipate interruptions and coordinate operations with less human intervention.

Technological developments have an impact on costs, speed, traceability and predictability. The result is a new competitive logic where data processing capacity begins to define operational efficiency and commercial profitability.

In Latin America, this trend gains relevance by the growth of e-commerce, pressure on margins and the need to scale operations with more efficient structures. Logistic companies face a scenario where operational automation begins to become a strategic factor to sustain competitiveness.

Artificial intelligence begins to intervene in critical operational decisions

For years, logistics digitization was focused on visibility, monitoring and administrative management. The new technology cycle advances on operational decision-making capacity.

The IA-driven platforms are already involved in:

  • Dynamic allocation of loads.
  • Automatic route optimization.
  • Delivery planning.
  • Demand prediction.
  • Inventory management.
  • Predictive maintenance.
  • Analysis of operating times.
  • Real-time detour control.

The economic impact is relevant. Companies manage to reduce unproductive kilometers, improve asset use and reduce operational errors.

According to McKinsey and Deloitte reports, advanced automation allows for reduced logistical costs and improved response times in complex supply chains. The trend is accelerating in industries with high pressure on availability and compliance.

The incorporation of operational IA also changes the competitive profile of the sector. Companies with the capacity to integrate data, automate processes and build operational intelligence gain greater capacity for expansion and scalability.

Logistics centres are moving towards autonomous operations

Automation is already central to deposits, logistics hubs and distribution centres.

Collaborative robotics, automated picking systems, internal self-contained vehicles and smart management platforms begin to integrate into large-volume operations.

Amazon, DHL, Maersk and other major global operators increased investments in automation of logistics centres to improve productivity and reduce operational dependence on repetitive tasks.

The trend is gradually moving to medium-sized enterprises through SaaS solutions, applied artificial intelligence and more accessible modular tools.

Operational change creates new priorities:

  • Technological integration between areas.
  • Total traceability of operations.
  • System interoperability.
  • Predictive analysis capacity.
  • Information processing speed.

Logistics efficiency takes on an ever-deeper technological dimension.

The pressure on margins accelerates investment in automation

The global economic context increases operational costs, wage pressure, compliance requirements and speed demand.

This combination requires logistics operators to seek structural productivity improvements.

Automation appears as an operational stabilization and margin protection tool.

In highly competitive markets, small improvements in delivery times, fleet use or storage efficiency generate direct impact on profitability.

Competitive pressure also accelerates changes in the expectations of corporate customers.

Companies demand:

  • More precision.
  • Real-time information.
  • Digital integration capacity.
  • Proper compliance.
  • Full traceability.
  • Operational adaptation capacity.

The commercial response speed begins to depend directly on the technological maturity of each operator.

Latin America faces structural challenges to scale automation

The region presents significant opportunities for the development of smart logistics, although it still faces structural constraints.

The main challenges include:

  • Low technological integration.
  • Operational fragmentation.
  • Inequitable infrastructure.
  • Manual process unit.
  • Investment difficulties.
  • Lack of specialized technical profiles.

However, different market segments show acceleration in technological adoption, especially in:

  • Retail.
  • E-commerce.
  • Agroindustry.
  • Mass consumption.
  • Last-mile operators.
  • Industrial logistics.

Brazil and Mexico lead much of the regional investments in logistics automation, driven by operational volume and growth of digital trade.

Argentina begins to record advances in traceability, applied analytical and partial automation in companies linked to distribution, warehousing and logistics for industry.

Regional developments remain central: automation is no longer an exclusively technological project and is becoming part of the business growth strategy.

Data availability becomes a competitive asset

The growth of automated operations increases the relevance of data within the logistics.

Each operational movement generates information about:

  • Times.
  • Productivity.
  • Costs.
  • Behavior of demand.
  • Route efficiency.
  • Service levels.
  • Use of assets.

Companies capable of transforming such data into operational decisions acquire concrete advantages on efficiency and predictability.

The quality of information begins to directly influence:

  • Profitability.
  • Trade speed.
  • Planning.
  • Regional expansion.
  • Customer experience.
  • Negotiating capacity.

The logistics sector is moving towards models where operational intelligence and analytical capacity are part of the competitive core.

Automation changes the commercial structure of the sector

The technological transformation also impacts on positioning and commercial strategy.

Logistic operators with higher technological capacity begin to compete for added value, traceability and integration capacity.

This change changes traditional logic based mainly on price and volume.

Companies that develop solutions with operational intelligence are able to build stronger business proposals for industries that demand predictability and control.

In parallel, automation increases the need for coordination between commercial, operational and financial areas.

Sustainable growth is increasingly dependent on:

  • Processes ordered.
  • Consistent indicators.
  • Cost-effective segmentation.
  • Technological integration.
  • Scalability.

Logistics enters a stage where operational efficiency, technology and business strategy function as interdependent variables.

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IA - Enterprise infrastructure
Vipzus
6 March, 2026

Generative artificial intelligence: from technological experiment to business infrastructure

The new stage of artificial intelligence in companies.

In recent months, the artificial, generative intelligence has begun to be consolidated as a key technology infrastructure within organisations.

What was initially perceived as an experimental tool to generate texts, images or code is evolving into a platform that allows automate processes, optimize decisions and redesign operating models.

Companies in multiple sectors are incorporating these technologies in areas such as customer care, marketing, data analysis and software development. The result is a gradual transformation of the way organizations produce, manage information and make decisions.

Recent reports from McKinsey and Deloitte indicate that generative artificial intelligence could generate billions of dollars in global economic value in the next decade, promoting a new phase of digital transformation.

From pilot projects to operational integration

In the first stage, many companies adopted the artificial, generative intelligence through internal experiments and tests. Technology teams explored their capacities through pilot projects aimed at improving productivity or reducing costs in specific tasks.

However, recent market developments show a significant change: technology is beginning to be integrated into Central operating processes.

The main applications include:

  • Automation of customer care through intelligent assistants.
  • Content generation and marketing campaign optimization.
  • Development of software assisted by artificial intelligence.
  • Advanced data analysis for decision-making.
  • Optimization of internal processes.

This transition marks the step of technological experimentation towards a model in which artificial intelligence works as a cross-border digital infrastructure.

A global technological career

The advance of artificial intelligence is also driving a international technological competence.

The United States maintains a dominant position thanks to its technological ecosystem and the investment of large companies in artificial intelligence infrastructure. At the same time, China and the European Union have accelerated their investments in data centres, semiconductors and development of advanced models.

Global competition is concentrated in three key areas:

  • Development of large-scale artificial intelligence models.
  • Advanced computing infrastructure.
  • Access to large volumes of data.

In this context, artificial intelligence is becoming a strategic assets for both companies and national economies.

Regulation and technology governance

As artificial intelligence is integrated into business processes, the interest of regulators in establishing policy frameworks is also growing.

The European Union has made progress in developing the AI Act, one of the first regulatory frameworks to establish standards of transparency, safety and risk control in artificial intelligence systems.

Other countries are evaluating similar regulations, especially in areas related to:

  • Use of data.
  • Algoritmic sessions.
  • Responsibility for automated decisions.
  • Labour impact of automation.

For companies, regulatory development becomes a key factor in defining technology adoption strategies.

Strategic implications for enterprises

Generative artificial intelligence offers relevant opportunities to improve productivity and competitiveness, but its impact will depend to a large extent on how companies integrate technology into their business models.

The organizations that can capture the most value will be those that can combine technological innovation with organizational transformation.

This involves developing new capacities in:

  • Data analysis.
  • Process automation.
  • Technology management.
  • Specialized talent training.

At the same time, companies should manage risks associated with the adoption of artificial intelligence, including technology dependence, data security and regulatory compliance.

Perspective for Latin America

In Latin America, the adoption of artificial generative intelligence is still at an early stage, although some sectors are already exploring its potential.

Banking companies, retail, telecommunications and logistics are incorporating artificial intelligence tools to improve operational efficiency and analytical capacity.

The main regional challenge relates to the availability of technological infrastructure and specialized talent. However, the integration of these tools also represents an opportunity for modernising productive sectors and improving productivity.

A transformation that just begins

Generative artificial intelligence is redefining the role of technology within companies. More than a point tool, it begins to consolidate as a strategic platform capable of transforming business processes and models.

In this scenario, understanding global technological trends and anticipating their impact on the different production sectors will be increasingly relevant to organizations.

In Vipzus we accompany companies in key productive sectors to identify opportunities, strengthen their positioning and design growth strategies in increasingly competitive markets.

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