Artificial Intelligence has fully reached our lives, and there are hardly any areas of it where the tentacles of said technology have not already reached. But without a doubt one of the most interesting and crucial aspects where AI is being incorporated is in companies, since in a very short time it has shown that it can revolutionize any sector and take companies to new levels.
However, this task is far from being easy, and AI presents several problems or issues that must be resolved, and it cannot be any other way than through trial and error in the adoption of this technology. Hugo Cortada, Director of Business Development at Serimag, a technology consultancy specialized in the design and implementation of solutions based on artificial intelligence (AI) and automation in the field of process transformation for large companies, is experiencing this transformation firsthand, and from elEconomista.es we have had the opportunity to Talk to him and find out how things are going.
What is the current state of AI adoption in large companies?
Low, very low. Adopting new technologies that radically change the way we work is complex. If we also talk about large companies The impact of making a mistake is very great and where there is often a lack of specialized talent, It ends up translating into great resistance to change.
For many companies, these efforts have remained in proof-of-concept phases and not large-scale projects. According to a 2024 Minsait study, 90% of companies do not have a defined AI Strategic Plan aligned with the business.
Which sectors are leading and which are lagging behind?
There are very competitive but little automated sectors such as The banking or insurance sector is leading the way by implementing use cases that allow them to be more efficient in their operations, reach their customers in a more personalized way and develop new products and services.
On the other hand, there are sectors that have been less proactive in adopting AI solutions such as the public, educational or retail sectors. The latter is largely due to the fact that you have to have expert profiles in AI and today there is still a small volume of technological profiles in some sectors, which makes the degree of implementation and how to get the most out of this tool difficult.
What are the main mistakes large companies are making when adopting AI?
In my opinion there are five key points; establish a clear and shared vision, prioritize cases of use based on ROI and fit with the visionestablish tracking KPIs that determine the success or failure of initiatives, encourage cross-team collaboration and Ensure data security and AI ethics implanted. In addition to these 5 points, talent is essential, training teams (upskilling) as well as relying on expert suppliers is a critical piece of any innovation and transformation process.
What are the main challenges that large companies face when implementing AI?
I would say that the first thing is a certain resistance to change caused by a lack of knowledge and a culture that does not encourage taking risks and daring to question the status quo. Teams must be trained and a culture must be established that allows and even encourages testing.
Secondly, it is still very complicated in innovative services to make a correct estimate of the return on investment, since a disruptive project may not come to fruition and that is difficult to take into account in these calculations. A culture of experimentation must be adopted. And in these calculations we must take into account not only the financial metrics but also the non-financial ones, because AI can generate immediate, non-tangible benefits such as operational efficiency or improved customer experience.
And finally, it is difficult to find good partners. That is why it is key rely on specialized and experienced suppliers contrasted in use cases similar to those sought to be developed.
What is the impact of AI on the workforce of large companies? How are employees adapting to this new reality?
I think that on a practical level, as a manager, Great opportunities arise to develop internal talent (upskilling) for gain productivity and be able to innovate more agilely. But at the same time, there are areas and functions that become obsolete and those teams must be redirected to tasks with greater added value. Changes are present in our daily lives and Technology must always contribute to our individual growth (in what refers to the people who are part of the company) and business.
Companies that are in the process of change with AI must assume that This is a transition period and we must know how to re-place the value of humans in the company’s tasks and the value of technology in its different functions.
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