Artificial Intelligence in Investments: Efficiency Advances, but Human Judgment Remains in Charge

into at least one of their investment processes, while another 27% are using it through pilot programs or proof-of-concept trials. Furthermore, 91% plan to increase its use over the next 12 months.

AI is Already Generating Measurable Benefits in the Financial Industry

For Ugaz, the most visible impact of artificial intelligence today lies in productivity and operational efficiency. According to the report, 73% of asset managers use AI to automate routine tasks and optimize internal operations. Similarly, 68% employ it as an ally to generate analyses and identify investment opportunities in the early stages of research.

These advancements are already showing concrete results:

• 69% of firms report improved operational efficiency.
• 55% state they are obtaining faster and higher-quality insights.
• AI allows for processing large volumes of information in significantly less time.
• Teams can dedicate more time to strategic, high-value activities.

Ugaz emphasized that this analytical capability translates into more timely recommendations for clients. “We can process enormous amounts of information related to markets, risks, and investment portfolios at an unprecedented speed, strengthening the depth and quality of our analyses,” he explained.

In Mercer’s specific case, the company develops AI-powered research tools to streamline data collection and the creation of due diligence documents, reducing operational times in key processes.

However, the executive pointed out that current benefits are primarily operational. In fact, only 8% of the organizations surveyed reported direct improvements in net investment performance, while another 8% noted a measurable reduction in portfolio volatility.

Why Human Judgment Remains Indispensable

Despite technological advancements, artificial intelligence continues to function as a support tool rather than a replacement for financial professionals. The report’s data is compelling: barely 5% of firms grant AI any level of autonomous or semi-autonomous authority to recommend investments or execute trades.

For Ugaz, this reflects a fundamental reality of the sector. “Portfolio construction and execution require tackling complex challenges related to information integration, market interpretation, risk management, and bias detection. These are tasks that still demand human judgment and professional responsibility,” he indicated.

Technology can identify patterns, analyze trends, and process data with great speed; however, it lacks the ability to evaluate contextual, reputational, or strategic factors that often influence investment decisions. Therefore, organizations are betting on a model of collaboration between people and technology, where AI functions as a co-pilot, not an autopilot.

Risks Worrying the Financial Industry

The increasing incorporation of artificial intelligence also opens the door to new challenges in governance, regulation, and cybersecurity. Among the main concerns identified by Mercer are:

• Data quality or access issues (69%).
• Regulatory and compliance risks (59%).
• Deficiencies in data governance (31%).
• Systemic risks arising from the so-called “herd effect” (24%).

This last phenomenon is of particular concern to asset managers, as multiple algorithms could simultaneously reach the same investment conclusions, amplifying errors or increasing market volatility. Ugaz warned that accelerated adoption without adequate oversight mechanisms can lead to significant consequences for organizations and the financial system as a whole. Therefore, he stressed the importance of maintaining robust control, audit, and cybersecurity structures that allow for continuous monitoring of AI tool performance.

Skills the Financial Future Will Demand

Technological transformation is also redefining the talent profile the industry will require in the coming years. According to Mercer, more than half of the firms (56%) already have specific programs to train their employees in the responsible use of AI. Additionally, 57% maintain specialized teams dedicated to developing, overseeing, or integrating these technologies.

For Alexander Ugaz, the competitive advantage of the future will not depend solely on who has access to the most sophisticated tools, but on who possesses the talent capable of using them strategically. Among the competencies he considers fundamental are:

• Data literacy and governance.
• Ability to interpret and validate algorithm-generated results.
• Detection of biases and errors in AI models.
• Management of regulatory risks and compliance.
• Critical thinking applied to decision-making. “The advantage will not be in competing with the machine in speed, but in knowing how to direct it, supervise it, and correctly interpret its results,” he stated.

Latin America Faces Gaps, but Also Opportunities

While AI adoption is advancing more rapidly in markets like the United States, United Kingdom, and Europe, Ugaz believes Latin America has a significant opportunity to accelerate its development. The main reason is that most organizations are not building their own systems from scratch. Currently, 63% use available technological solutions on the market, and 51% make adaptations to platforms developed by specialized providers. Only 9% operate entirely proprietary infrastructure. This significantly reduces entry barriers for Latin American companies, allowing them to focus on strengthening aspects such as data quality, technological integration, and regulatory compliance. For Mercer Mexico, the window of opportunity is open. The key will be to build the necessary foundations now to leverage a technology that will continue to gain prominence in asset management.

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