Why 2026 will be the year of intelligent automation in businesses.

For a long time, automation simply meant doing things faster that were already done manually: reports, spreadsheets, repetitive processes. But the scenario has changed. With the evolution of artificial intelligence, especially generative AI and integrated Business Intelligence, automation has ceased to be operational and has become strategic. By 2026, it will no longer be about executing tasks, but about automating decisions, prioritizations, and data interpretations.

According to PwC, AI could contribute up to US$15.7 trillion to the global economy by 2030. A large part of this value comes precisely from intelligent automation applied to management, analysis, and decision-making. Companies that understand this sooner gain speed, predictability, and a competitive advantage.

From data overload to the need for intelligence

Today, companies produce increasingly larger volumes of data. Marketing generates metrics daily, sales feeds CRMs, and finance records costs, margins, and projections. The problem is not a lack of information, but an excess without rapid interpretation.

In many organizations, managers still rely on manual reports, lengthy meetings, and consolidations that take days. By the time the data arrives, the scenario has already changed. Intelligent automation emerges to close this gap between what happens and what is decided.

According to IDC, by 2026 more than 65% of global organizations will use AI-driven automation to support strategic decisions. Not to replace managers, but to expand human capacity for analysis and response.

Generative AI and integrated BI are changing the game

The big turning point is the combination of generative AI and integrated Business Intelligence. Before, managers needed to know where to click, which report to open, and how to cross-reference data. Now, they ask questions in natural language and receive contextualized answers.

This completely changes the dynamics of management. Instead of navigating complex dashboards, leaders begin to engage in dialogue with their data. Questions like "which campaign is impacting margins the most?" or "where am I losing revenue this week?" cease to be projects and become everyday actions.

Business Intelligence (BI) is no longer just visualization; it's becoming applied intelligence. AI interprets patterns, suggests priorities, and anticipates risks, reducing the space for isolated intuition.

Automation that generates action, not just efficiency

Automating for the sake of automation doesn't create an advantage. The differentiating factor of intelligent automation is generating action. It's not just about consolidating data, but transforming it into practical recommendations: where to cut costs, where to invest, what to adjust now.

According to McKinsey, companies that use advanced analytical automation can increase productivity by up to 30% and consistently improve operating margins. This happens because AI reduces the time between analysis and execution.

In 2026, managers won't ask "where's the report?", but "what decision needs to be made now?". Automation will operate as a strategic co-pilot for the business.

Speed ​​and scale as a competitive standard

The market has become faster, more integrated, and more unpredictable. Campaigns change in hours, cash flows fluctuate in days, and consumer behavior transforms in weeks. In this scenario, slow processes are costly.

Intelligent automation allows for scalable decisions. A small company gains analytical capabilities close to those of large organizations. It can monitor multiple areas in real time without increasing its structure.

According to Deloitte, companies that adopt AI-based automation reduce the time spent on repetitive analytical tasks by up to 40%. This time is reallocated to planning, strategy, and innovation.

From operational managers to strategic managers

Another direct impact is on the role of leadership. Instead of being report collectors, managers become orchestrators of decisions. AI takes care of the collection, organization, and initial analysis, while humans focus on context, vision, and direction.

This changes the profile of management. The leader stops spending energy compiling data and starts investing in interpreting scenarios, aligning teams, and accelerating strategic movements.

Intelligent automation does not replace people; it elevates the level of human work.

Sherlock within the logic of intelligent automation

It is in this scenario that Sherlock positions itself. By connecting marketing, sales, finance, and operations data, enabling simple questions, and delivering prioritized insights, the platform transforms automation into actionable intelligence.

Instead of more dashboards, Sherlock delivers answers, alerts, and action paths. It reduces the friction between data and decision-making, which is exactly what intelligent automation proposes for 2026.

2026 will not be about working harder, but about making better decisions.

The next business cycle will not be won by those who collect the most data, but by those who automate interpretation and execution better.