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Report Reveals Data Quality Challenges in AI Implementation

As the world continues to embrace artificial intelligence (AI) at scale, AvePoint, in collaboration with the Association for Intelligent Information Management (AIIM) and the Centre for Information Policy Leadership (CIPL), has released an AI and Information Management Report. The study, which surveyed over 750 digital workplace leaders across various industries, highlights the critical challenges organizations face when implementing AI, with data quality issues topping the list.

The report's findings underscore the importance of mature information management (IM) strategies in realizing the benefits of AI. Organizations with more advanced IM strategies are 1.5 times more likely to reap the advantages of AI compared to those with less mature approaches. However, the survey reveals that fewer than half of the organizations are confident in their ability to use AI safely, with concerns about data privacy, security, and quality being prevalent.

Marcus Fowler, CEO of Darktrace Federal, emphasizes the need for a comprehensive understanding of "normal" behavior across networks and IT environments to ensure the safe and effective deployment of AI tools. "In order to ensure the safe and effective deployment of these AI tools in the workplace, it is vital that AI officers and their associated teams have a firm understanding of 'normal' behavior across their networks and IT environments," Fowler stated.

Fowler also highlighted the importance of prioritizing data privacy, control, and trust in AI implementations. He stressed the significance of leadership influence in maintaining the effectiveness of these areas and the need for organizations to establish trust in AI-focused roles to encourage collaboration and strengthen security postures.

Despite the challenges, the report indicates that organizations are increasingly investing in AI, with 65% using ChatGPT and 40% using Google Gemini. However, the survey also reveals contradictions in organizations' perceptions of readiness for AI compared to their reality, with many experiencing gaps in data readiness and information management that could pose obstacles to safe and successful AI implementation.

As the volume of data managed by organizations continues to grow, with 64% handling at least 1 petabyte and 41% managing at least 500 petabytes, the need for automation in IM strategies becomes more pressing. Yet, only 29% of organizations currently use automation in most aspects of their IM strategy.

The AI and Information Management Report serves as a wake-up call for organizations to address the challenges of data quality and information management to unlock the full potential of AI and ensure its safe and effective use in the digital workplace.

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