AI applications in different industries are growing steadily around the world and will undoubtedly revolutionize the industrial world in the coming years.
According to a survey commissioned by the European Commission, the first on the acceptance of artificial intelligence by European companies, “awareness of artificial intelligence is almost universal”. The study shows that 78% of companies in the region know what artificial intelligence is; 15% are not clear and 7% say they do not know what it is. However, more than half of the companies surveyed (51%) do not use these technologies and have no plans to surf the wave.
The study -in which more than 9,000 European companies participated- shows that in the case of Spain, 40% of the companies surveyed have implemented at least one of these technologies.
But it also shows that both those who already use these tools and those who have not yet been encouraged to incorporate them face certain internal barriers. 56% of Spanish companies mention the labor market’s lack of training in these topics (programming, big data, robotics, etc.), while implementation costs discourage 66 % of national businesses. The complexity of algorithms and the resulting difficulties in understanding and trusting them are also mentioned.
At European level, the main strategy for incorporating these technologies is to opt for some form of outsourcing, by purchasing platforms (59%) or contracting third parties to develop them on a custom basis (38%). Only 20% opt for in-house adoption.
However, this post is not about the multiple benefits of the use and applications of AI in companies and industrial environments, but about something less obvious: the incorporation of these tools will be key in the “fourth industrial revolution”, but the real differential will be to do it according to a long-term strategy if we expect to see a real return on investment.
Whether they are digital natives or those facing migration, the multi-disciplinary teams that will implement these projects will need to define a strategy from the outset that answers nodal questions: how will the incorporation of AI help our department or company? How will it contribute to better serve our customers, improve our operations and, ultimately, win in the marketplace?
In the short term, AI approached as a series of point solutions without any fundamental improvement in issues such as data infrastructure can be more of a headache than an opportunity for the organization. At the same time, poor project selection, unrealistic ROI expectations, lack of strategic focus and understanding of AI maturity lead to the failure of 80-90% of AI projects.
But in the long run, the benefits will not be achieved with a single successful deployment, but with a transformation of the way the company operates and its vision of how it can win in the marketplace through AI.
To define a holistic approach, several factors will need to be analyzed:
*Timeline: how many years does this vision cover?
*What specific objectives and results does the company intend to achieve in that time horizon? This could be the opening of new lines of business, a basic transformation of who we serve and how, or simply goals related to growth, profits or market share that AI and digital technologies could help achieve.
*Which lines of business, products or services that will incorporate AI appeal to or respond to a specific customer need? Which will be less important with AI? It is also necessary to consider the trends in each sector and how the company will adapt to them, as well as to analyze how AI will contribute to consolidate advantages in the market.
*Which processes or operations involve more resources and which have a greater impact on overall company performance or as a driver of growth? In which areas or processes could automation add efficiency and which could be redesigned or even eliminated altogether depending on the lines of business?
*What data sources are important to the business, and how could they be improved or made more accessible, both in relation to current lines of business and future products or services?
*Which markets and segments (defined by demographics or business criteria) or product lines would benefit from AI? Which are the most important? This analysis may even open up new market opportunities or make irrelevant ones relevant.
In addition to answering these questions, it is important to keep in mind that this vision must be alive and evolving, so it is advisable to review it in depth at least once a year.
Finally, it will be very important throughout the process of ideation, planning and deployment of any AI project and strategy that it be considered unfailingly as part of a broader digital transformation.