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, a technology that can help any company identify the best possible decision among multiple alternatives taking into account complex variables and operational restrictions. The goal is to understand why each company is still not taking the step and what it would take to do so.
95% of companies sense 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 not have any relevant effect on their business or the competitiveness of their company.
This data rules out that the brake is technological skepticism. The problem is not that organizations doubt the value of prescriptive AI, but that many companies 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 company’s management focus, and prescriptive AI is displaced on the agenda. This is followed, with 16% each, by the fact that this technology has not been considered in the organization until now, and the lack of specialized internal talent to implement it within the company.
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 within a company.
«This ranking of barriers is very revealing. Investment is not the main problem. The problem is the agenda, knowledge and internal capacity of each company. They are obstacles that can be addressed with the appropriate levers,” adds Daniel Herrero.
A low-risk pilot, the most effective lever to activate adoption
The study also asked non-user companies what they would need to take the step. The most cited response, at 26%, is to start with a low-risk pilot that allows the company to see concrete results without compromising resources or critical processes.
Next, with 19% each, is the possibility that the solution does not require a specialized internal technical team and that it integrates with the company’s 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.
What would help to better understand the real value of technology?
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 a company in the same sector (31%).
This demand profile reflects that the market does not need more theoretical arguments. It needs evidence, applied examples, tools that translate the potential into understandable figures for the company’s internal decision making, and expert support during implementation.
57% of companies that do not currently use prescriptive AI give it an exploratory or experimental role
“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: mostly exploratory, but with increasing openness
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 company 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 a company 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.
