92% of organizations use AI, but only 8% achieve economic impact
The expansion of AI across organizations contrasts with the difficulty of taking projects from experimentation to a scale that delivers economic impact.
Artificial intelligence has moved beyond being a technology reserved for experimental projects and has become part of companies’ investment priorities. However, adoption does not in itself guarantee a competitive advantage.
Global data from McKinsey & Company shows that around 92% of organizations use AI in at least one of their functions, but only 8% have managed to bring these initiatives to a scale capable of generating real and sustainable economic impact.
For Servinformación, this gap shows that the value of AI does not depend on the number of tools a company incorporates, but on its ability to integrate them with specific business needs.
“The conversation about artificial intelligence must move from how many solutions a company has to what results it achieves with them. An organization gains a competitive advantage when it identifies processes where AI can generate a specific impact, establishes indicators to measure it, and has the technological and organizational conditions to scale it,” says Juan Manuel Urrego, Regional Innovation Manager at Servinformación.
Identifying where AI can generate results.
One of the first steps is to identify use cases directly aligned with corporate objectives.
AI can help optimize costs and time, but also improve the customer experience, anticipate behavior, support decision-making, develop new services, and generate growth opportunities.
The second aspect is to measure the value generated. Defining indicators before implementing a solution makes it possible to determine whether an initiative delivers results and which ones have the potential to scale.
Productivity, revenue, costs, quality, response times, and customer satisfaction are some of the variables that can form part of this assessment.
Measuring value before scaling.
The third component concerns the organization’s ability to bring these solutions into real-world processes. This involves reviewing data, infrastructure, security, talent, and AI governance, as well as adapting workflows when technology changes the way people perform their functions.
“A proof of concept can demonstrate that a technology works, but an AI strategy must demonstrate that it generates value for the business. Moving toward broader adoption requires reliable data, infrastructure, specialized talent, security, and a roadmap that connects each initiative with a business priority,” adds Juan Manuel Urrego, Regional Innovation Manager at Servinformación.
Moving from experimentation to strategic adoption.
For the company, the evolution of artificial intelligence presents an opportunity for businesses to move from experimentation to strategic adoption. Competitive advantage does not lie in using AI simply for the sake of using it, but in turning it into a capability that generates measurable results, can scale, and responds to each organization’s priorities.
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