![[ITmedia Enterprise] AI won't take away jobs, but they won't be created - Gartner predicts employment in 2030](/api/img?u=https%3A%2F%2Fimage.itmedia.co.jp%2Fenterprise%2Farticles%2F2611%2F13%2Fcover_news014.jpg&w=1200&q=72&f=webp)
8.9 million people will lose their jobs, 10.6 million people will be created, and 5 million deferred jobs will be affected.
AI-generated summary
Gartner has predicted the impact that AI will have on the labor market, both in terms of creation and loss. It emphasizes that the impact varies by industry.
Gartner predicts that AI will create 10.6 million jobs and eliminate 8.9 million jobs globally by 2030, resulting in a net gain of 1.7 million jobs.
Helen Poitevin, Gartner's Distinguished Vice President Analyst, said:
“Organizations that are furthest ahead in implementing AI see it not as a replacement for labor, but as a catalyst for restructuring operations and rebalancing the capabilities of labor and technology to compete in changing markets. These organizations are ensuring that the economic value of AI extends beyond labor replacement.”
A distinctive feature of the forecast is that it shows ``deferred employment'' in addition to job losses. Gartner estimates that by 2026, AI will eliminate 2.2 million jobs and create 1.6 million jobs. An equally significant impact was the decision by management to postpone the creation and hiring of 1.3 million positions. Gartner estimates that by 2030, a total of 5 million people will experience hiring delays as executives and IT leaders postpone creating new positions.
"Jobs deferred are not the same as jobs lost; they just aren't created," said John Lovelock, distinguished vice president analyst and chief of research at Gartner.
Regarding the scale of job loss, Gartner predicts that by 2030, 0.4% to 1.8% of workers will experience job loss directly due to AI. Meanwhile, by 2030, more than 20% of workers (435.5 million people worldwide) will have to adapt to changes in the nature of their work, the way they perform their jobs, and the scope of their responsibilities.
How does the impact vary by industry?
Gartner breaks down the employment changes related to AI into three industry groups:
Mr. Poitevin commented on the differences between industries as follows:
"The impact of AI on employment will be uneven across regions, roles, and industries. The worst mistake executives and IT leaders can make is applying lessons from one industry or role to another, which can lead to poor judgment and missed goals. Each industry has unique challenges and risks that business leaders must understand and address."
AI outlook — possibilities, not facts
By 2030, over 20% of workers will have to adapt to changing job descriptions
Likely · Within years
![[ITmedia Business Online] The “cautious” Yayoi will collaborate with general-purpose AI tools. Freee and Manefo will follow in “MCP compatibility,” and what are the “accounting x AI” strategies of each company?](/api/img?u=https%3A%2F%2Fimage.itmedia.co.jp%2Fbusiness%2Farticles%2F2611%2F13%2Fcover_news031.jpg&w=320&q=72&f=webp)
Starting from December, Yayoi's cloud accounting software "Accounting Next" will be compatible with the common standard "MCP" that connects generated AI and external software. Although it is the third company after freee and Money Forward, it has a policy of carefully determining its distance from AI, such as allowing AI to register journal entries but not registering business partners.
![[ITmedia Enterprise] NEC prepares 1,435 data catalogs in one year, taking on the challenge of decision-making support using AI](/api/img?u=https%3A%2F%2Fimage.itmedia.co.jp%2Fenterprise%2Farticles%2F2610%2F30%2Fcover_news006.jpg&w=320&q=72&f=webp)
NEC has developed the "One NEC Data Platform" to realize data-driven management, and has built 1,435 data catalogs and 44 new dashboards in one year. We aim to become an AI native company in five years by utilizing the generative AI platform "NGS" and Knowledge AI. We are moving toward an "AI Ready Platform" equipped with an ontology layer that allows AI to interpret meaning.
Kando CIO and CISO of Tokyo Electric Power Company Holdings says that the company has overcome the stagnation of ``no one using it'' after introducing generative AI by reorganizing business processes and dividing the roles between humans and AI. He also mentioned the case study of the on-site support app ``Safe Now,'' an attitude that emphasizes return on investment, and the three elements necessary for change makers.
![[ITmedia Mobile] What is the difference between Pixel Tag and AirTag? How to choose a loss prevention tag that can be used with Android smartphones and can be purchased from the 1,000 yen range](/api/img?u=https%3A%2F%2Fimage.itmedia.co.jp%2Fmobile%2Farticles%2F2611%2F13%2Fcover_news044.png&w=320&q=72&f=webp)
Google released the loss prevention tag "Pixel Tag" on November 12th. It costs 5,010 yen per piece and 16,940 yen for a set of 4, and can be used on smartphones running Android 9 or later. We will introduce the difference from AirTag, points to consider when choosing a tag for Android, and recommended models such as Xiaomi Tag, UGREEN Finder Duo, and Logitech products.
Google announced the AI model "Gemini 4 Hydrogen" on November 12th, and began offering it gradually around the world. Optimized for daily coding and AI agent work, it achieved 51 points in the Artificial Analysis Intelligence Index and is approximately 2.5 times faster than the previous generation "Gemini 3.8 Flash". The context window is 1 million tokens, and the API price is $1.5 per million tokens for input and $7.5 for output. Available in Google AI Studio, Gemini API, Android Studio, Firebase AI Logic, Gemini for business, Gemini apps, Google Search, etc. The model card states that the biological and cybersecurity fields have reached a level that requires caution, but have not yet reached the critical capability level.
On November 12, Cyber Security Cloud announced that personal information such as customers' company names, names, and email addresses may have been leaked due to suspicious access to the administrative area on GitHub. One employee's GitHub authentication information was leaked and access by a third party was confirmed on November 5th. The scope of the incident is currently under investigation, and no secondary damage or impact on services has been confirmed.