O’Reilly, a training and learning platform, conducts an annual survey regarding the adoption of AI in companies. Last December and January, it asked the recipients of its information newsletters to answer a questionnaire on this subject. Participation was less than last year, perhaps due to the end of year holidays, the highlight is that the responses are similar to those of 2021, although after verification, they only come from 10% of the same people.
This report on enterprise AI adoption was written by Mike Loukides, vice president of content strategy for O’Reilly Media, Inc. He has a particular interest in programming languages, Unix, data and artificial intelligence, ethics, the future of programming… In this report, he examines the different ways in which artificial intelligence is implemented, the techniques, tools used by companies in order to better understand the results its adoption has brought over the past year.
The 2022 figures show that the percentage of organizations reporting AI applications in production, generating revenue in production, has remained constant over the past two years, at 26%, which according to Mike Loukides indicates that the ‘AI has taken a step following the hype. He declares :
“For years, AI has been at the center of the tech world. Now that the hype has died down, it’s time for AI to prove that it can deliver real value, whether it’s cost savings, increased productivity for businesses, or creating applications that can generate real value for human lives. This will undoubtedly require practitioners to develop better ways to collaborate between AI systems and humans, and more sophisticated methods to train AI models that can circumvent the biases and stereotypes that plague decision-making. human. »
The adoption of AI
31% of companies say they do not use AI (compared to 13% in 2021), 43% assess its adoption and 26% have implemented AI applications.
The main increase, from 18 to 31%, of respondents from the manufacturing industry having AI is in Oceania.
Next, North America and Europe had the highest percentages of respondents: 27%, followed by Asia (24%) and South America (22%). As for Africa, it has only 13% of respondents adopting AI in manufacturing (13%) but the highest number of non-users (42%).
A lack of governance
Many organizations lack AI governance. Of the 26% of respondents with AI products in production, only 49% have a governance plan in place to oversee how projects are created, measured and observed (49%) vs. 51% for those who do not have.
When it comes to risk assessment, unexpected outcomes (68%) remained the top concern for mature organizations, followed closely by model interpretability and model degradation (61% each). Confidentiality (54%), fairness (51%) and security (42%) are the least cited risks by organizations.
The key figures of the report concerning mature practices
- TensorFlow and scikit-learn (both 63%) are the most used AI tools, followed by PyTorch (50%), Keras (40%) and AWS SageMaker (26%).
- AutoML tools are used to automatically generate models in 67% of organizations compared to 49% of organizations the previous year, an increase of 37%.
- A 20% increase in the use of automated tools for deployment and monitoring is also seen. The most used tools are MLflow (26%), Kubeflow (21%) and TensorFlow Extended (TFX, 15%).
- The top bottlenecks to AI adoption are lack of skilled people and lack of data or data quality issues (both at 20%).
- Organizations with mature practices and those currently evaluating AI agree that a lack of skilled people is a significant barrier to AI adoption, although only 7% of respondents in each group cited it as their most important problem. Experts in ML modeling and data science (45%), data engineering (43%), and managing a set of business use cases (40%) were cited the most.
- The retail and financial services sectors have the highest percentage of mature practices (37% and 35%, respectively). Education and government (9%) have the lowest percentage of respondents but are the most considering AI adoption (46% and 50%, respectively).
Laura Baldwin, President of O’Reilly, concludes:
“While AI adoption is slowing, it is certainly not stagnating. There are significant venture capital investments in AI, with 20% of all funds going to AI companies. This likely means AI growth is plateauing in the near term, but these investments will pay off later in the decade. In the meantime, companies should not lose sight of the purpose of AI: to improve people’s lives. The AI community must take the necessary steps to create applications that generate real human value, or we risk entering a period of reduced AI funding. »
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O’Reilly Releases 2022 Enterprise AI Adoption Report
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