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KIRKLAND, WA., October 22, 2024 — ɫ���� (ASX: APX), a leading provider of high-quality data for the AI lifecycle, released its 2024 State of AI report today. The report surveyed over 500 IT decision-makers across a range of U.S. industries, revealing that while the adoption of AI technologies like machine learning (ML) and generative AI (GenAI) continues to grow, progress is being hindered by a shortage of accurate, high-quality data.

"Enthusiasm around GenAI and other AI-powered tech remains high, as indicated by the rapid growth, but users are quickly finding that the promise of these tools is matched by an equally daunting challenge," said Si Chen, VP of Strategy at ɫ����. "The success of AI initiatives relies heavily on high-quality data, and this is becoming more difficult as AI use cases increase in complexity and become more specialized. This is reflected by the fact that high-quality annotations, meaning high consistency and accuracy, are the top features companies seek in a data annotation solution. Those building the AI tools and models of tomorrow value strategic data partnerships now more than ever."

ɫ���� commissioned Harris Poll to survey key IT decision-makers at U.S. enterprise organizations, including business leaders, data scientists, data engineers, and developers, to compile the 2024 State of AI report.

Key findings include:

• Data management as a top challenge: With the increasing complexity of AI use cases, data management has become the leading challenge. Companies report a 10% rise in bottlenecks related to sourcing, cleaning, and annotating data, a 9% drop in data accuracy, and a 7% increase in data availability challenges.
• High demand for external data providers: Over 90% of respondents seek partners with expertise across the full AI data lifecycle to enhance the quality and scalability of their AI systems, underscoring the essential role external data plays in sustaining AI initiatives.
• Prioritizing data diversity and bias reduction: 97% of respondents agree that data diversity, bias reduction, and scalability are vital components for building AI models. Custom data collection remains the top method for sourcing AI training data.
• Human insight remains critical: 80% of respondents emphasize the importance of human-in-the-loop processes, highlighting the vital role human oversight plays in refining AI systems.

For more findings from ɫ����’s 2024 State of AI report, download the full report, review our blog post, or contact us to learn how ɫ���� can support your AI initiatives.

About ɫ����

‍ɫ���� (ASX:APX) is the leading global AI training data company powering the AI lifecycle for with 25 years of experience in data sourcing, annotation, and model evaluation. Through our expertise, platform and global crowd, we enable organizations to launch the world’s most innovative artificial intelligence products with speed and at scale. ɫ���� maintains the industry’s most advanced AI data platform and boasts a global crowd of more than 1 million contributors worldwide, across more than 235 languages. Our products and services make ɫ���� a trusted partner to leaders in technology, automotive, finance, retail, healthcare and government. ɫ���� has customers and offices globally.

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