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One chart shows how the 'magnificent 7' have dominated the stock market in 2023.

The S&P 500 ( ^GSPC ) has never been this top-heavy.

The "Magnificent Seven" tech stocks — Apple ( AAPL ), Alphabet ( GOOGL , GOOG ), Microsoft ( MSFT ), Amazon ( AMZN ), Meta ( META ), Tesla ( TSLA ), and Nvidia ( NVDA ) — make up 29% of the S&P 500's market cap.

And a chart in Goldman Sachs' 2024 US Equity Outlook shows that's the largest portion of S&P 500 market cap ever dominated by just seven stocks.

That perspective helps explain a second chart from Goldman that shows the Magnificent Seven have gained 71% while the other 493 stocks have added just 6%. Given the benchmark's market cap distribution, which allows larger stocks to contribute more to the index's movements, the S&P 500 has added about 19% this year.

Goldman Sachs' equity research team led by chief US equity strategist David Kostin described the Magnificent Seven's outperformance as a "defining feature of the equity market in 2023." And perhaps rightfully so.

Two other charts included in Goldman's outlook show how the Magnificent Seven have outperformed the other 493 stocks in key metrics that typically drive stock performance.

From 2013 to 2019, the Magnificent Seven stocks grew at a compound annual growth rate of 15% compared to a 2% growth rate from the rest of the pack. That margin narrowed in the past two years to 18% and 15% respectively, but Goldman sees it widening again in the coming years. From 2023 to 2025, Goldman sees the Magnificent Seven growing at a compound annual growth rate of 11% compared to a 3% rate for the rest of the S&P 500.

The Magnificent Seven's net profit   margin also outperforms, where its 19% margins are above the 9.8% for the rest of the companies. Not to mention, the long-term earnings per share growth expectations are 17% for the Seven while that number sits at 9% for the other companies in the index.

"From a fundamental perspective, in recent years the trajectory of earnings has explained the performance of the Magnificent 7 relative to the rest of the market," Kostin wrote. "The outperformance of the Magnificent 7 this year has coincided with a rebound in margins and earnings that has outpaced the weakness across the rest of the market."

He added: "Consensus expects the Magnificent 7 will continue to deliver faster growth than the rest of the index."

Goldman sees the path forward for the Magnificent Seven stocks to likely be higher, too, but that doesn't make it the ideal trade for 2024 given the group's rise over the last year.

"The 7 stocks have faster expected sales growth, higher margins, a greater re-investment ratio, and stronger balance sheets than the other 493 stocks and trade at a relative valuation in line with recent averages after accounting for expected growth," Kostin wrote. "However, the risk/reward profile of this trade is not especially attractive given elevated expectations."

Josh Schafer is a reporter for Yahoo Finance.

Click here for the latest stock market news and in-depth analysis, including events that move stocks

Read the latest financial and business news from Yahoo Finance

Wall Street Analysts Think Goldman (GS) Is a Good Investment: Is It?

I nvestors often turn to recommendations made by Wall Street analysts before making a Buy, Sell, or Hold decision about a stock. While media reports about rating changes by these brokerage-firm employed (or sell-side) analysts often affect a stock's price, do they really matter?

Before we discuss the reliability of brokerage recommendations and how to use them to your advantage, let's see what these Wall Street heavyweights think about Goldman Sachs (GS).

Goldman currently has an average brokerage recommendation (ABR) of 1.48, on a scale of 1 to 5 (Strong Buy to Strong Sell), calculated based on the actual recommendations (Buy, Hold, Sell, etc.) made by 23 brokerage firms. An ABR of 1.48 approximates between Strong Buy and Buy.

Of the 23 recommendations that derive the current ABR, 17 are Strong Buy and one is Buy. Strong Buy and Buy respectively account for 73.9% and 4.4% of all recommendations.

Brokerage Recommendation Trends for GS

Check price target & stock forecast for Goldman here>>>

While the ABR calls for buying Goldman, it may not be wise to make an investment decision solely based on this information. Several studies have shown limited to no success of brokerage recommendations in guiding investors to pick stocks with the best price increase potential.

Are you wondering why? The vested interest of brokerage firms in a stock they cover often results in a strong positive bias of their analysts in rating it. Our research shows that for every "Strong Sell" recommendation, brokerage firms assign five "Strong Buy" recommendations.

In other words, their interests aren't always aligned with retail investors, rarely indicating where the price of a stock could actually be heading. Therefore, the best use of this information could be validating your own research or an indicator that has proven to be highly successful in predicting a stock's price movement.

With an impressive externally audited track record, our proprietary stock rating tool, the Zacks Rank, which classifies stocks into five groups, ranging from Zacks Rank #1 (Strong Buy) to Zacks Rank #5 (Strong Sell), is a reliable indicator of a stock's near -term price performance. So, validating the Zacks Rank with ABR could go a long way in making a profitable investment decision.

ABR Should Not Be Confused With Zacks Rank

In spite of the fact that Zacks Rank and ABR both appear on a scale from 1 to 5, they are two completely different measures.

Broker recommendations are the sole basis for calculating the ABR, which is typically displayed in decimals (such as 1.28). The Zacks Rank, on the other hand, is a quantitative model designed to harness the power of earnings estimate revisions. It is displayed in whole numbers -- 1 to 5.

It has been and continues to be the case that analysts employed by brokerage firms are overly optimistic with their recommendations. Because of their employers' vested interests, these analysts issue more favorable ratings than their research would support, misguiding investors far more often than helping them.

In contrast, the Zacks Rank is driven by earnings estimate revisions. And near-term stock price movements are strongly correlated with trends in earnings estimate revisions, according to empirical research.

Furthermore, the different grades of the Zacks Rank are applied proportionately across all stocks for which brokerage analysts provide earnings estimates for the current year. In other words, at all times, this tool maintains a balance among the five ranks it assigns.

Another key difference between the ABR and Zacks Rank is freshness. The ABR is not necessarily up-to-date when you look at it. But, since brokerage analysts keep revising their earnings estimates to account for a company's changing business trends, and their actions get reflected in the Zacks Rank quickly enough, it is always timely in indicating future price movements.

Is GS Worth Investing In?

Looking at the earnings estimate revisions for Goldman, the Zacks Consensus Estimate for the current year has increased 3.3% over the past month to $36.57.

Analysts' growing optimism over the company's earnings prospects, as indicated by strong agreement among them in revising EPS estimates higher, could be a legitimate reason for the stock to soar in the near term.

The size of the recent change in the consensus estimate, along with three other factors related to earnings estimates, has resulted in a Zacks Rank #1 (Strong Buy) for Goldman. You can see the complete list of today's Zacks Rank #1 (Strong Buy) stocks here >>>>

Therefore, the Buy-equivalent ABR for Goldman may serve as a useful guide for investors.

To read this article on Zacks.com click here.

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BHP shares dip after mining giant walks from $49 bln Anglo takeover deal

The Australian-listed shares of BHP Group fell 1.5% on Thursday after the mining giant walked away from its $49 billion plan to take over rival Anglo American , ending for now its six-week pursuit.

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US Daily: Remote Work, Three Years Later

Remote work, three years later.

The share of US workers working from home (WFH) at least part of the week has stabilized at around 20-25%, below its peak of 47% at the height of the pandemic but well above the pre-pandemic average of 2.6%. In this US Daily , we discuss the implications of WFH for office demand, consumer spending, and productivity.

The persistence of WFH reflects both structural and cyclical factors. Structurally, the pandemic-related lockdowns spurred technological innovations that make teleworking easier, and surveys show that workers now place more value on being able to work from home. Cyclically, tight labor markets over the last two years have made employers more willing to allow employees to work remotely. Using state-level data, we find that a 1pp increase in the job-worker gap leads to a 0.3pp increase in the share of remote job postings. This implies that further labor market rebalancing should reduce the share of remote job postings from 11.5% to 10.8% in the next 3 years.

WFH has reduced office utilization rates but has not yet led to substantial declines in office occupancy rates because most firms are locked in long duration leases. Going forward, 17% of all office leases are scheduled to expire by the end of 2024, 47% between 2024-2029, and the rest after 2030. Our baseline estimates suggest that remote work will likely exert 0.8pp of upward pressure on the office vacancy rate by 2024, an additional 2.3pp over 2025-2029, and another 1.8pp in 2030 and beyond, though this is likely to be partially offset by a decline in new construction.

The shift to remote work has also changed the geographic distribution of retail spending and employment. While spending on services that require face-to-face contact has now fully recovered in the aggregate, the recovery has been skewed towards suburban areas and away from city centers where traditional office-related activities take place.

Economic studies disagree on the productivity effects of WFH, with estimates ranging from -19% to +13% and compared to our baseline of +3% for pandemic productivity gains more generally. The lack of consensus across these studies is likely driven by differences in how they measure productivity and the types of tasks and industries they study. More recent studies that measure productivity through complex performance metrics in industries involving high-cognitive tasks reveal more negative effects.

The share of US workers working from home (WFH) at least part of the week has declined from its peak and stabilized at an elevated level. Combining various data sources, we estimate that the share of US workers performing at least some work from home remains at 20-25% ( Exhibit 1 ), below its peak of 47% at the height of the pandemic but well above the pre-pandemic average of 2.6%.

Exhibit 1 : The Share of Workers Working at Least Partly Remotely Has Declined by Roughly Half From Its Peak to Around 20-25%

*May 2020-Sep 2022 is based on the average of WFH Research, IPSOS, CPS. We use the implied linear relationship between WFH Research and the average to extrapolate for months after Sep 2022.

Source: WFH Research, IPSOS, Current Population Survey, Goldman Sachs Global Investment Research

The WFH rate varies across industries ( Exhibit 2 ). The share of employees working remotely remains remarkably elevated in industries like information that require less face-to-face interaction, while it is much lower in contact-heavy sectors like retail and hospitality. As of July 2023, 16% of workers are in hybrid roles and 8% are in fully remote roles, suggesting that the hybrid work model remains the more prevalent option across industries relative to the fully remote model.

Exhibit 2 : The Work From Home Rate Varies Across Industries

Source: Goldman Sachs Investment Research, WFH Research

We suspect both structural and cyclical factors are driving the persistence of remote work.

The pandemic caused several structural changes that have made remote work appealing to both firms and workers. The pandemic lockdowns spurred a wave of technological innovations that made teleworking easier and more widespread. The onset of remote work allowed workers to relocate away from offices with little to no short-term consequences, but these workers now face higher costs of returning to offices due to longer or more costly commutes. [ 1 ] At the same time, survey data also shows that workers prefer the flexibility and work-life balance of remote work, signaling a lasting shift in work environment preferences. [ 2 ]

Cyclical labor market tightness has also contributed to the persistence of remote work. The share of remote job openings increased rapidly with the onset of the pandemic and is now above 10%, roughly 2.5 times its pre-pandemic level (left-hand side of Exhibit 3 ). Using state-level panel data, we estimate that a 1pp increase in our jobs-worker gap is associated with a 0.3pp increase in remote work postings as a share of the local labor force, similar to our global economics team’s estimate based on cross-country data . Going forward, we expect that further labor market rebalancing will modestly weaken firms’ incentive to provide the remote work benefit and lead to a decline in the remote share of job openings from 11.5% to 10.8% in the next 3 years.

Exhibit 3 : Firms Continue to Offer Remote Work Positions and Are More Likely to Do So in Tight Labor Markets

Source: Lightcast, WFH Research, Goldman Sachs Global Investment Research

The persistence of remote work has implications for office demand, consumption patterns, and productivity.

Remote work has depressed office utilization. Indeed, data from Kastle Systems tracking building access swipes across 10 major US cities shows that the average office utilization remains half of the pre-pandemic level (dark blue line on the left-hand side of Exhibit 4 ). But the depressed office utilization rates have not yet translated into significant declines in occupancy rates by commercial tenants, with the CoStar data showing a small drop from 90% to 86% in the past 3 years (light blue bars on the left-hand side of Exhibit 4 ).

The extent to which the high WFH rate translates into a higher office vacancy rate depends on (1) how frequently firms can renew their lease contracts, and (2) how much firms reduce their office demand at the time of renewal. First, the duration of lease terms in the office market is quite long, on average 4-7 years, according to a report by Compstak. For the inventory of office spaces as of August 2023, 17% is scheduled to expire by the end of 2024, 11% expires in 2025, and more than 35% expires after 2030. The lock-in effect of long lease duration limits firms’ ability to adjust office demand in the near term.

Exhibit 4 : Elevated WFH Results in Lower Utilization of Office Space, but Tenant Occupancy Rate Remains High Due to the Long Duration of Most Leases

Source: CoStar, Kastle, Compstak

The second factor is how sensitive firms’ office demand is given the current remote work rate. A recent study using lease-level data finds that a 10% increase in the remote work share leads to a 4-5% reduction in office demand at the time of lease renewal. Combing these two factors, we estimate the remote work induced office vacancies for the next 10 years ( Exhibit 5 ).

Our baseline analysis assuming further labor market rebalancing shows that remote work will likely exert 0.8pp of upward pressure on the office vacancy rate by 2024, an additional 2.3pp over 2025-2029, and another 1.8pp in 2030 and beyond. This is equivalent to an increase in vacant office space by 46 million sqft at the end of 2024, an additional 125 million sqft over 2025-2029, and another 96 million sqft in 2030 and beyond, a sizable impact compared to the 49 million sqft of new office construction completed in 2022. The increased vacant space from remote work is likely to crowd out new investment in office structures by $6.4 billion in 2024 and $6.0 billion in 2025. [ 3 ] We estimate the combined drag on annual GDP growth is likely to be small, with a decline of 0.03pp in 2024 and in 2025.

Exhibit 5 : Office Vacancy Rates Will Rise if WFH Rates Stay Elevated

The projection uses GS forecasted labor market rebalancing for 2023-2026. For horizons that extend beyond our forecasts, we assume the labor market tightness stays unchanged. The vacancy rate is imputed using 2023 office inventory data from the Cushman & Wakefield market report.

Source: Goldman Sachs Global Investment Research

Real spending on services that involve face-to-face contact has mostly recovered to its pre-pandemic level (left-hand side of Exhibit 6 ). Categories associated with “fun” activities such as food and accommodation, recreation, and transportation have rebounded strongly, while spending on less “fun” activities such as personal care, laundry and clothing services remains depressed.

While the aggregate spending in these service categories has rebounded, the prevalence of remote work has skewed the recovery away from downtown where traditional office activities take place. The right-hand side of Exhibit 6 shows that both foot traffic at retail and recreation sites—a good proxy for consumer spending—and employment in retail services are much higher in suburban areas than in city centers.

Exhibit 6 : Real Spending on Services Has Rebounded, but Recovery Is Skewed Away From Downtown Office Areas

Our sample includes Austin, Chicago, Washington DC, Dallas, Houston, Los Angeles, New York, Philadelphia, San Francisco, and San Jose, where the Kastle and Costar office occupancy data are available.

Source: Department of Commerce, Google Mobility Report, Department of Labor, Goldman Sachs Global Investment Research

In theory, WFH could either lower or raise productivity. On the one hand, remote work may lower productivity by reducing workers’ ability to learn from their peers, interfering with workers’ ability to focus on work-related tasks, and reducing creativity and innovation. [ 4 ] On the other hand, WFH may increase workers’ productivity by offering shorter commuting times, more flexible scheduling, and a quieter working environment. [ 5 ] Firms can also repurpose office-related expenses to other more productive uses. [ 6 ] The technological innovations spurred by the shift to remote work could generate positive spillover effects throughout the economy.

In previous research, we found that WFH adoption was positively correlated with post-pandemic productivity outcomes in the industry cross-section. This cautions against a “return to normal” explanation of last year’s productivity weakness. However, economic studies disagree on the productivity effects of remote work ( Exhibit 7 ). The lack of consensus is likely driven by differences in how the studies measure productivity and the types of tasks and industries they study. Earlier work that used survey data with a self-assessed measure of productivity or experimental evidence in an industry that involved routine tasks (e.g. call centers) tended to find positive impacts of remote work. More recent studies that measure productivity through complex performance metrics and draw evidence from industries involving high-cognitive tasks (e.g. IT services) reveal more negative effects. One limitation of the academic studies is that they have largely focused on how remote work can affect productivity through changing workers’ performance. But remote work can also have effects on economy-wide productivity through other channels, such as helping firms reduce office expenses and spurring technological innovations. In previous research, we estimated that remote work and other pandemic changes boosted private-sector productivity by roughly 3% once these channels are considered (see here and here ), though we continue to see considerable uncertainty around these estimates.

Exhibit 7 : Estimates of the Impact of Remote Work on Productivity From Economic Studies

We thank Elsie Peng and Jessica Rindels for their work on this report.

Investors should consider this report as only a single factor in making their investment decision. For Reg AC certification and other important disclosures, see the Disclosure Appendix , or go to www.gs.com/research/hedge.html .

Disclosure Appendix

We, Jan Hatzius, Alec Phillips, David Mericle, Spencer Hill, CFA, Ronnie Walker, Tim Krupa and Manuel Abecasis, hereby certify that all of the views expressed in this report accurately reflect our personal views, which have not been influenced by considerations of the firm's business or client relationships.

Unless otherwise stated, the individuals listed on the cover page of this report are analysts in Goldman Sachs' Global Investment Research division.

Disclosures

Regulatory disclosures, disclosures required by united states laws and regulations.

See company-specific regulatory disclosures above for any of the following disclosures required as to companies referred to in this report: manager or co-manager in a pending transaction; 1% or other ownership; compensation for certain services; types of client relationships; managed/co-managed public offerings in prior periods; directorships; for equity securities, market making and/or specialist role. Goldman Sachs trades or may trade as a principal in debt securities (or in related derivatives) of issuers discussed in this report.

The following are additional required disclosures: Ownership and material conflicts of interest:  Goldman Sachs policy prohibits its analysts, professionals reporting to analysts and members of their households from owning securities of any company in the analyst's area of coverage.   Analyst compensation:  Analysts are paid in part based on the profitability of Goldman Sachs, which includes investment banking revenues.  Analyst as officer or director:  Goldman Sachs policy generally prohibits its analysts, persons reporting to analysts or members of their households from serving as an officer, director or advisor of any company in the analyst's area of coverage.   Non-U.S. Analysts:  Non-U.S. analysts may not be associated persons of Goldman Sachs & Co. LLC and therefore may not be subject to FINRA Rule 2241 or FINRA Rule 2242 restrictions on communications with subject company, public appearances and trading securities held by the analysts. 

Additional disclosures required under the laws and regulations of jurisdictions other than the United States

The following disclosures are those required by the jurisdiction indicated, except to the extent already made above pursuant to United States laws and regulations. Australia:  Goldman Sachs Australia Pty Ltd and its affiliates are not authorised deposit-taking institutions (as that term is defined in the Banking Act 1959 (Cth)) in Australia and do not provide banking services, nor carry on a banking business, in Australia. This research, and any access to it, is intended only for "wholesale clients" within the meaning of the Australian Corporations Act, unless otherwise agreed by Goldman Sachs. In producing research reports, members of Global Investment Research of Goldman Sachs Australia may attend site visits and other meetings hosted by the companies and other entities which are the subject of its research reports. In some instances the costs of such site visits or meetings may be met in part or in whole by the issuers concerned if Goldman Sachs Australia considers it is appropriate and reasonable in the specific circumstances relating to the site visit or meeting. To the extent that the contents of this document contains any financial product advice, it is general advice only and has been prepared by Goldman Sachs without taking into account a client's objectives, financial situation or needs. A client should, before acting on any such advice, consider the appropriateness of the advice having regard to the client's own objectives, financial situation and needs. A copy of certain Goldman Sachs Australia and New Zealand disclosure of interests and a copy of Goldman Sachs’ Australian Sell-Side Research Independence Policy Statement are available at: https://www.goldmansachs.com/disclosures/australia-new-zealand/index.html .  Brazil:  Disclosure information in relation to CVM Resolution n. 20 is available at https://www.gs.com/worldwide/brazil/area/gir/index.html . Where applicable, the Brazil-registered analyst primarily responsible for the content of this research report, as defined in Article 20 of CVM Resolution n. 20, is the first author named at the beginning of this report, unless indicated otherwise at the end of the text.  Canada:  This information is being provided to you for information purposes only and is not, and under no circumstances should be construed as, an advertisement, offering or solicitation by Goldman Sachs & Co. LLC for purchasers of securities in Canada to trade in any Canadian security. Goldman Sachs & Co. LLC is not registered as a dealer in any jurisdiction in Canada under applicable Canadian securities laws and generally is not permitted to trade in Canadian securities and may be prohibited from selling certain securities and products in certain jurisdictions in Canada. If you wish to trade in any Canadian securities or other products in Canada please contact Goldman Sachs Canada Inc., an affiliate of The Goldman Sachs Group Inc., or another registered Canadian dealer.  Hong Kong:  Further information on the securities of covered companies referred to in this research may be obtained on request from Goldman Sachs (Asia) L.L.C.  India:  Further information on the subject company or companies referred to in this research may be obtained from Goldman Sachs (India) Securities Private Limited, Research Analyst - SEBI Registration Number INH000001493, 951-A, Rational House, Appasaheb Marathe Marg, Prabhadevi, Mumbai 400 025, India, Corporate Identity Number U74140MH2006FTC160634, Phone +91 22 6616 9000, Fax +91 22 6616 9001. Goldman Sachs may beneficially own 1% or more of the securities (as such term is defined in clause 2 (h) the Indian Securities Contracts (Regulation) Act, 1956) of the subject company or companies referred to in this research report. 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• Jan Hatzius
• Economics Research
• Commercial real estate (CRE)
• Labor Markets
• United States

AI is showing ‘very positive’ signs of eventually boosting GDP and productivity

Goldman Sachs Research predicted last year that generative AI could boost GDP and raise labor productivity growth over the coming decade. Since publishing that outlook, investment in generative AI has boomed, but it will take time for the technology to filter into the overall economy.

“Until we've seen more significant uptake in the actual application of AI, in the regular work production process, I don't think that we're going to see as big of an impact on productivity,” says Joseph Briggs, who co-leads the Global Economics team in Goldman Sachs Research. Briggs wrote last year’s AI report with Goldman Sachs economist Devesh Kodnani.

“That being said, the early signals of future productivity gains look very, very positive,” he adds.  

While adoption of generative AI is lagging investment in the technology , Goldman Sachs Research sees potential for AI to automate many work tasks. It’s expected to start having a measurable impact on US GDP in 2027 and begin affecting growth in other economies around the world in the years that follow.

We spoke with Briggs about how the team’s forecast has held up over the past year, which businesses are adopting generative AI, and the technology’s impact on the labor market.

Based on what you’re seeing from the data, how are we tracking against your productivity prediction?

We haven't seen much of an impact on productivity growth so far. But the reason being is, even though we still see a lot of potential for AI to automate a lot of the things that workers do on a day-to-day basis, thereby saving a lot of time and generating large productivity gains, the adoption rates are just fairly limited right now. The key step, of course, in automating tasks is that people have to start using it. And so until we've seen more significant uptake in the actual application of AI, in the regular work production process, I don't think that we're going to see as big of an impact on productivity.

That being said, the early signals of future productivity gains look very, very positive. Some of the academic literature and economic studies that have looked at the increase in productivity that we've seen following AI adoption, in a few specific cases, supports our view that large productivity gains are possible. The average increase in productivity is about 25%. Case studies of companies that have adopted AI imply similarly large efficiency gains. And so, you know, there's a lot of reasons to be optimistic. It will just take a little bit more time to see these productivity gains realized.

Did you change your forecast for the coming decade based on the actual data?

No, it really hasn't changed because our forecasts don’t assume any AI boost at all before 2027. And the very small increases in adoption that we've seen in the one year since we wrote our initial report, I think, are consistent with our view that over the next three years AI is probably not going to be a main driver of labor productivity and potential GDP growth. Even though we do still think that it's going to be a significant driver of productivity and GDP growth over a much longer horizon.

What explains the divergence between the strong investment in generative AI that you’re seeing compared with the slow rates of adoption?

For AI to be deployed on a widespread basis, there's a lot of things that need to happen. First you need to have models that are powerful enough and trained appropriately so they can actually be useful in everyday work product. Then you need to have the capability to facilitate and answer all the queries that people are going to be posing to AI models, when they do use them every day multiple times a day when they're engaged in regular work. Having both these things requires a big increase in investment in semiconductors which in turn requires a big increase in investment in network capacity.

And ultimately, that’s going to require an increase in electricity and collective power investment to support the increase in demand that facilitating queries will require.

We are seeing clear signs that investment is increasing. Revenues of semiconductor manufacturers are up about 50% since early 2023. If you look at forecast revisions for AI hardware providers, they imply about a $250 billion increase since a year ago. And so there's a lot of signs that the investment laying the groundwork for future use of AI is occurring.

The adoption and usage will occur when these pieces are in place, and companies actually start using AI on an everyday basis. For the most part that hasn't happened yet. We see about 5% of companies reporting that they do use generative AI today in regular production, but this is a fairly small share relative to the overall number of companies that we think will ultimately benefit.

How is that 5% putting generative AI to use?

There are a few specific use cases that are emerging if you look across the industries that are using generative AI. First and foremost, we see adoption rates higher in areas like information services, finance and insurance. The motion picture and sound recording industry, for instance, is another area where adoption is far above the economy wide average.

If we're talking about the things that people say that they're using it for, marketing, automation, chatbot, speech text, and data analysis are all areas that stand out as ways that companies are applying AI right now. This is kind of the low hanging fruit where AI is most applicable, at least in its current form. Ultimately, we think that a broader set of tasks are going to be automated by generative AI. But that probably requires a build out of an application layer to support the broader automation we see possible.

What about the other 95%? What’s holding them back?

There are a number of factors that are slowing down the pace of AI adoption. A lot of executives can see the economic potential of generative AI, but even those that see benefits report a lack of knowledge about AI, concerns about privacy and security, and concerns about overinvesting in an early version of the technology as barriers. I think that a lot these reasons broadly reflect that companies want to make sure that they get generative AI right, and companies are therefore taking deliberate approach to AI adoption.

These views generally align with what we've seen in some of the business surveys, where CEOs are asked about their intention to use generative AI. Very few say that they expect it's going to significantly impact their business over the next one to three years. Most say that they expect to see a significant impact over the three-to-10-year horizon.  

What’s been the net impact on jobs? How do you expect that to change over time?

Given that we've seen very little adoption, it's not surprising that we haven't seen much of an impact on the labor market. If we look at things like the unemployment rate between occupations that are highly exposed to AI automation, and those that are less, they basically tracked each other one-for-one for the last year or two. There have been some layoff announcements attributed to generative AI, but for the most part it seems like a very, very small share – less than 20,000 of all layoffs generated in the economy, which comes down to less than 0.1% of total job separations. So AI hasn't resulted in any significant job loss yet.

In fact, if we look at the labor demand that is generated it’s probably driven a net increase in employment. There has been a notable pickup in job postings mentioning AI as a desirable skill. This is especially true in the information technology sector. And so, it's very well possible, and probably even likely, that the net impact on the labor market has been positive thus far. This is kind of in line with our expectations over the long run, where we do expect that generative AI won't lead to a large amount of job loss. We generally think that it's going to create opportunities either in AI adjacent sectors or occupations or in sectors where labor has a comparative advantage. 

This article is being provided for educational purposes only. The information contained in this article does not constitute a recommendation from any Goldman Sachs entity to the recipient, and Goldman Sachs is not providing any financial, economic, legal, investment, accounting, or tax advice through this article or to its recipient. Neither Goldman Sachs nor any of its affiliates makes any representation or warranty, express or implied, as to the accuracy or completeness of the statements or any information contained in this article and any liability therefore (including in respect of direct, indirect, or consequential loss or damage) is expressly disclaimed.

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