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Appen’s State of AI Annual Report Reveals Significant Industry Growth

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Appen Limited (ASX: APX), the leading provider of high-quality training data for organizations that build effective AI systems at scale, today announced its annual State of AI Report for 2020.

The State of AI 2020 report is the output of a cross-industry, large-organization study of senior business leaders and technologists. The survey intended to examine and identify the main characteristics of the expanding AI and machine learning landscape by gathering responses from AI decision-makers.

There were multiple key takeaways:

  • While nearly 3 out of 4 organizations said AI is critical to their business, nearly half feel their organization is behind in their AI journey.
  • AI Budgets greater than $5M doubled YoY
  • An increasing number of enterprises are getting behind responsible AI as a component to business success, but only 25% of companies said unbiased AI is mission-critical.
  • 3 out of 4 organizations report updating their AI models at least quarterly, signifying a focus on the model’s life after deployment.
  • The gap between business leaders and technologists continues, despite their alignment being instrumental in building a strong AI infrastructure.
  • Despite turbulent times, more than two-thirds of respondents do not expect any negative impact from COVID-19 on their AI strategies.

One of the key findings is that nearly half of those who responded feel their company is behind in their AI journey, this suggests a critical gap exists between the strategic need and the ability to execute.

Lack of data and data management was reported as a main challenge, this includes training data which is foundational of AI and ML model deployments, so, unsurprisingly, 93% of companies report that high-quality training data is important to successful AI.

Organizations also reported using 25% more data types (text, image, video, audio, etc.) in 2020, compared to 2019. Not only are models getting more frequent updates, but teams are using increasingly more data types, and that will translate in an increasing need for investment in reliable training data.

One key indicator of exponential growth of AI was the rapid YoY growth in AI initiates. In 2019, only 39% of executives owned AI initiatives. In 2020, executive ownership of AI skyrocketed to 71%. With this increase in executive ownership, the number of organizations reporting budgets greater than $5M also doubled.

Global cloud providers gained significant traction as data science and ML tools compared to 2019. This may be due to increased budget and executive oversight. What is even more impressive is the increase of respondents who are reporting using global cloud machine learning providers which are identified as: Microsoft Azure (49%), Google Cloud (36%), IBM Watson (31%), AWS (25%), and Salesforce Einstein (17%). Each of these front runners saw double-digit adoption increases vs 2019, proving that as more companies are moving to scale, they’re looking for solutions that can scale with them.

Something of which AI developers may want to take note of is the variability in languages used to build models has also shifted from 2019. While Python remains the most used language in both 2019 and 2020, SQL and R were the second and third most commonly used language in 2019. However, in 2020, Java, C/C++, and JavaScript gained significant traction. Python, R, and SQL are often indicative of the pilot stage, while Java, C/C++, and JavaScript are more production stage languages.

To learn more, we recommend downloading the entire State of AI and Machine Learning Report.

Antoine Tardif is a Futurist who is passionate about the future of AI and robotics. He is the CEO of BlockVentures.com, and has invested in over 50 AI & blockchain projects. He is the Co-Founder of Securities.io a news website focusing on digital assets, digital securities and investing. He is a founding partner of unite.AI & a member of the Forbes Technology Council.