Today artificial intelligence contributes to bringing the company to a higher level of efficiency, automation and profit. But a careful selection must be made when choosing software for specific projects and applications. But let’s take a step back and try to understand what is meant by artificial intelligence and how it can increase the organization’s performance. It is necessary to understand the importance of the right software in an Artificial Intelligence project.
AI for current competitive challenges
Inevitable premise are the challenges of the current competitive landscape, globalized and digitized: to compete in an environment that requires high performance, speed of execution and a “to do with less” approach, companies must implement efficient processes and effective strategies, where the margin of error is reduced to a minimum and work flows are agile. Realizing such an ecosystem means having the ability to make decisions quickly, trigger automatisms to eliminate inefficiencies and malfunctions, predict future situations by anticipating solutions. Advances in big data management, analytics, machine learning and cognitive computing(i.e. the main ingredients of artificial intelligence platforms) are putting a powerful tool in the hands of companies in order to gain efficiency and achieve profit objectives.
The importance of software selection
How to realize the benefits of artificial intelligence applied to business? First of all, it is necessary to start from a correct software selection in the design phase, identifying business needs with prudence and knowledge of facts. Artificial intelligence offers specific solutions to concrete problems and must be trained to adapt to a specific application area.
At the base there must be the ability to collect, manage and process huge volumes of data. After appropriate processing, they allow us to return useful evidence both to speed up and make decision-making more aware and to trigger automatisms to regulate systems and improve process management.
Customized and future-proof intelligence
An artificial intelligence platform must therefore be tailored to the particular business needs, that is, capable of managing specific data sets by type of application and capable of creating calculation models aimed at solving certain problems. The software must not only be declined according to the organizational reality, but must also learn and adapt in the course of work. The algorithms defined and developed in the development phase must be refined over time according to the results obtained, continuously raising the levels reliability and accuracy.
In short, the intelligence suite must be future-proof and guarantee long-term performance improvement, following the principle of continuous improvement thanks to the machine learning functions.
Distribute and improve intelligence
The platform must ensure the rapid deployment of intelligence (the applications and algorithms that allow you to predict and solve specific business problems) within the organization. Think for example of a manufacturing plant, where thanks to the widespread distribution of IoT devices, it is possible to monitor the health of the machinery and avoid any production stoppages: the artificial intelligence software not only can accurately predict failures, but also intervene automatically to adjust the parameters of the machines and prevent possible breakages. It is therefore a matter of distributing the intelligence within an entire system to maximize the overall performance level, while simultaneously maintaining the algorithms and intelligences that regulate the machines based on previous experiences and refinement processes.
The choice of partner and skills
Only with the right software for data management and processing, capable of triggering automatisms that fluidify business processes and capable of evolving over time by perfecting analytical and predictive algorithms, can a company successfully complete the artificial intelligence, promptly solving specific issues and making the business evolve.
Obviously, in the software selection phase, the partner who provides the solution and offers support in deployment must also not be underestimated. Artificial intelligence projects are not technological implementation tout court, but provide for a careful understanding and rationalization of the underlying processes. It therefore requires the ability to isolate the application areas, identify the correct datasets that allow to shed light on the problem. It also requires to develop and maintain the algorithms to find solutions. There is therefore a whole phase of preliminary strategic definition which should not be underestimated. It must be rather managed with the know-how and experience that only a specialist in the sector can have.
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