Opportunities and risks of Artificial Intelligence

Artificial Intelligence (AI) and Machine Learning (ML) have increasingly established themselves as key technologies for business growth in many industries, becoming the driving force behind digital transformation and revolutionizing the way we interact with processes and data. The increasing importance given to its information assets and the way it is managed, combined with the spread of Cloud platforms, which offer computational and storage resources at an advantageous price, led to a democratization of Artificial Intelligence.

In particular, with the recent spread of Generative Artificial Intelligence (Genai), we have increasingly witnessed the introduction of integrated systems to business processes, such as chatbot and virtual assistants.

AI-based systems represent both an opportunity and a risk for companies. In this article we will discuss the main advantages associated with the introduction and management of these systems, and how the associated risks can be mitigated.

AI systems: the opportunities

Business process improvement: AI systems are built with the idea of integrating normal business processes, offering features such as support, data analysis, prediction and detection of anomalies. This translates into greater efficiency in the processes and the possibility of introducing automations.
Big Data Analysis: AI algorithms, in particular those based on Deep Learning such as Neural Networks, allow to process large amounts of data and extract hidden Insights, reporting higher performance than the classic statistical algorithms, which often cannot handle too high data loads.
Anomaly detection: one of the main advantages of AI models is the ability to detect anomalies, trends or patterns within large data moles. This information can be used as a reference for new investment opportunities or to capture malicious behavior, allowing you to promptly take countermeasures.
Predictive analysis: the ability to predict the future finds interest in many sectors, from manufacturing to finance to healthcare. More advanced AI models can analyze data from past transactions or events, capture the internal structure of data, and use it to predict future patterns or behaviors.
Informed decision making: the possibilities offered by Artificial Intelligence lead to a more informed decision making process, which is based on insights and information collected from business data, which could escape a human review. Companies that rely on data from their processes (data-based organizations) have a competitive advantage in the market.
Customer experience: The introduction of chatbot and virtual assistants improves customer experience, as these advanced systems are able to answer questions, make suggestions, and even identify issues in real time. Using chatbots improves productivity and customer satisfaction.

AI systems: the risks

Development and implementation costs: the initial costs of developing and implementing an AI system can be significant. Using Cloud solutions is one way to reduce these costs, as the cost of the service is based solely on consumption.
Need for technical expertise: developing an AI algorithm is a combined effort of Data Science and Engineering, and requires a lot of technical experience and specialized staff, which for many organizations could be difficult to find.
Security and privacy: Data security and privacy management are key elements for every organization. In particular, when using Generative AI systems, there must be certainty that private company data will not be used to train third-party models
Transparency and reliability: Machine Learning models can present unexpected and difficult to understand results, and often perpetuate the biases that are present in the data used for training. A correct phase of Data Preparation and the introduction of Explainable AIsolutions significantly limit these problems.
Human impact: the idea behind introducing an AI solution is to support, not replace, human activity. Artificial intelligence lacks the creativity and attention that human beings can give, and should be used to complement human work.

How to reach the full potential of Artificial Intelligence?

Introducing AI systems within your organization can bring great benefits but it is important to also consider risks. AI systems should be developed following the principles of Human Centric AI, in which consideration of the impact on human activities, the security of persons and data (privacy), and the guarantee of transparency and reliability are key elements.

Blue BI has been working for years in the field of Business Intelligence and Business Analytics, and offers solutions based on Artificial Intelligence such as Forecasting systems, Anomaly Detection and Chatbot. Following the principles of Responsible AI, Blue BI puts data security and GDPR regulations first, as well as the efficiency and accuracy of models.