Advances in artificial intelligence and advanced analytics today make it possible to address increasingly complex decision problems with higher levels of precision and efficiency. Although practically all large Spanish companies recognize room for improvement in costs and operational efficiency, 84.5% of complex decisions are still made mainly based on the experience and judgment of their teams, or with the support of basic tools such as spreadsheets, fixed rules and traditional analytics solutions. This is one of the most striking conclusions of the I Barometer of Mathematical Optimization in Spain and Portugal, prepared by DECIDE | Linkroad in collaboration with Gurobi, a leader in mathematical optimization technology, whose first advance was presented in May in Madrid.
Now, the study delves into the segment of companies that have not yet adopted prescriptive AI, the technology that allows not only to predict scenarios, but also to identify the best possible decision among multiple alternatives taking into account variables and complex operational restrictions, to understand why they still do not take the step, and what they would need to do so.
The gap is not one of ignorance: 95% of companies sense the value, but do not act
One of the most revealing findings of the study is the contradiction between perception and action. Among large Spanish companies that do not currently use prescriptive AI, 95% recognize that it would have some positive impact on their ROI. Of that percentage, 46% rate it as moderate or significant. Only 5% consider that it would have no relevant effect on their business.
This data rules out that the brake is technological skepticism. The problem is not that organizations doubt the value of prescriptive AI, but that they have not managed, or have not prioritized, turning that conviction into action.
«Many companies already know that mathematical optimization works, they know that it has an impact and, in some cases, they already know where to apply it. What is missing is not vision, it is execution. And that has a solution with the right approach,” says Daniel Herrero, Global Capability Lead – Decision Intelligence at Linkroad.
Strategic priorities, the number one brake
The study clearly identifies the barriers that explain this gap. The main one is strategic prioritization, indicated by 19% of companies that do not use it: there are other initiatives that occupy the managerial focus, and prescriptive AI is displaced on the agenda. Next, with 16% each, is the fact that this technology has not been considered in the organization until now, and the lack of specialized internal talent to implement it.
Next are the perceived complexity of the solution (14%), the difficulty in justifying the ROI to management or investors (13%) and the lack of knowledge about what it is or how it really works (11%). Significantly, lack of budget is the last brake on the list, indicated by only 10% of respondents, which dismantles one of the most common arguments to justify non-adoption.
«This ranking of barriers is very revealing. Investment is not the main problem. The problem is the agenda, knowledge and internal capacity. They are obstacles that can be addressed with the appropriate levers,” adds Daniel Herrero.
A low risk pilot, the most effective lever
The study also asked non-user companies what they would need to take the step. The most cited answer, with 26%, is: start with a low-risk pilot, which allows seeing concrete results without compromising resources or critical processes.
The study reveals that companies demand practical and tangible resources to help them understand the value of prescriptive AI
Next, with 19% each, is the possibility that the solution does not require a specialized internal technical team and that it integrates with current systems without major changes. The drive from management and the clear quantification of the economic impact stand at 18%, respectively.
This data points to a pattern. Companies are looking for concrete evidence, technical accessibility and a progressive path to adoption.
Tools that translate potential
Along the same lines, the study reveals that companies demand practical and tangible resources that help them understand the value of prescriptive AI before committing. Product demonstrations are the most valued resource, indicated by 38% of those surveyed, followed by ROI calculators (37%) and success stories from the same sector (31%).
This demand profile reflects that the market does not need more theoretical arguments. You need evidence, applied examples, tools that translate potential into understandable figures for internal decision-making, and expert support at the time of implementation.
“Adoption is not accelerated with more theory, but with evidence. When a company sees a case applied to its reality, understands the economic impact and has a team that accompanies it in the implementation, the leap from exploration to action is much more natural,” says Begoña López Piedra, CMO of DECIDE | Linkroad.
The future is mostly exploratory
Despite current barriers, the study detects a majority predisposition to explore technology in the coming years. 57% of companies that do not currently use prescriptive AI give it an exploratory or experimental role in a horizon of two to three years. 28% see it as possible specific support in specific decisions. Only 15% consider that it does not fit their operating model.
«Mathematical optimization already drives high-impact decisions in multiple sectors, with adoption that continues to accelerate. And the most natural path for organizations to incorporate it begins with a well-designed pilot: a real problem, clear metrics and the support of the management team,” concludes Duke Perrucci, CEO of Gurobi.
