Recently, McKinsey released a global survey report on the state of AI. This is the third consecutive year that the report has been released. Interviews with executives and surveys of practitioners found that the gap between companies that use AI and companies that do not use AI may widen. The
survey report shows that in the field of technology and telecommunications, the use of artificial intelligence is more common than in other industries, followed by automobiles and manufacturing. More than two-thirds of the respondents said that the adoption of AI has increased their income, but less than one-quarter saw a significant impact.
The McKinsey AI State Report, together with issues related to AI applications and implementation, has conducted research on companies whose AI applications have caused EBIT (earnings before interest and taxes) growth of 20% or more in 2019. Compared with other companies, these companies may be very efficient at rating senior managers and are more likely to hire data scientists.
Compared with other companies that differ by 20% to 30% or more, high-performance companies are also more likely to have a strategic vision and AI roadmap, use AI model deployment or need to use comprehensive data when encountering the lack of data in the century. . These results appear to be consistent with the Altimeter Group survey conducted by Microsoft in early 2019, which found that half of high-growth companies plan to implement AI next year.
If there is anything surprising in the report, it is that only 16% of the respondents said that their company has developed deep learning projects beyond the experimental stage. (This is the first year McKinsey has focused on deep learning deployments.) Z1z
is also surprisingly, the report shows that companies have made little progress in dealing with the risks associated with AI deployment. Compared with the responses submitted last year, companies that took measures to mitigate such risks have increased by an average of 3% in dealing with 10 different risks (from national security and personal safety to compliance and fairness).
Cybersecurity is the only risk that most respondents said their companies are working hard to address. There are many categories that believe that the company-related AI risk is declining, including equity and fairness, from 26% in 2019 to 24% in 2020.
“Although certain risks such as personal safety only apply to specific industries, it is difficult to understand why a high percentage of respondents did not recognize the general risks.” McKinsey’s partner Roger Burkhardt (Roger Burkhardt) ) Said in the report, "Considering the attention to racial prejudice and other examples of discriminatory treatment, such as age-based positioning in job advertisements on social media, it is particularly surprising to see that this risk has hardly been mitigated or improved. "Z1z
is not surprising. The survey found that during the pandemic, the level of automation in certain industries has increased. VentureBeat found that this is true in industries such as agriculture, construction, meat packaging, and shipping. The
report reads: "Most of the high-performing respondents said that their organizations have increased their investment in AI in every major business function in response to this epidemic, while less than 30% of other respondents said The same."
McKinsey's 2020 AI State Global Survey was conducted online from June 9th to June 19th, and nearly 2,400 results were obtained, of which 48% of the respondents indicated that their companies use some form of AI. A survey conducted by McKinsey in 2019 with about the same number of business leaders found that although nearly two-thirds of companies reported increased revenue due to the use of AI, many companies are still struggling to expand their use . Another state of
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One month before McKinsey released the business survey report, Air Street Capital released its "State of Artificial Intelligence" report, which has been extended to the third year. The London-based venture capital firm found that the artificial intelligence industry is very popular when it comes to corporate financing, but its report called the concentration and calculation of artificial intelligence talent "a huge problem." Other serious problems discovered by
Air Street Capital include the continuous brain drain from academia to industry, and the reproducibility of models created by small companies. A team of 40 Google researchers also recently discovered that insufficient specifications are a major obstacle to machine learning.
Many conclusions in the report and the latest analysis of AI research papersNow, deep learning activities among large technology companies, industry leaders, and elite universities are increasingly concentrated, which has exacerbated inequality. The team behind the analysis stated that the growing "computing gap" can be resolved to a certain extent by implementing a national research cloud.
As the end of the year approaches, we can expect more reports on the state of machine learning. The AI status report released in the past two months shows various challenges, but claims that AI can help companies save costs, generate revenue and follow tried and tested best practices to succeed. At the same time, researchers are looking for solutions to the huge opportunities associated with deploying AI. Lei Feng net
