Artificial intelligence and business: companies want reliable data

Artificial Intelligence (AI) is revolutionizing data management, pushing businesses to seek ever more reliable data to take full advantage of the opportunities offered by advanced analytics and real-time personalization.
In this context, a complete and reliable database becomes crucial to guide business decisions and develop strategies to work more efficiently, with particular emphasis in the field of AI, where trust emerges as the main priority.
This connection between the ability to fully exploit the power of AI and accurate and complete data emerges forcefully from the “State of Data & Analytics”, the Salesforce report that summarizes the responses of 10,000 global decision makers and highlights the strategies adopted to exploit all the advantages of artificial intelligence and maximize the power of data.
Artificial intelligence and business Artificial intelligence and data reliability What is holding back the adoption of AI in companies How to increase trust in artificial intelligence Artificial intelligence and data reliability Generative artificial intelligence is considered a disruptive technology aimed at increasing productivity in companies (for 91% of those interviewed).
Despite the numerous advantages and possibilities offered, ranging from content creation to software development, this new technology is not without risks.
One of these comes from the reliability of the data used in the training phase.
94% of business leaders say advances in artificial intelligence make data management a top priority.
However, such progress is rapid and companies are eager to profit from this technology.
According to the survey, more than three-quarters of business leaders already fear losing the benefits of generative AI.
Not only due to the lack of technical requirements, but above all due to the inability to integrate AI into one's technological stack (for 60% of the leaders interviewed) and for the difficulty of having complete, unified and accurate data (necessary for 55% of IT leaders).
A discriminating element for the success of the adoption of artificial intelligence is data maturity: organizations with high maturity that can boast superior infrastructure, strategy and alignment compared to organizations with low data maturity manage to use AI effectively .
What's holding back AI adoption in businesses Over the next 12 months, the amount of data generated by businesses will increase by 22% according to a Salesforce report.
Without reliable and complete data, business leaders will fail to correctly set business priorities.
According to the research, given the dependence of AI results on the quality of the underlying data, 92% of IT leaders highlight the need for reliable data.
At the same time, only 57% of data and analytics leaders have complete confidence in the accuracy of their data.
This percentage drops to 43% in line of business departments and explains the aversion to adopting AI on a larger scale.
Inaccurate or non-homogeneous data risk generating distorted results in terms of bias for 73% of respondents.
Not only that, the improper use of data or its manipulation also raises considerations from an ethical and privacy point of view.
How to increase trust in AI To increase trust in AI, it is essential to foster a data culture.
The report reveals that a strong data culture not only drives productivity and innovation, but also results in superior customer service.
75% of IT and analytics leaders expect an increase in investment in training and development, recognizing the critical importance of employee skills.
In a context where artificial intelligence promises to simplify various aspects of daily life, it becomes imperative to equip people with the skills necessary to evaluate the ethics and accuracy of the results generated.
As already highlighted, the effectiveness of artificial intelligence depends on the quality of the data inputs.
Consequently, fostering a data culture in which employees feel confident in dealing with data issues, are capable of using data and can identify potential issues, will result in significant benefits.
A robust and mature data base not only facilitates deeper and faster analysis, but also provides tools to interpret natural language, allowing everyone to fully benefit from the results generated by artificial intelligence.
Trust in AI grows alongside a well-established data culture: high-maturity organizations that can boast superior infrastructure, strategy and alignment compared to organizations with low data maturity are able to use AI effectively.