In this article, we explore why implementing AI agents in companies can transform artificial intelligence from potential into action — optimizing processes and accelerating innovation.
AI: From Promise to Execution
Artificial intelligence is no longer a futuristic promise or an experiment reserved for curious companies. In just a few years, it has moved from research labs and pilot tests to becoming a strategic tool for organizations of all sizes and industries.
According to McKinsey’s State of AI Report, 78% of global companies already use AI in at least one business function — up from 55% in 2023. This rapid growth marks one of the fastest technological adoptions in history.
The economic impact is equally undeniable: PwC estimates that AI could add up to USD 15.7 trillion to global GDP by 2030 — driving productivity, reducing costs, and creating new business opportunities once thought impossible.
But behind the numbers lies a key question: How can companies turn AI into real, sustainable results?
The Role of AI Agents
At Novis, we believe one of the most powerful answers lies in AI agents. They’re not new language models or just another chatbot — they’re something far more action-oriented.
An AI agent is a configurable assistant that handles specific tasks using natural language, tools, and contextual data. It not only understands what it’s asked to do — it also knows how to execute it, by connecting to different data sources and systems.
Let’s look at a real-world example:
- A company receives hundreds of customer requests daily. A traditional chatbot might answer FAQs but escalate any special case to a human.
- An AI agent, on the other hand, could check inventory in real time, generate a replenishment order in the ERP, send confirmation to the customer, and log the entire process automatically.
That leap — from responding to executing — is what makes AI agents a true game-changer.
Why Are We Talking About Agents Now?
In recent months, we’ve seen many organizations start AI projects that remain stuck at the prototype stage — assistants for internal queries, bots that summarize documents, or classifiers for support tickets.
Interesting advances, yes — but they don’t transform the way the business operates.
AI agents do. By connecting to real systems, automating workflows, and coordinating actions, they stop being experiments and become active members of the operation.
And here’s the key part: they don’t require training a model from scratch. They rely on existing large language models — from OpenAI, Anthropic, Google, and others — and connect them to enterprise tools and data to build customized, goal-driven solutions.
The Challenge: Building a Functional AI Agent
This is the less visible — yet most critical — part.
Building a working agent is not as simple as opening an interface and typing a prompt. It requires understanding model behavior, API integration, sensitive data handling, orchestration logic, and above all, ensuring scalability and security.
Each model provider operates differently in performance, cost, and capabilities. That forces developers to learn multiple environments, write custom integrations, and adjust parameters manually — increasing both implementation time and adoption costs.
How Novis Simplifies the Journey
At Novis, we’ve built an operational platform that dramatically simplifies this process.
It allows our clients to:
- Develop and fine-tune AI agents without needing deep knowledge of model architectures or APIs.
- Switch between LLL providers (OpenAI, Anthropic, Google, etc.) with just a few clicks — no rework needed.
- Iterate fast, moving from concept to production-ready agent in days, not weeks.
This empowers business units to experiment and optimize independently — while the platform manages permissions, data, and security by design.
Beyond the platform, Novis offers consulting and implementation services to help organizations adopt agents strategically. This includes user training, agent blueprint definition, MCP design, RAG architecture setup, and LLM security configuration. Our approach goes beyond technology delivery — we ensure companies adopt AI effectively and sustainably, with an expert partner guiding them every step of the way.
Conclusion
Most companies already have access to AI — but the real value doesn’t come from having a model. It comes from putting it to work.
An AI agent is the bridge between technology and action — between potential and execution.
And with the right approach, it can move from promise to measurable competitive advantage.
At Novis, we accompany organizations throughout this journey — from use-case definition to implementation and optimization of agents that deliver real business value from day one.
We invite you to watch the recording of our webinar Enterprise AI Agent Adoption Strategy, where we explore these topics in depth.
And whenever you’re ready, contact us to discuss your next project.
Written by Cristian Marín, CTO – Novis
