Artificial intelligence is consolidating its move from experimentation to real operation in the company, and it is doing so with measurable results at the level of operational efficiency. More and more organizations are seeing how these technologies allow them to optimize resources, reduce time and increase the efficiency of key business processes.
In this sense, IFS, a global leader in industrial artificial intelligence and business software for critical assets and services, ensures that in asset-intensive industrial and service sectors, the adoption of AI-based systems is already generating improvements of up to 60% in operational efficiency, the recovery of 20 hours of work per week per team and returns that can reach almost 3 million euros annually. These results place efficiency as one of the main indicators of the real impact of AI on the company.
Drivers of organizational transformation
Furthermore, as stated by the company, “another key indicator is added to these figures, such as the ability to free up work time on a large scale, which has a direct impact on the overall efficiency of the organization.” In fact, some implementations are returning up to 90,000 hours to the workforce, reflecting the direct impact of these systems on productivity and business efficiency.
These data show a phase change in the adoption of AI. “What until recently were pilot projects or proofs of concept are evolving into real deployments integrated into daily operations, with clear improvements in efficiency and control,” says Gonzalo Valle, IFS pre-sales manager. The so-called agentic AI, based on systems capable of executing tasks and processes autonomously, is positioned as one of the main drivers of this transformation aimed at operational efficiency.
In this context, companies are beginning to apply these systems in critical business processes. In the industrial field, for example, the automation of tasks such as supply chain management, inventory replenishment or coordination with suppliers is already reducing the operational burden and improving efficiency in the ability to anticipate supply problems.
The results are also observed in more specific operations. In some cases, the automation of more than 150 weekly order confirmations has made it possible to achieve significant efficiency improvements and recover operational time for teams, which in turn drives the expansion of these systems within organizations as a lever for sustained efficiency.
Another example is materials management in field services, where the incorporation of AI-based assistants allows technicians to locate and request parts through conversation, directly contributing to generating million-dollar returns, improving service efficiency and optimizing the use of time in critical operations.
“This advance not only responds to greater technological maturity, but also to a change in business priorities. The focus is no longer solely on the capacity of the models, but on their tangible impact, their contribution to efficiency and their ability to operate safely in complex environments,” explains Valle.
Task automation and inventory replenishment are already reducing operational burden
Aspects such as governance, auditability or life cycle management of these systems are becoming determining factors for their adoption, since they allow AI to scale without compromising efficiency or operational control.
Efficiency as a new operating model
In parallel, the market is evolving towards operating models based on supervision by exception, in which automated systems manage entire processes and human teams intervene only when necessary. This change redefines the organization of work and reinforces efficiency as the central axis of the new operating model.
Taken together, the figures point to a clear trend in which industrial AI has ceased to be a promise and has become a direct lever of efficiency, productivity and economic return, with a real impact on the daily operations of organizations.
In this same line of evolution, IFS continues to expand its capabilities with initiatives such as IFS Loops Agent Studio, a platform that allows organizations to design, deploy and govern digital workers in an agile and secure way, helping to maximize efficiency without the need for advanced technical knowledge.
