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Once you've made your investment choices, managing them is critical to being successful. You can use all the tools mentioned above to monitor and research your open positions. There are also ways to determine whether the stocks you’ve researched and chosen are a good mix when looked at as a whole.

Fidelity offers a Planning & Guidance Center , a guidance tool that compares your current portfolio with your target asset mix so you can evaluate areas that may need adjustment. This portfolio-level review can be a great way to see whether the stocks that you've researched are collectively meeting your investing objectives. You may also want to consider Fidelity's Guided Portfolio Summary SM Log In Required which can help you break down the investments in your portfolio and identify areas that may need more attention.

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How To Do Investment Research

• The investment research process is one of constant refinement and improvement.
• Whether you're just starting out or you're a seasoned veteran, there's always something to learn.
• Here, the Seeking Alpha editors have compiled a set of perspectives and best practices based on their evaluation of hundreds of thousands of article submissions.

By Mike Taylor

When I started reading and writing about the stock market in the summer of 2007, I had little background in financial research and analysis. I'd studied poetry in college, and I'd moved to New York to become a fiction writer. But when my laptop full of mediocre short stories was stolen from my apartment during a raucous late-bull-market housewarming party, it was time for plan B.

When I joined TheStreet.com that October to copy edit investment commentary, I was both mystified by and skeptical about the world of finance. How could anyone predict what would happen among the seemingly random events of a given market day? Was everyone who pretended to know what was going on a complete fraud and a liar?

As I spent the first year of my career watching the Great Financial Crisis unfold, my skepticism seemed increasingly warranted. But as I learned more about the investment research process, I also gained confidence that a smart and enterprising writer could publish informative work that would help investors make better decisions - or at least avoid some of the stock market's most dangerous traps.

It was a steep climb up that first section of the learning curve for me, and I imagine it's the same for many aspiring analysts and portfolio managers when they're getting started. To provide an orientation to those beginning their education and to offer a brush-up for veterans, we've compiled here a guide to the Seeking Alpha Author Experience's treatment of the investment research process.

Put Your Investment Research In Context

The universal right way to invest may not exist - everyone has different preferences for risk, cognitive strengths and weaknesses, future cash needs, and time horizons. But you can convince readers that you have useful insight (and confront some of your own imperfections with honesty) by being transparent about your own circumstances , and explaining those circumstances to your audience.

Remember, whether you're discussing your own portfolio decisions or analyzing a particular company, context is the lifeblood of investment research . Make sure you're situating the evidence you've unearthed so that someone who's new to the story can incorporate the discussion into his or her own decision process.

We believe that sound research forms the basis from which all success at Seeking Alpha follows.

If you're writing about an individual company, it never hurts to start by reading the most recent 10-K filing . This annual report gives highly detailed insight into company business models, recent performance, and key risks.

Don't stop with the 10-K. Use Seeking Alpha's SEC filing database to get more key primary source information. Make sure you know the benefits of going directly to the filings vs. relying on third-party data sources.

Armed with many of the details regulators have decided companies need to share with investors, it can help to contrast what you know with what the company management says in its press releases . If the narrative the company is feeding to the press differs from what it's disclosing to the SEC, there's usually a big opportunity to inform investors - the basis of a successful Seeking Alpha article.

How To Write Investment Analysis

Investment analysts need to know the difference between factual information/data and their reasoned opinions and inferences. Successful Seeking Alpha articles provide a balance of fact and opinion . Avoid rants and screeds that are heavy on opinion and light on fact; conversely, avoid recaps and overviews that gather readily available information without injecting your own independent perspective.

Analysts have a variety of approaches, but it's important to be comprehensive along two dimensions: qualitative and quantitative information . Make sure you have a solid understanding of the fund or company's strategy and competitive position (qualitative) as well as how that strategy plays out in the financial statements (quantitative). When the connection between the qualitative and quantitative is strong, you have the beginnings of a very compelling investment analysis.

How To Credit Sources In Investment Analysis

In investment research, attention to detail is key. And nowhere is this more true than in the basic but absolutely critical matter of giving proper credit to one's sources . Know when to use direct quotes, paraphrases, and summaries when presenting material from outside sources.

How To Value A Stock

The investment community abounds with variations on the cliche that valuation models are never right, but they're often useful. To land closer to the "useful" side of things, it can help to understand how different models work and when/why to use one compared to another.

Get familiar with the classic discounted cash flow model . Then, as you're deploying it, make sure you're putting discounted cash flows in proper context . Understand that cash flow estimates can be refined and improved and that caveats apply.

Some analysts prefer to use EBITDA as a basis for financial decisions. But be careful using EBITDA - it's got some known flaws to go with its benefits. Check the inputs to your model - are you using traditional and often more conservative GAAP accounting, or are you making some adjustments ?

Maybe you're just going with a handy P/E ratio. If so, make sure you understand how the P/E ratio works .

More experienced authors may want to try their hand at writing for Seeking Alpha's PRO+ research offering. Before you embark on that journey, familiarize yourself with what PRO+ does , look for upcoming catalysts , and see if you can find a mispriced opportunity in the market . PRO is all about the asymmetric risk-reward .

Article Index

Investment Research In Context

• Tell Readers About Your Circumstances
• Financial Analysis And Context

Conducting Investment Research

• 'Other Guys Read Playboy, I Read Annual Reports': A Beginner's Guide To The 10-K
• Using SEC Filings
• More On Using SA's SEC Filings

Writing Investment Analysis

• Critiquing Earnings Press Releases
• Qualitative Vs. Quantitative Analysis
• Fact Vs. Opinion
• Properly Quoting Your Research Sources
• Improving Cash Flow Estimates
• Using Discounted Cash Flows - Context
• Modeling Discounted Cash Flows
• GAAP Vs. Non-GAAP Accounting
• Fundamental Analysis: PE ratios
• Seeking Alpha Author Experience #79: What SA PRO Covers
• Market Mispricing
• Asymmetric Risk/Reward
• What We Mean By 'Quantification'

This article was written by

Analyst’s Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article.

Seeking Alpha's Disclosure: Past performance is no guarantee of future results. No recommendation or advice is being given that any particular security, portfolio, transaction or investment strategy is suitable for any specific person. The author is not advising you personally concerning the nature, potential, value or suitability of any particular security or other matter. You alone are solely responsible for determining whether any investment, security or strategy, or any product or service, is appropriate or suitable for you based on your investment objectives and personal and financial situation. The author is an employee of Seeking Alpha. Any views or opinions expressed herein may not reflect those of Seeking Alpha as a whole. Seeking Alpha is not a licensed securities dealer, broker or US investment adviser or investment bank.

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5 ways to research stocks like the pros

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Knowledge is power on Wall Street, and investing professionals have the reputation of being the most knowledgeable. But if you’re not a pro? Well, individual investors can still take advantage of many of the pros’ top techniques and turn some of their own knowledge into real investing success.

Individual investors have many advantages over the big institutional investors – especially the ability to invest with a long-term mentality and to buy out-of-the-way hidden gems. But they can also leverage information to identify some potentially high-flying stocks, too.

Here are a few of the best ways for individual investors to research stocks and get a leg up on their professional counterparts, as well as one way they can keep more of those gains.

How to research stocks like a pro

Here are five techniques that pros use to figure out what’s really going on in the market. Often these methods require a little more hustle than just reading the numbers on a screen or balance sheet, but you can also find out more that way than you could otherwise.

1. Use a stock screener

A stock screener is a great place to begin for investors on the hunt for new ideas. With a good stock screener, you can find stocks that are hitting 52-week lows, if you’re a value investor , or new highs, if you’re looking for momentum stocks that could continue their trend.

You can pair this information with other financial details that are available in the screener, such as a company’s revenue growth, profit margins, debt and many more. You’ll want to look for a high-quality screener so that you can get highly granular – and fully up to date – information.

You can find stock screeners at some of the top brokers , but you may want to hunt around for one that fits your exact needs and process best.

2. Talk to management teams

It may seem like the management teams are off-limits to individual investors, but not always. Sure, Meta Platforms CEO Mark Zuckerberg is not likely to take your call, but you have a real chance to ask questions at smaller firms, where execs will speak with current or future investors.

You’ll want to have pertinent questions lined up that show you know the business, and it can be a moment to ask insiders the finer points about the business. Even if you can’t get on the phone with the top brass, you can access a public company’s investor relations department. IR, as it’s known, can give you financial details or perspective on a press release, among other things.

It can also be helpful to ask a management team which other companies they respect most in the industry and why. This line of questioning can give you a good perspective on which rivals are worth watching – and they may even be worth investing in, too.

3. Do your own first-hand research

Getting out from behind the desk can be a great way to find out what’s actually going on before it breaks big. That’s classic advice from investing legend Peter Lynch , who recommends watching for new trends emerging with friends, whether it’s a new product or service.

Have you heard about a great new restaurant in the area? Check it out yourself and see what you like and whether its operation is running smoothly. Your neighbor likes a new tech gadget? See for yourself what it’s all about – and then assess if the company is worth an investment. (Are you a beginning investor? Here’s how to invest in stocks .)

This way is great for finding a hot new consumer brand, especially in the restaurant or retail spaces. Food fans could easily have picked up future high-flyers such as Chipotle and Panera before they became big household names. Even if investors didn’t get in at the bottom, these restaurants had years of attractive growth remaining in them after they were “discovered.”

4. Run your own channel checks

Especially for consumer or retail brands, you can do some of what Wall Street analysts call “channel checks.” A channel check is a fancy name for actually seeing what amount of product is moving through the system. A channel check can give you valuable information about what’s happening now before it shows up in the reported financial statements in three or six months.

For the pros, a channel check might involve calling up suppliers and customers of a target investment and seeing how much business the company is doing. In the case of individual investors, you can do much of the same with consumer brands, asking questions such as:

• Is that new product getting shelf space at your local grocery store?
• Is the product getting more space over time or less?
• Is the parking lot at that hot new chain restaurant or retail shop getting even more crowded?
• Or maybe the restaurant is getting less crowded or getting poor reviews?

You can run your own channel checks and see trends that might not show up in the results yet.

5. Subscribe to a newsletter

An investing newsletter is a great resource for individual investors, and it’s a technique that pro investors use as well, though the two kinds of newsletters typically focus on much different analysis. Still, a good newsletter can help individual investors find and evaluate good investment opportunities, and give them a wider perspective, since the market is so large.

It may seem like Wall Street investors are omniscient, but they outsource a lot of research to third parties. That’s exactly what individuals can do, but they may have an additional advantage, because they can invest in small, high-growth businesses that the big investors can’t touch. Plus, you may have the added advantage of bouncing good stock ideas off the newsletter pros.

Look for a reputable newsletter company with a long track record and a history of treating subscribers well. In some cases, you can find good newsletters for a few hundred dollars a year.

How to really let your money compound

While Wall Street has a reputation for being knowledgeable, success is not all about having the most info. The best investors really know how to minimize taxes and keep more of their money. So you’ve researched and found a great stock – here’s how to keep your gains compounding.

You may have found an undervalued stock that should go up to fair value and then you’ll sell. Or you may hunt for compounders, stocks that can grow for years, even decades. Think of PayPal, Amazon , or Starbucks, for example. It’s a classic dilemma between growth and value investing .

But whether you’re a value or growth investor, it’s important to realize that if you sell a winning investment in a taxable account, you’ll be liable for taxable gains ( at either the short- or long-term rates ).

Instead, by not selling, you’ll defer any taxes, meaning that the wealth remains yours. But not only do you avoid the taxes, you’ll be able to compound on the full pre-tax amount each year. To be clear, you will always still need to watch out if you owe taxes or not, but by allowing the investment to compound, you give yourself a better chance for the investment to grow beyond what it would have been had you cashed out earlier.

For example, imagine you invested $10,000 and gained 20 percent annually but sold right at the end of the year, incurring a tax rate of 20 percent. In five years you’d turn $10,000 into $21,000, and average about 16 percent annualized gains, since the government took its cut each year.

But what if you held your stock during that whole period? You’d compound the whole amount at 20 percent annually, turning $10,000 into just over $24,883. Even if you decided to sell at that point, you’d still realize an after-tax amount of about $21,906 – more than in the first scenario.

The difference? You’ve compounded further gains on top of the gains you had to pay taxes on in the first scenario. In effect, by not selling your stock, you’re forcing the government to defer its taxes and to give you the ability to keep compounding on the full, pre-tax amount.

That’s how legendary investors compound their gains when it makes sense. It’s not just a question of having the best research but also using it the best, in this case by minimizing taxes.

Bottom line

While it’s easy to lament that Wall Street pros have huge advantages over individual investors, even the little guys have ways to use some of the pros’ techniques. And in some cases, individual investors even have advantages that large investors can never take advantage of.

Editorial Disclaimer: All investors are advised to conduct their own independent research into investment strategies before making an investment decision. In addition, investors are advised that past investment product performance is no guarantee of future price appreciation.

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• Research in Bull & Bear Markets

How Equity Research Is Changing

• Who Pays for Research?
• The Role of Fee-Based Research

The Bottom Line

The changing role of equity research.

Yarilet Perez is an experienced multimedia journalist and fact-checker with a Master of Science in Journalism. She has worked in multiple cities covering breaking news, politics, education, and more. Her expertise is in personal finance and investing, and real estate.

The role of equity research is to provide information to the market. A lack of information creates inefficiencies that result in stocks being misrepresented (whether over or undervalued). Analysts use their expertise and spend a lot of time analyzing a stock, its industry, and its peer group to provide earnings and valuation estimates. Research is valuable because it fills information gaps so that each individual investor does not need to analyze every stock. This division of labor makes the market more efficient.

The title of this article is perhaps a bit misleading, because the role of equity research really hasn't changed since the first U.S. stock trade occurred under the buttonwood tree on Manhattan Island. What has changed is the economic and trading environments (e.g. the character of bull and bear markets) that influence research.

Key Takeaways

• Equity research is a key piece of Wall Street analysis, used by investors large and small to make better-informed investment decisions in the stock market.
• Often research is funded by institutional investors on a fee-basis or using soft dollars.
• Depending on whether the market is in a bull or bear mode, equity research has begun to shift its lens of analysis and the types of reports issued.

Research in Bull and Bear Markets

In every bull market, some excesses become apparent only in the bear market that follows. Whether it is dotcoms or organic foods, each age has its mania that distorts the normal functioning of the market. In a rush to make money, rationality is the first casualty. Investors rush to jump on the bandwagon and the market over-allocates capital to the "hot" sector(s). This herd mentality is the reason why bull markets have funded so many "me-too" ideas throughout history.

Research is a function of the market and is influenced by these swings. In a bull market, investment bankers , the media and investors pressure analysts to focus on the hot sectors. Some analysts morph into promoters as they ride the market. Those analysts that remain, rational practitioners, are ignored, and their research reports go unread.

Seeking to blame someone for investment losses is a normal event in bear markets. It happened in the 1930s, 1970s, during the dot com crash and the financial crisis of 2008, too. Some of the criticisms are deserved, but generally, the need to provide information about companies has not changed.

To discuss the role of research in today's market , we need to differentiate between Wall Street research and other research. The major brokerages provide Wall Street research—typically sell-side firms—both on and off Wall Street. Other research is produced by independent research firms and small boutique brokerage firms.

This differentiation is important. First, Wall Street research has become focused on large-cap , very liquid stocks, and ignores the majority of publicly traded stocks. To remain profitable, Wall Street firms have focused on big-cap stocks to generate highly lucrative investment banking deals and trade profits, but also face the daunting task of cutting costs.

Those companies that are likely to provide the research firms with sizable investment banking deals are the stocks that are determined worthy of being followed by the market. The stock's long-term investment potential is often secondary.

Other research is filling the information gap created by Wall Street. Independent research firms and boutique brokerage firms are providing research on the stocks that have been orphaned by Wall Street. This means that independent research firms are becoming a primary source of information on the majority of stocks, but investors are reluctant to pay for research because they don't know what they are paying for until well after the purchase. Unfortunately, not all research is worth buying, as the information can be inaccurate and misleading.

These days there is a great deal of research that is provided for free to clients via email. Even at essentially zero cost to the investor, a large majority of the research goes unread.

Who Pays for Research? Big Investors Do!

The ironic thing is that while research has proven to be valuable, individual investors do not seem to want to pay for it. This may be because, under the traditional system, brokerage houses provided research to gain and keep clients. Investors just had to ask their brokers for a report and received it at no charge. What seems to have gone unnoticed is that the investor commissions paid for that research.

A good indicator of the value of research is the amount institutional investors are willing to pay for it. Institutional investors typically hire their own analysts to gain a competitive edge over other investors. Although spending on equity research analysts has significantly declined in recent years, institutions may also pay for the sell-side research they receive (either with dollars or by giving the supplying brokerage firm trades to execute).

European regulations that went into effect in 2018, known as  MiFID II , require asset managers to fund external research from their own profit and loss account (P&L) or through research payments that are tracked with clear audit trails. This will lead to billing clients for research and trading separately.

The Role of Fee-Based Research

Fee-based research increases market efficiency and bridges the gap between investors who want research (without paying) and companies who realize that Wall Street is not likely to provide research on their stock. This research provides information to the widest possible audience at no charge to the reader because the subject company has funded the research.

It is important to differentiate between objective fee-based research and research that is promotional. Objective fee-based research is similar to the role of your doctor. You pay a doctor not to tell you that you feel good, but to give you their professional and truthful opinion of your condition.

Legitimate fee-based research is a professional and objective analysis and opinion of a company's investment potential. Promotional research is short on analysis and full of hype. One example of this is the email reports and misleading social media posts about the penny stocks that will supposedly triple in a short time.

Legitimate fee-based research firms have the following characteristics:

• They provide analytical, not promotional services.
• They are paid a set annual fee in cash; they do not accept any form of equity, which may cause conflicts of interest .
• They provide full and clear disclosure of the relationship between the company and the research firm so investors can evaluate objectivity.

Companies that engage a legitimate fee-based research firm to analyze their stock are trying to get information to investors and improve market efficiency.

Such a company is making the following important statements:

• It believes its shares are undervalued because investors are not aware of the company.
• It is aware that Wall Street is no longer an option.
• It believes that its investment potential can withstand objective analysis.

The National Investor Relations Institute (NIRI) was probably the first group to recognize the need for fee-based research. In January 2020, NIRI issued a letter emphasizing the need for small-cap companies to find alternatives to Wall Street research to get their information to investors.

The reputation and credibility of a company and research firm depends on the efforts they make to inform investors. A company does not want to be tarnished by being associated with unreliable or misleading research. Similarly, a research firm will only want to analyze companies that have strong fundamentals and long-term investment potential. Fee-based research continues to provide a professional and objective analysis of a company's investment potential, although the market for its services remains challenged in the current business environment.

CFA Institute. " MiFID II Equity Research Costs Survey ."

National Investor Relations Institute (NIRI). " NIRI Proposes Guidance on Company-sponsored Research ."

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• The May jobs report showed a softening in hires and wage growth, raising prospects for a "soft landing."
• Meanwhile, the world's largest chip foundry is going ahead with a purchase of an advanced EUV tool, suggesting AI investment remains in full swing.
• AI growth and lower interest rates help all three of these stocks, and many across the chip sector.
• Motley Fool Issues Rare “All In” Buy Alert

NASDAQ: ARM

Arm holdings.

Chip stocks are breaking out on more AI news combined with hopes for an economic soft landing.

Shares of most semiconductor stocks including sector leaders Broadcom ( AVGO 0.38% ) , Arm Holdings ( ARM -0.41% ) , and Lam Research ( LRCX 0.06% ) were rallying today, with these three up 5.2%, 5.3%, and 4.6%, respectively, as of 12:50 p.m. ET on Wednesday.

These three chip leaders are players within the artificial intelligence (AI) race, and their stocks have seen solid price appreciation in 2024. But that growth stalled last month, as recent inflation reports came in hotter than expected in April.

But today, more positive AI news continued to roll in. Meanwhile, Wednesday saw a softer-than-expected May jobs report. That fueled hope that lower inflation could be in the cards, and strengthened the prospects for Federal Reserve interest rate cuts this year.

Bad news is good news?

This morning, the Automatic Data Processing (ADP) employment report came out for May, showing that 152,000 jobs were added last month, below expectations of 175,000.

Furthermore, the April reading was revised down to 188,000 jobs added. The report also showed that wage gains for job-switchers moderated to 7.8%. The report dovetailed nicely with yesterday's Job Openings and Labor Turnover Survey report, which also showed falling job openings.

What does this have to do with semiconductor stocks, and why would it be good? Because a softer-than-expected jobs number and wage growth that's moderating but still solid suggest services inflation might begin to come down, as wage pressures and labor shortages have been a key factor in the services inflation we've seen over the past couple years.

A moderating economy that doesn't tip into recession would be an ideal scenario, enabling the Federal Reserve to cut the federal funds rate this year without needing a recession -- what is called a "soft landing."

High interest rates in particular weigh on growth stocks , which often trade at high multiples, as well as cyclical stocks that can be sensitive to an economic slowdown. And semiconductor stocks have both those qualities, especially since many have seen their valuations run up on expectations of strong AI-fueled growth.

For example, Broadcom and Lam Research have each seen their price-to-earnings (P/E) ratios more than double over the past year to 52 and 35, respectively. Meanwhile, Arm Holdings has always traded at an extremely high valuation since going public in September, with a P/E of 460.

So, the prospects for lower interest rates seem to be lifting the entire chip sector today, especially as the AI growth story remains intact.

AVGO PE ratio data by YCharts.

A report that Taiwan Semiconductor Manufacturing (TSMC) would be investing in the most advanced kind of extreme ultraviolet lithography (EUV) machine this year, called high N.A., suggests that the world's leading foundry will move rapidly to the latest chipmaking technology.

That suggests AI demand and associated competition continues unabated, and may even be picking up steam, which would be a great thing for these three companies. TSMC makes chips for Broadcom, as well as many chips based on the Arm-based architecture. In fact, TSMC's biggest customer is Apple , which designs Arm-based chips for its smartphones and PCs.

Qualcomm has also begun producing Arm-based chips for AI-enabled PCs and potentially even servers in a bid to expand its market beyond handsets. Those chips will also be made by TSMC fabs. So the TSMC investment news could mean strong growth for Arm.

A bigger investment in EUV would also be good for Lam Research, whose etch-and-deposition machines are used alongside EUV lithography machines as part of the chipmaking process.

Lam has pioneered a new technology that will likely have to be used alongside high-N.A. EUV machines, like the one TSMC reportedly is buying, in order to prevent defects that more easily happen at extremely fine molecular sizes. Existing processes struggle to maintain design integrity at extremely small sizes, so an acceleration of high-N.A. adoption could mean good things for Lam Research as well.

Image source: Getty Images.

Is the chip cycle getting long in the tooth or just getting started?

The semiconductor sector has broadly recovered from the 2022 lows, with many stocks now up by multiples of their 2022 bottom prices. However, their businesses are really just starting to see a recovery in revenue and profit, driven by AI and a recovery in legacy sectors like smartphones and PCs.

Yet while the upturn is about 18 months old, AI-backed growth could make the boom last longer than prior cycles. And if the Fed can pull off a soft landing with falling interest rates and no recession, so much the better.

Billy Duberstein and/or his clients have positions in Apple, Broadcom, Lam Research, and Taiwan Semiconductor Manufacturing. The Motley Fool has positions in and recommends Apple, Lam Research, Qualcomm, and Taiwan Semiconductor Manufacturing. The Motley Fool recommends Broadcom. The Motley Fool has a disclosure policy .

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Rent vs. Buy: The Full Decision for 2024

When mortgage rates are near 3%, the majority of buyers break even and start building up a windfall relative to a renter making financial investments fully (but conservatively) within a few years. With mortgage rates above 6%, home buying is for households making a long-run financial decision again. 

Zillow Research has abundant analyses describing the rising barriers to becoming a new homeowner. Here however, rather than ask “ Can the typical household own a home?” we seek to answer “ Should they?” We strip the decision down to its financials by estimating comparable for-sale prices and asking-rate rents on the typical home and then simulating transaction costs, home values, rents, insurance, property taxes, maintenance expenses and mortgage dynamics into the future to determine if the household is financially better off renting or buying the same home. (Not considered in this paper are cases in which properties available to purchase are not really available to rent.) 

If you’re a risk-loving, stock-savvy individual who loves living in a different city every few years and never wants to paint a wall, you’re a “lifestyle renter.” If you want to shape your home into your legacy over many decades, you’re obviously a buyer. 

We’re talking about the household that is somewhere in between: a typical risk-averse household unfamiliar with stock markets beyond retirement funds. The household is interested in the lifestyle that buying a home has to offer, but its members aren’t certain they will want to (or be able to) stay in the house they can afford for decades. What is that cutoff point? In other words, how much time is needed for the financial advantages of buying with a fixed-rate mortgage in the U.S. to overcome the large transaction costs of becoming an owner?

A consumer should buy if …

• They are confident they will stay, or can stay, in the home long enough for the financial benefits of buying their primary home to overcome the lower upfront costs of renting the same unit and investing in stock markets. This is the breakeven year.
• They consider the “price” of selling before the breakeven year worth whatever value they place on having full control and the option to customize the property during that time. 

   In this white paper and over the following weeks, we’ll be diving into the different components of the rent-versus-buy decision. 

• Upfront financial commitment
• Affordability of recurring monthly costs
• Investment component

Our goal is to go beyond just the breakeven year that our simulation produces, and work toward helping our audience really understand the decision and its tradeoffs. When we report one number that supposedly summarizes so much complexity, we ask the audience for significant trust and hide a lot of detail. Each breakout is still fairly complex, but much less so.

There is also value in the details, especially for individual households, each with different concerns. Renting versus buying, depending on where you are in the country or on your credit profile, can be nuanced. It can be good for affordability and stability into the future, but bad as a real estate investment, for example. Breaking down the rent-versus-buy decision into three components goes a step beyond a black-box-style number to help customers make decisions according to what matters to them.  

Stay tuned. 

• How the Housing Market is Changing in Cities Gaining the Most New Neighbors
• Coming in Hot: Phoenix is Named the Best Market for New College Graduates
• Treasury Yields, Mortgage Rates Increase Again As Concerns Over Debt Issuance Re-emerge
• April 2024 Existing Home Sales: Weaker Than Expected Sales Due To Higher Mortgage Rates
• Mortgage Rates Increase This Week On New Insights Into Fed Outlook
• Zillow Home Value and Home Sales Forecast (April 2024)
• April 2024 Housing Starts: Builders Cautiously Scale Back New Home Construction As Expectations Shift
• Mortgage Rates Lowest Since February As The Disinflation Trend Resumes
• Market One-Pager
• Racial Disparities in Housing

AI Index: State of AI in 13 Charts

In the new report, foundation models dominate, benchmarks fall, prices skyrocket, and on the global stage, the U.S. overshadows.

This year’s AI Index — a 500-page report tracking 2023’s worldwide trends in AI — is out.

The index is an independent initiative at the Stanford Institute for Human-Centered Artificial Intelligence (HAI), led by the AI Index Steering Committee, an interdisciplinary group of experts from across academia and industry. This year’s report covers the rise of multimodal foundation models, major cash investments into generative AI, new performance benchmarks, shifting global opinions, and new major regulations.

Don’t have an afternoon to pore through the findings? Check out the high level here.

A Move Toward Open-Sourced

This past year, organizations released 149 foundation models, more than double the number released in 2022. Of these newly released models, 65.7% were open-source (meaning they can be freely used and modified by anyone), compared with only 44.4% in 2022 and 33.3% in 2021.

But At a Cost of Performance?

Closed-source models still outperform their open-sourced counterparts. On 10 selected benchmarks, closed models achieved a median performance advantage of 24.2%, with differences ranging from as little as 4.0% on mathematical tasks like GSM8K to as much as 317.7% on agentic tasks like AgentBench.

Biggest Players

Industry dominates AI, especially in building and releasing foundation models. This past year Google edged out other industry players in releasing the most models, including Gemini and RT-2. In fact, since 2019, Google has led in releasing the most foundation models, with a total of 40, followed by OpenAI with 20. Academia trails industry: This past year, UC Berkeley released three models and Stanford two.

Industry Dwarfs All

If you needed more striking evidence that corporate AI is the only player in the room right now, this should do it. In 2023, industry accounted for 72% of all new foundation models.

Prices Skyrocket

One of the reasons academia and government have been edged out of the AI race: the exponential increase in cost of training these giant models. Google’s Gemini Ultra cost an estimated $191 million worth of compute to train, while OpenAI’s GPT-4 cost an estimated $78 million. In comparison, in 2017, the original Transformer model, which introduced the architecture that underpins virtually every modern LLM, cost around $900.

What AI Race?

At least in terms of notable machine learning models, the United States vastly outpaced other countries in 2023, developing a total of 61 models in 2023. Since 2019, the U.S. has consistently led in originating the majority of notable models, followed by China and the UK.

Move Over, Human

As of 2023, AI has hit human-level performance on many significant AI benchmarks, from those testing reading comprehension to visual reasoning. Still, it falls just short on some benchmarks like competition-level math. Because AI has been blasting past so many standard benchmarks, AI scholars have had to create new and more difficult challenges. This year’s index also tracked several of these new benchmarks, including those for tasks in coding, advanced reasoning, and agentic behavior.

Private Investment Drops (But We See You, GenAI)

While AI private investment has steadily dropped since 2021, generative AI is gaining steam. In 2023, the sector attracted $25.2 billion, nearly ninefold the investment of 2022 and about 30 times the amount from 2019 (call it the ChatGPT effect). Generative AI accounted for over a quarter of all AI-related private investments in 2023.

U.S. Wins $$ Race

And again, in 2023 the United States dominates in AI private investment. In 2023, the $67.2 billion invested in the U.S. was roughly 8.7 times greater than the amount invested in the next highest country, China, and 17.8 times the amount invested in the United Kingdom. That lineup looks the same when zooming out: Cumulatively since 2013, the United States leads investments at $335.2 billion, followed by China with $103.7 billion, and the United Kingdom at $22.3 billion.

Where is Corporate Adoption?

More companies are implementing AI in some part of their business: In surveys, 55% of organizations said they were using AI in 2023, up from 50% in 2022 and 20% in 2017. Businesses report using AI to automate contact centers, personalize content, and acquire new customers. 

Younger and Wealthier People Worry About Jobs

Globally, most people expect AI to change their jobs, and more than a third expect AI to replace them. Younger generations — Gen Z and millennials — anticipate more substantial effects from AI compared with older generations like Gen X and baby boomers. Specifically, 66% of Gen Z compared with 46% of boomer respondents believe AI will significantly affect their current jobs. Meanwhile, individuals with higher incomes, more education, and decision-making roles foresee AI having a great impact on their employment.

While the Commonwealth Worries About AI Products

When asked in a survey about whether AI products and services make you nervous, 69% of Aussies and 65% of Brits said yes. Japan is the least worried about their AI products at 23%.  

Regulation Rallies

More American regulatory agencies are passing regulations to protect citizens and govern the use of AI tools and data. For example, the Copyright Office and the Library of Congress passed copyright registration guidance concerning works that contained material generated by AI, while the Securities and Exchange Commission developed a cybersecurity risk management strategy, governance, and incident disclosure plan. The agencies to pass the most regulation were the Executive Office of the President and the Commerce Department. 

The AI Index was first created to track AI development. The index collaborates with such organizations as LinkedIn, Quid, McKinsey, Studyportals, the Schwartz Reisman Institute, and the International Federation of Robotics to gather the most current research and feature important insights on the AI ecosystem. 

More News Topics

The state of AI in early 2024: Gen AI adoption spikes and starts to generate value

If 2023 was the year the world discovered generative AI (gen AI) , 2024 is the year organizations truly began using—and deriving business value from—this new technology. In the latest McKinsey Global Survey  on AI, 65 percent of respondents report that their organizations are regularly using gen AI, nearly double the percentage from our previous survey just ten months ago. Respondents’ expectations for gen AI’s impact remain as high as they were last year , with three-quarters predicting that gen AI will lead to significant or disruptive change in their industries in the years ahead.

About the authors

This article is a collaborative effort by Alex Singla , Alexander Sukharevsky , Lareina Yee , and Michael Chui , with Bryce Hall , representing views from QuantumBlack, AI by McKinsey, and McKinsey Digital.

Organizations are already seeing material benefits from gen AI use, reporting both cost decreases and revenue jumps in the business units deploying the technology. The survey also provides insights into the kinds of risks presented by gen AI—most notably, inaccuracy—as well as the emerging practices of top performers to mitigate those challenges and capture value.

AI adoption surges

Interest in generative AI has also brightened the spotlight on a broader set of AI capabilities. For the past six years, AI adoption by respondents’ organizations has hovered at about 50 percent. This year, the survey finds that adoption has jumped to 72 percent (Exhibit 1). And the interest is truly global in scope. Our 2023 survey found that AI adoption did not reach 66 percent in any region; however, this year more than two-thirds of respondents in nearly every region say their organizations are using AI. 1 Organizations based in Central and South America are the exception, with 58 percent of respondents working for organizations based in Central and South America reporting AI adoption. Looking by industry, the biggest increase in adoption can be found in professional services. 2 Includes respondents working for organizations focused on human resources, legal services, management consulting, market research, R&D, tax preparation, and training.

Also, responses suggest that companies are now using AI in more parts of the business. Half of respondents say their organizations have adopted AI in two or more business functions, up from less than a third of respondents in 2023 (Exhibit 2).

Gen AI adoption is most common in the functions where it can create the most value

Most respondents now report that their organizations—and they as individuals—are using gen AI. Sixty-five percent of respondents say their organizations are regularly using gen AI in at least one business function, up from one-third last year. The average organization using gen AI is doing so in two functions, most often in marketing and sales and in product and service development—two functions in which previous research  determined that gen AI adoption could generate the most value 3 “ The economic potential of generative AI: The next productivity frontier ,” McKinsey, June 14, 2023. —as well as in IT (Exhibit 3). The biggest increase from 2023 is found in marketing and sales, where reported adoption has more than doubled. Yet across functions, only two use cases, both within marketing and sales, are reported by 15 percent or more of respondents.

Gen AI also is weaving its way into respondents’ personal lives. Compared with 2023, respondents are much more likely to be using gen AI at work and even more likely to be using gen AI both at work and in their personal lives (Exhibit 4). The survey finds upticks in gen AI use across all regions, with the largest increases in Asia–Pacific and Greater China. Respondents at the highest seniority levels, meanwhile, show larger jumps in the use of gen Al tools for work and outside of work compared with their midlevel-management peers. Looking at specific industries, respondents working in energy and materials and in professional services report the largest increase in gen AI use.

Investments in gen AI and analytical AI are beginning to create value

The latest survey also shows how different industries are budgeting for gen AI. Responses suggest that, in many industries, organizations are about equally as likely to be investing more than 5 percent of their digital budgets in gen AI as they are in nongenerative, analytical-AI solutions (Exhibit 5). Yet in most industries, larger shares of respondents report that their organizations spend more than 20 percent on analytical AI than on gen AI. Looking ahead, most respondents—67 percent—expect their organizations to invest more in AI over the next three years.

Where are those investments paying off? For the first time, our latest survey explored the value created by gen AI use by business function. The function in which the largest share of respondents report seeing cost decreases is human resources. Respondents most commonly report meaningful revenue increases (of more than 5 percent) in supply chain and inventory management (Exhibit 6). For analytical AI, respondents most often report seeing cost benefits in service operations—in line with what we found last year —as well as meaningful revenue increases from AI use in marketing and sales.

Inaccuracy: The most recognized and experienced risk of gen AI use

As businesses begin to see the benefits of gen AI, they’re also recognizing the diverse risks associated with the technology. These can range from data management risks such as data privacy, bias, or intellectual property (IP) infringement to model management risks, which tend to focus on inaccurate output or lack of explainability. A third big risk category is security and incorrect use.

Respondents to the latest survey are more likely than they were last year to say their organizations consider inaccuracy and IP infringement to be relevant to their use of gen AI, and about half continue to view cybersecurity as a risk (Exhibit 7).

Conversely, respondents are less likely than they were last year to say their organizations consider workforce and labor displacement to be relevant risks and are not increasing efforts to mitigate them.

In fact, inaccuracy— which can affect use cases across the gen AI value chain , ranging from customer journeys and summarization to coding and creative content—is the only risk that respondents are significantly more likely than last year to say their organizations are actively working to mitigate.

Some organizations have already experienced negative consequences from the use of gen AI, with 44 percent of respondents saying their organizations have experienced at least one consequence (Exhibit 8). Respondents most often report inaccuracy as a risk that has affected their organizations, followed by cybersecurity and explainability.

Our previous research has found that there are several elements of governance that can help in scaling gen AI use responsibly, yet few respondents report having these risk-related practices in place. 4 “ Implementing generative AI with speed and safety ,” McKinsey Quarterly , March 13, 2024. For example, just 18 percent say their organizations have an enterprise-wide council or board with the authority to make decisions involving responsible AI governance, and only one-third say gen AI risk awareness and risk mitigation controls are required skill sets for technical talent.

Bringing gen AI capabilities to bear

The latest survey also sought to understand how, and how quickly, organizations are deploying these new gen AI tools. We have found three archetypes for implementing gen AI solutions : takers use off-the-shelf, publicly available solutions; shapers customize those tools with proprietary data and systems; and makers develop their own foundation models from scratch. 5 “ Technology’s generational moment with generative AI: A CIO and CTO guide ,” McKinsey, July 11, 2023. Across most industries, the survey results suggest that organizations are finding off-the-shelf offerings applicable to their business needs—though many are pursuing opportunities to customize models or even develop their own (Exhibit 9). About half of reported gen AI uses within respondents’ business functions are utilizing off-the-shelf, publicly available models or tools, with little or no customization. Respondents in energy and materials, technology, and media and telecommunications are more likely to report significant customization or tuning of publicly available models or developing their own proprietary models to address specific business needs.

Respondents most often report that their organizations required one to four months from the start of a project to put gen AI into production, though the time it takes varies by business function (Exhibit 10). It also depends upon the approach for acquiring those capabilities. Not surprisingly, reported uses of highly customized or proprietary models are 1.5 times more likely than off-the-shelf, publicly available models to take five months or more to implement.

Gen AI high performers are excelling despite facing challenges

Gen AI is a new technology, and organizations are still early in the journey of pursuing its opportunities and scaling it across functions. So it’s little surprise that only a small subset of respondents (46 out of 876) report that a meaningful share of their organizations’ EBIT can be attributed to their deployment of gen AI. Still, these gen AI leaders are worth examining closely. These, after all, are the early movers, who already attribute more than 10 percent of their organizations’ EBIT to their use of gen AI. Forty-two percent of these high performers say more than 20 percent of their EBIT is attributable to their use of nongenerative, analytical AI, and they span industries and regions—though most are at organizations with less than $1 billion in annual revenue. The AI-related practices at these organizations can offer guidance to those looking to create value from gen AI adoption at their own organizations.

To start, gen AI high performers are using gen AI in more business functions—an average of three functions, while others average two. They, like other organizations, are most likely to use gen AI in marketing and sales and product or service development, but they’re much more likely than others to use gen AI solutions in risk, legal, and compliance; in strategy and corporate finance; and in supply chain and inventory management. They’re more than three times as likely as others to be using gen AI in activities ranging from processing of accounting documents and risk assessment to R&D testing and pricing and promotions. While, overall, about half of reported gen AI applications within business functions are utilizing publicly available models or tools, gen AI high performers are less likely to use those off-the-shelf options than to either implement significantly customized versions of those tools or to develop their own proprietary foundation models.

What else are these high performers doing differently? For one thing, they are paying more attention to gen-AI-related risks. Perhaps because they are further along on their journeys, they are more likely than others to say their organizations have experienced every negative consequence from gen AI we asked about, from cybersecurity and personal privacy to explainability and IP infringement. Given that, they are more likely than others to report that their organizations consider those risks, as well as regulatory compliance, environmental impacts, and political stability, to be relevant to their gen AI use, and they say they take steps to mitigate more risks than others do.

Gen AI high performers are also much more likely to say their organizations follow a set of risk-related best practices (Exhibit 11). For example, they are nearly twice as likely as others to involve the legal function and embed risk reviews early on in the development of gen AI solutions—that is, to “ shift left .” They’re also much more likely than others to employ a wide range of other best practices, from strategy-related practices to those related to scaling.

In addition to experiencing the risks of gen AI adoption, high performers have encountered other challenges that can serve as warnings to others (Exhibit 12). Seventy percent say they have experienced difficulties with data, including defining processes for data governance, developing the ability to quickly integrate data into AI models, and an insufficient amount of training data, highlighting the essential role that data play in capturing value. High performers are also more likely than others to report experiencing challenges with their operating models, such as implementing agile ways of working and effective sprint performance management.

About the research

The online survey was in the field from February 22 to March 5, 2024, and garnered responses from 1,363 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 981 said their organizations had adopted AI in at least one business function, and 878 said their organizations were regularly using gen AI in at least one function. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.

Alex Singla and Alexander Sukharevsky  are global coleaders of QuantumBlack, AI by McKinsey, and senior partners in McKinsey’s Chicago and London offices, respectively; Lareina Yee  is a senior partner in the Bay Area office, where Michael Chui , a McKinsey Global Institute partner, is a partner; and Bryce Hall  is an associate partner in the Washington, DC, office.

They wish to thank Kaitlin Noe, Larry Kanter, Mallika Jhamb, and Shinjini Srivastava for their contributions to this work.

This article was edited by Heather Hanselman, a senior editor in McKinsey’s Atlanta office.

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