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A significant 54% of Indian IT leaders view data security gaps as major obstacles to AI adoption. The survey conducted by Hitachi Vantara highlights concerns over potential data breaches and the challenges of maintaining data quality for AI initiatives. Despite the rapid growth of AI technologies, many enterprises are struggling to align their practices with the demands of AI, jeopardizing long-term success.
The findings indicate that high-quality data is crucial for successful AI projects, with 58% of leaders emphasizing its importance. Concerns about ethical issues, skilled workforce shortages, and sustainability further complicate the AI landscape in India. Addressing these challenges requires a strategic focus on modern infrastructure that prioritizes data quality and cybersecurity.
• 54% of IT leaders cite data security as a barrier to AI success.
• 58% agree high-quality data is essential for AI project success.
Data security refers to the protection of digital information from unauthorized access or corruption, which is a primary concern for IT leaders in AI adoption.
Data quality involves the accuracy and reliability of data, which is critical for training AI systems effectively.
Cybersecurity encompasses measures taken to protect computer systems from cyber threats, which is a top priority for enterprises implementing AI.
Hitachi Vantara specializes in data storage and infrastructure solutions, playing a key role in addressing data quality and security challenges in AI.
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