By 2026, 40% of enterprise applications will feature AI agents (Gartner). Discover how agentic AI turns operational costs into growth levers and how to prepare your workflows with MTM.

The Advent of Agentic AI: Why 2025 Marks the End of 'Everything Manual' for Brands

Less than 5% in 2024, but over 40% by 2026. This is the share of enterprise applications that will integrate autonomous AI agents according to Gartner forecasts. This figure is not just a technological trend; it is an alarm signal for every Operations or Marketing Director.

We are leaving the era of "passive" Generative AI (the kind you speak to via a prompt) to enter the era of Agentic AI (the kind that acts). For brands, this transition marks a brutal rupture: value no longer lies solely in the capacity to produce content, but in the capacity to autonomize its orchestration.

In 2025, competitive advantage will belong to organizations capable of transforming their fixed coordination costs into fluid, autonomous flows. Here is an analysis of this transformation and how to anticipate it.

Beyond the "Co-pilot": Understanding the Agentic AI Disruption

To grasp the upcoming financial impact, we must first clear up the technical ambiguity. Too many decision-makers still confuse Generative AI (GenAI) with Agentic AI.

The Fundamental Difference: Creation vs Action

Generative AI is a creation tool: it writes, draws, or summarizes upon request. It waits for an order. Agentic AI, however, is a system designed to achieve objectives. It reasons, plans, uses software tools, and makes decisions to execute a complex task without constant human intervention.

As highlighted by BCG, these agents do not just assist; they integrate into the core of enterprise platforms to "transform operating models." We are moving from software that helps you work, to software that does the work.

A $450 Billion Economic Seismic Shift

This paradigm shift is not just a matter of comfort, it is a question of valuation. The Capgemini Research Institute estimates that agentic AI will generate an economic value of $450 billion by 2028. This value will not come from selling new products, but from massive gains in efficiency and execution speed. For a brand, ignoring this wave amounts to accepting an obsolete cost structure in the face of "Agent-Native" competitors.

The Economic Equation: Why Autonomy is the New Margin Lever

Through a financial lens, the integration of Agentic AI addresses a critical issue: the inflation of coordination costs (overhead).

Reducing "Friction Cost"

In content management and marketing, time wasted is not found in creation, but in the interstices: validations, format conversions, metadata, file transfers. These invisible frictions weigh heavily on the P&L (Profits & Losses).

Agentic AI attacks these hidden costs. According to PwC, it allows for a drastic reallocation of human resources. By delegating "digital logistics" to agents, teams refocus on high-value tasks (strategy, creativity). The agent costs no mental load; it executes repetitive tasks (tagging, distribution) at a speed no human can equal, mechanically reducing the unit production cost of an asset.

Scalability Without Salary Inflation

The historical challenge for brands has always been scalability: to produce twice as much, you often had to hire twice as many people (or outsource at great cost). The IBM TechXchange Community highlights how Agentic AI breaks this linear correlation. It allows for managing exponential volumes of data and tasks without increasing the wage bill proportionally. This is where tomorrow's profitability is played out: the ability to scale a brand globally without exploding OpEx (Operating Expenses).

2025: What Does an "Agent-Native" Brand Look Like?

If we project current weak signals to a 12 to 24-month horizon, the functioning of marketing and communication departments will mutate radically.

Self-Orchestrating Workflows

Imagine a product launch. Today, it is a succession of emails, Slack pings, and manual checks. Tomorrow, in an "Agent-Native" structure, the human defines the objective ("Launch Winter Campaign EU on social channels"). The agents take over:

• They identify validated assets.
• They adapt formats for each channel via API connectors.
• They notify legal leads only if an anomaly is detected.

As Forbes indicates, Agentic AI becomes the engine of value creation by fluidifying these complex processes.

AI as the Guardian of Consistency

The other major cost for global brands is image dilution (brand inconsistency). An AI agent never "forgets." It can verify compliance with visual and semantic guidelines 24/7 across thousands of assets. Autonomy here guarantees a standardization of quality that is impossible to maintain manually at scale.

Concrete Orchestration: Moving from Theory to Practice with MTM

At MTM, we anticipated this transition. We do not view content management as storage, but as a living flow. This is the philosophy behind our Accelerate module.

Stop Managing Files, Start Piloting Flows

The mistake would be to think you need to replace your teams. MTM's vision is one of collaborative automation. Our platform integrates agentic logic to handle heavy workflows. Thanks to an intelligent metadata structure and robust API connections, MTM acts as the central nervous system of your operations:

• Assets do not sleep: they are automatically tagged, classified, and pushed to the right channels.
• Validation tasks are routed without friction to the right decision-makers.

The "Human-in-the-Loop" Approach

Total autonomy without control is a risk. This is why our solutions allow you to define precisely where the agent acts alone and where the human must validate. You retain strategic control; MTM handles operational execution. This is how Time-to-Market is transformed into a real competitive advantage.

Operational Autonomy as the New Standard for Profitability

Agentic AI is not a "nice-to-have" option for 2025; it is a condition of economic survival for brands operating at scale. Those who remain stuck in manual processes will see their margins erode against more agile and automated competitors.

Operational autonomy is within reach. The question is no longer "if" you will adopt it, but "when" you will decide to free your teams from execution to focus them on strategy.

FAQ: Agentic AI Essentials in 5 Questions: Definitions, ROI, and Key Differences

What is Agentic AI? Agentic AI refers to artificial intelligence systems capable of perceiving their environment, reasoning, and acting autonomously to achieve specific goals. Unlike a simple chatbot, an AI agent can use software tools and execute complex workflows without constant human intervention.

What is the difference between Generative AI and Agentic AI? Generative AI (like ChatGPT) focuses on content creation (text, image) based on a prompt. Agentic AI focuses on action and task execution (planning, sending emails, file management) to achieve a concrete result.

What is the ROI of Agentic AI for a company? Return on investment comes primarily from operational efficiency: reduction of repetitive tasks, acceleration of Time-to-Market, and the ability to process massive data volumes without increasing the wage bill (scalability).

How does Agentic AI improve marketing workflows? It automates coordination. Agents can manage the content lifecycle: from automatic tagging to legal validation and distribution on social channels, thereby freeing creative teams from administrative tasks.

Does Agentic AI replace humans? No, it modifies their role. The recommended approach is "Human-in-the-loop": AI manages execution and low-value tasks, while humans retain strategic control, final validation, and management of complex exceptions.

Sources

• Gartner: Gartner Predicts 40% of Enterprise Apps Will Feature Task-Specific AI Agents by 2026
• Forbes: How Agentic AI Is Shaping Business Value For Enterprises
• Boston Consulting Group (BCG): How Agentic AI Is Transforming Enterprise Platforms
• IBM TechXchange: The Rise of Agentic AI in Enterprise Operations
• PwC France: IA agentique : un moteur d’expérience client et d'efficacité opérationnelle
• Capgemini Research Institute: Retombées économiques de l'IA Agentique estimées à 450 milliards de dollars d'ici 2028