While AI continues to enjoy a continuously increasing adoption in 2019, much work is still needed in order for it to create significant impact — McKinsey reveals in their released 2019 Global AI Survey paper.

Let’s look further into the main findings of this year’s survey.

Most respondents are seeing returns from AI

63 percent of the survey respondents reported revenue increases in their business units which adopted AI tech. McKinsey said that the growth in revenue is concentrated on three business functions:

  1. Marketing and development
  2. Product and service development
  3. Supply chain management (SCM)

Apart from this, 43 percent of the respondents also reported lower costs due to AI adoption.

With this, we can see that AI appears to be quite a useful addition in the existing tools of companies.

AI adoption is increasing in nearly all industries, but capabilities vary

58 percent of the respondents reported employing at least once AI capability in at least one business function. This is an increase from last year’s 47 percent.

However, the gap between the high performers and other companies remains wide. High performers reported an average of 11 cases of AI use. This is in stark contrast with the average of three cases of AI uses in other companies.

This gap might become wider in the succeeding years since a large proportion of high performers also plan to increase their investment in AI in the next three years.

AI high performers tend to engage in value-capturing practices

McKinsey identified several core practices that are necessary to capture value at scale when it comes to AI:

  • Aligning AI strategy with corporate strategy
  • Investing in talent
  • Collaboration
  • Applying strong data practices
  • Giving sufficient training for staff and tech teams

High performers consistently have a higher proportion adopting each practice by significantly large margins.

A minority of companies acknowledge most AI risks—fewer mitigate them

Only 41 percent of the respondent organizations reported that their organization identify and prioritize AI-related risks.

McKinsey cited ten risks in adopting AI:

  1. Cybersecurity
  2. Regulatory compliance
  3. Personal privacy
  4. Explainability
  5. Workforce displacement
  6. Organization reputation
  7. Equity and fairness
  8. Physical safety
  9. National security
  10. Political stability

Out of these 10, only cybersecurity and regulatory compliance are deemed relevant by the majority of the respondents. It is clear that there is still a lot of education needed when it comes to the risks surrounding the adoption of AI.

More expect AI to cause workforce decreases than increases, with variances across functions

Among the respondents, McKinsey found that in the next three years,

  • 34% of AI-adopting companies expect a decrease in employees, at least by 10 percent
  • 21 % expect an increase, at least by ten percent
  • 28% expect that AI adoption will have little impact on the size of the workforce, only by around three percent in either direction

Slowly, the opinion of the companies is shifting towards AI having some sort of impact on the future workforce.

Greater emphasis on workforce retraining is likely

83 percent of the companies expect at least some of their workforce to be retrained in the next three years.

This might also explain why companies do not see AI decimating the workforce since they are placing their focus on retraining.

Some of the high performers realize the power of AI and are making huge strides to reach new heights in AI adoption. Hopefully, this will also prod the lagging companies to catch up.

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