Rohit Anabheri, CEO of Sakesh Solutions, charts AI adoption for SMEs as well as strategies for growth and innovation. Read Rohit Anabheri's full executive profile here.
In the age of advanced data analytics and artificial intelligence , organizations are continuously confronted with new and increasingly complex challenges of data legitimacy. The proliferation of AI-generated
hallucinations and other deceptive outputs can lead not only to distorted business insights but also to the erosion of basic trust in AI technologies. In this article, I'll explain why it is important to address these issues today and provide concrete guidelines for enterprise decision-makers to improve the reliability and effectiveness of their AI systems.With the rapid adoption of AI across all sectors—most recently supercharged by large language models and powered by sophisticated technologies for data processing and analysis—companies must consider the accuracy of data and AI-generated outputs to be a pressing issue.
These steps not only improve the quality of AI outputs, they also increase the trustworthiness of AI among users and stakeholders and set the stage for more sustainable and ethical AI use in business.
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