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RESEARCH & RESOURCES

Appen’s Annual State of AI and Machine Learning Report Identifies Data Quality Issues

Appen partners with the Harris Poll to uncover bottlenecks, challenges, and opportunities for practitioners in the AI industry.

Note: TDWI’s editors carefully choose vendor-issued press releases about new or upgraded products and services. We have edited and/or condensed this release to highlight key features but make no claims as to the accuracy of the vendor's statements.

Appen Limited, a leading provider of data for the AI life cycle, released its eighth annual State of AI and Machine Learning report. This year’s report reveals that sourcing quality data is an obstacle to creating AI.

According to the report’s findings, 51 percent of participants agree that data accuracy is critical to their AI use case. To successfully build AI models, organizations need accurate and high-quality data. Unfortunately, business leaders and technologists report a significant gap between the ideal and reality in achieving data accuracy.

Appen’s research also found that companies are shifting their focus to responsible AI and maturing in their use of AI. More business leaders and technologists are focusing on improving the data quality behind AI projects in order to promote more inclusive data sets and, as a result, unbiased and better AI. In fact, 80 percent of respondents stated data diversity is extremely important or very important, and 95 percent agree that synthetic data will be a key player when it comes to creating inclusive data sets.

“This year’s State of AI report finds that 93 percent of respondents believe responsible AI is the foundation of all AI projects,” said Mark Brayan, CEO at Appen. “The problem is [that] many are facing the challenges of trying to build great AI with poor data sets, and it’s creating a significant roadblock to reaching their goals.”

Additional key takeaways from the 2022 State of AI Report include:

  • Sourcing: 42 percent of technologists say the data sourcing stage of the AI life cycle is very challenging
  • Evaluation: 90 percent are retraining their models more than quarterly
  • Adoption: Business leaders are split down the middle about whether their organization is ahead of (49 percent) or even with (49 percent) others in their industry

“The majority of AI efforts are spent managing data for the AI life cycle, which means it is an incredible undertaking for AI leads to handle alone -- and is the area many are struggling with,” said Sujatha Sagiraju, chief product officer at Appen. “Sourcing high-quality data is critical to the success of AI solutions, and we are seeing organizations emphasize the importance of data accuracy.”

The report was sourced from 504 interviews collected via The Harris Poll online survey of IT decision makers, business leaders and managers, and technical practitioners from the U.S., U.K., Ireland, and Germany.

To learn more, download the full 2022 State of AI and Machine Learning report.

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