research studies synonym

50 Useful Academic Words & Phrases for Research

Like all good writing, writing an academic paper takes a certain level of skill to express your ideas and arguments in a way that is natural and that meets a level of academic sophistication. The terms, expressions, and phrases you use in your research paper must be of an appropriate level to be submitted to academic journals.

Therefore, authors need to know which verbs , nouns , and phrases to apply to create a paper that is not only easy to understand, but which conveys an understanding of academic conventions. Using the correct terminology and usage shows journal editors and fellow researchers that you are a competent writer and thinker, while using non-academic language might make them question your writing ability, as well as your critical reasoning skills.

What are academic words and phrases?

One way to understand what constitutes good academic writing is to read a lot of published research to find patterns of usage in different contexts. However, it may take an author countless hours of reading and might not be the most helpful advice when faced with an upcoming deadline on a manuscript draft.

Briefly, “academic” language includes terms, phrases, expressions, transitions, and sometimes symbols and abbreviations that help the pieces of an academic text fit together. When writing an academic text–whether it is a book report, annotated bibliography, research paper, research poster, lab report, research proposal, thesis, or manuscript for publication–authors must follow academic writing conventions. You can often find handy academic writing tips and guidelines by consulting the style manual of the text you are writing (i.e., APA Style , MLA Style , or Chicago Style ).

However, sometimes it can be helpful to have a list of academic words and expressions like the ones in this article to use as a “cheat sheet” for substituting the better term in a given context.

How to Choose the Best Academic Terms

You can think of writing “academically” as writing in a way that conveys one’s meaning effectively but concisely. For instance, while the term “take a look at” is a perfectly fine way to express an action in everyday English, a term like “analyze” would certainly be more suitable in most academic contexts. It takes up fewer words on the page and is used much more often in published academic papers.

You can use one handy guideline when choosing the most academic term: When faced with a choice between two different terms, use the Latinate version of the term. Here is a brief list of common verbs versus their academic counterparts:

Although this can be a useful tip to help academic authors, it can be difficult to memorize dozens of Latinate verbs. Using an AI paraphrasing tool or proofreading tool can help you instantly find more appropriate academic terms, so consider using such revision tools while you draft to improve your writing.

Top 50 Words and Phrases for Different Sections in a Research Paper

The “Latinate verb rule” is just one tool in your arsenal of academic writing, and there are many more out there. But to make the process of finding academic language a bit easier for you, we have compiled a list of 50 vital academic words and phrases, divided into specific categories and use cases, each with an explanation and contextual example.

Best Words and Phrases to use in an Introduction section

1. historically.

An adverb used to indicate a time perspective, especially when describing the background of a given topic.

2. In recent years

A temporal marker emphasizing recent developments, often used at the very beginning of your Introduction section.

3. It is widely acknowledged that

A “form phrase” indicating a broad consensus among researchers and/or the general public. Often used in the literature review section to build upon a foundation of established scientific knowledge.

4. There has been growing interest in

Highlights increasing attention to a topic and tells the reader why your study might be important to this field of research.

5. Preliminary observations indicate

Shares early insights or findings while hedging on making any definitive conclusions. Modal verbs like may , might , and could are often used with this expression.

6. This study aims to

Describes the goal of the research and is a form phrase very often used in the research objective or even the hypothesis of a research paper .

7. Despite its significance

Highlights the importance of a matter that might be overlooked. It is also frequently used in the rationale of the study section to show how your study’s aim and scope build on previous studies.

8. While numerous studies have focused on

Indicates the existing body of work on a topic while pointing to the shortcomings of certain aspects of that research. Helps focus the reader on the question, “What is missing from our knowledge of this topic?” This is often used alongside the statement of the problem in research papers.

9. The purpose of this research is

A form phrase that directly states the aim of the study.

10. The question arises (about/whether)

Poses a query or research problem statement for the reader to acknowledge.

Best Words and Phrases for Clarifying Information

11. in other words.

Introduces a synopsis or the rephrasing of a statement for clarity. This is often used in the Discussion section statement to explain the implications of the study .

12. That is to say

Provides clarification, similar to “in other words.”

13. To put it simply

Simplifies a complex idea, often for a more general readership.

14. To clarify

Specifically indicates to the reader a direct elaboration of a previous point.

15. More specifically

Narrows down a general statement from a broader one. Often used in the Discussion section to clarify the meaning of a specific result.

16. To elaborate

Expands on a point made previously.

17. In detail

Indicates a deeper dive into information.

Points out specifics. Similar meaning to “specifically” or “especially.”

19. This means that

Explains implications and/or interprets the meaning of the Results section .

20. Moreover

Expands a prior point to a broader one that shows the greater context or wider argument.

Best Words and Phrases for Giving Examples

21. for instance.

Provides a specific case that fits into the point being made.

22. As an illustration

Demonstrates a point in full or in part.

23. To illustrate

Shows a clear picture of the point being made.

24. For example

Presents a particular instance. Same meaning as “for instance.”

25. Such as

Lists specifics that comprise a broader category or assertion being made.

26. Including

Offers examples as part of a larger list.

27. Notably

Adverb highlighting an important example. Similar meaning to “especially.”

28. Especially

Adverb that emphasizes a significant instance.

29. In particular

Draws attention to a specific point.

30. To name a few

Indicates examples than previously mentioned are about to be named.

Best Words and Phrases for Comparing and Contrasting

31. however.

Introduces a contrasting idea.

32. On the other hand

Highlights an alternative view or fact.

33. Conversely

Indicates an opposing or reversed idea to the one just mentioned.

34. Similarly

Shows likeness or parallels between two ideas, objects, or situations.

35. Likewise

Indicates agreement with a previous point.

36. In contrast

Draws a distinction between two points.

37. Nevertheless

Introduces a contrasting point, despite what has been said.

38. Whereas

Compares two distinct entities or ideas.

Indicates a contrast between two points.

Signals an unexpected contrast.

Best Words and Phrases to use in a Conclusion section

41. in conclusion.

Signifies the beginning of the closing argument.

42. To sum up

Offers a brief summary.

43. In summary

Signals a concise recap.

44. Ultimately

Reflects the final or main point.

45. Overall

Gives a general concluding statement.

Indicates a resulting conclusion.

Demonstrates a logical conclusion.

48. Therefore

Connects a cause and its effect.

49. It can be concluded that

Clearly states a conclusion derived from the data.

50. Taking everything into consideration

Reflects on all the discussed points before concluding.

Edit Your Research Terms and Phrases Before Submission

Using these phrases in the proper places in your research papers can enhance the clarity, flow, and persuasiveness of your writing, especially in the Introduction section and Discussion section, which together make up the majority of your paper’s text in most academic domains.

However, it's vital to ensure each phrase is contextually appropriate to avoid redundancy or misinterpretation. As mentioned at the top of this article, the best way to do this is to 1) use an AI text editor , free AI paraphrasing tool or AI proofreading tool while you draft to enhance your writing, and 2) consult a professional proofreading service like Wordvice, which has human editors well versed in the terminology and conventions of the specific subject area of your academic documents.

For more detailed information on using AI tools to write a research paper and the best AI tools for research , check out the Wordvice AI Blog .

Related Words and Phrases

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Synonyms and antonyms of study in English

• TO LEARN SOMETHING

Synonyms and examples

• TO STUDY SOMETHING

study | American Thesaurus

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noun as in reviewing

Strong matches

• criticizing
• investigating
• summarizing

noun as in speculation

Strongest matches

• cerebration
• consideration
• contemplation
• deliberation
• excogitation
• guesstimate
• supposition

Weak matches

• shot in the dark
• sneaking suspicion
• stab in the dark

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Example sentences.

I had been studying abroad in London, and came back to finish the semester at Tufts.

He has been living, studying and working in the United States for the past year and a half.

He holds them on his belly and looks at them with a magnifying glass, studying possible escape routes.

All this time, even back when he was studying at Purdue, Pragnell was an avid home-brewer.

Archaeologists have an uncanny ability to ignore the discomforts and channel the time period and the people they're studying.

A very interesting way of studying Ferns is that of collecting the fronds of the species which the hunter may come across.

He simply devoured books, studying every detail of construction, and learning a great deal as to style and effect.

After studying my formulas let the pupil endeavour in each case to find a better one himself.

They not only do their studying aloud, but they talk very loud, as if each one were trying to make more noise than his neighbour.

One of them is taking lessons of Deppe, and the other has a great talent for drawing, and has been two years studying in Berlin.

Related Words

Words related to studying are not direct synonyms, but are associated with the word studying . Browse related words to learn more about word associations.

noun as in inspecting

noun as in theory, guess

On this page you'll find 51 synonyms, antonyms, and words related to studying, such as: analyzing, criticizing, critiquing, evaluating, examining, and investigating.

From Roget's 21st Century Thesaurus, Third Edition Copyright © 2013 by the Philip Lief Group.

Synonyms of 'research' in American English

Synonyms of 'research' in british english, additional synonyms.

Browse alphabetically research

• researching
• resemblance
• All ENGLISH synonyms that begin with 'R'

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Synonyms of researches

• as in investigations
• as in explores
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Thesaurus Definition of researches

 (Entry 1 of 2)

Synonyms & Similar Words

• investigations
• examinations
• explorations
• disquisitions
• inspections
• inquisitions
• questionnaires
• interrogations
• reinvestigations
• questionaries
• cross - examinations
• goings - over
• self - reflections
• self - examinations
• soul - searchings
• self - explorations
• self - questionings
• self - scrutinies

Thesaurus Definition of researches  (Entry 2 of 2)

• investigates
• looks (into)
• delves (into)
• digs (into)
• inquires (into)
• checks up on
• checks into
• skims (through)
• thumbs (through)
• reinvestigates

Thesaurus Entries Near researches

researchers

researching

Cite this Entry

“Researches.” Merriam-Webster.com Thesaurus , Merriam-Webster, https://www.merriam-webster.com/thesaurus/researches. Accessed 5 Jun. 2024.

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Nglish: Translation of researches for Spanish Speakers

Britannica English: Translation of researches for Arabic Speakers

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GPT-4 is better than humans at financial forecasting, new study shows

• OpenAI's GPT-4 is better than humans at analyzing financial statements and making forecasts, according to a new study.
• "Even without any narrative or industry-specific information, the LLM outperforms financial analysts in its ability to predict earnings changes," the study found.
• Trading strategies based on GPT-4 also delivered more profitable results than the stock market.

OpenAI's GPT-4 proved to be a better financial analyst than humans, according to a new study.

The findings could upend the financial services industry that, like other business sectors, is racing to adopt generative AI technologies.

According to the study conducted by the Booth School of Business at the University of Chicago, the large language model did a better job of analyzing financial statements and making predictions based on those statements.

"Even without any narrative or industry-specific information, the LLM outperforms financial analysts in its ability to predict earnings changes," the study said. "The LLM exhibits a relative advantage over human analysts in situations when the analysts tend to struggle."

The study utilized "chain-of-thought" prompts that directed GPT-4 to identify trends in financial statements and calculate different financial ratios. From there, the large language model analyzed the information and predicted future earnings results.

"When we use the chain of thought prompt to emulate human reasoning, we find that GPT achieves an accuracy of 60%, which is remarkably higher than that achieved by the analysts," the study said. The human analysts were closer to the low 50% range with regard to prediction accuracy.

The large language models' ability to recognize financial patterns and business concepts with incomplete information suggests that the technology should play a key role in financial decision-making going forward, according to the study's authors.

Finally, the study found that applying GPT-4's financial acumen to trading strategies produced more profitable trading, with higher share ratios and alpha that ultimately beat the stock market.

"We find that the long-short strategy based on GPT forecasts outperforms the market and generates significant alphas and Sharpe ratios," the study said. 

• Main content

How Does “Not” Affect What We Understand? Scientists Find Negation Mitigates Our Interpretation of Phrases

Photo credit: Bill Chizek/Getty Images.

When we’re told “This coffee is hot” upon being served a familiar caffeinated beverage at our local diner or cafe, the message is clear. But what about when we’re told “This coffee is not hot”? Does that mean we think it’s cold ? Or room temperature? Or just warm?

A team of scientists has now identified how our brains work to process phrases that include negation (i.e., “not”), revealing that it mitigates rather than inverts meaning—in other words, in our minds, negation merely reduces the temperature of our coffee and does not make it “cold.”

“We now have a firmer sense of how negation operates as we try to make sense of the phrases we process,” explains Arianna Zuanazzi, a postdoctoral fellow in New York University’s Department of Psychology at the time of the study and the lead author of the paper , which appears in the journal PLOS Biology . “In identifying that negation serves as a mitigator of adjectives—‘bad’ or ‘good,’ ‘sad’ or ‘happy,’ and ‘cold’ or ‘hot’—we also have a better understanding of how the brain functions to interpret subtle changes in meaning.”

In an array of communications, ranging from advertising to legal filings, negation is often used intentionally to mask a clear understanding of a phrase. In addition, large language models in AI tools have difficulty interpreting passages containing negation. The researchers say that their results show how humans process such phrases while also potentially pointing to ways to understand and improve AI functionality.

While the ability of human language to generate novel or complex meanings through the combination of words has long been known, how this process occurs is not well understood.

To address this, Zuanazzi and her colleagues conducted a series of experiments to measure how participants interpreted phrases and also monitored participants’ brain activity during these tasks—in order to precisely gauge related neurological function.

Large language models in AI tools have difficulty interpreting passages containing negation—such as "no" or "not." The researchers say that their results show how humans process such phrases while also potentially pointing to ways to understand and improve AI functionality.

In the experiments, participants read—on a computer monitor—adjective phrases with and without negation (e.g., “really not good” and “really really good”) and rated their meaning on a scale from 1 (“really really bad”) to 10 (“really really good”) using a mouse cursor. This scale was designed, in part, to determine if participants interpreted phrases with negation as the  opposite  of those without negation—in other words, did they interpret “really not good” as “bad”—or, instead, as something more measured?

Here, the researchers found that participants took longer to interpret phrases with negation than they did phrases without negation—indicating, not surprisingly given the greater complexity, that negation slows down our processing of meaning. In addition, drawing from how the participants moved their cursors, negated phrases were first interpreted as affirmative (i.e., “not hot” was initially interpreted as closer to “hot” than to “cold”), but later shifted to a mitigated meaning, suggesting that, for instance, “not hot” is not interpreted as either “hot” or “cold,” but, rather, as something between “hot” and “cold.”

The scientists also used magnetoencephalography (MEG) to measure the magnetic fields generated by the electrical activity of participants’ brains while they were performing these phrase-interpretation tasks. As with the behavioral experiments, neural representations of polar adjectives such as “cold” and “hot” were made more similar by negation, suggesting that the meaning of “not hot” is interpreted as “less hot” and the meaning of “not cold” as “less cold,” becoming less distinguishable. In sum, neural data matched what was observed for the mouse movements in the behavioral experiments: negation does not invert the meaning of “hot” to “cold,” but rather weakens or mitigates its representation along the semantic continuum between “cold” and “hot.”

“This research spotlights the complexity that goes into language comprehension, showing that this cognitive process goes above and beyond the sum of the processing of individual word meanings,” observes Zuanazzi, now at the Child Mind Institute.

The paper’s other authors were: Pablo Ripollés, an assistant professor in NYU’s Department of Psychology and associate director of Music and Audio Research Laboratory at NYU’s Steinhardt School of Culture, Education, and Human Development; Jean-Rémi King, a researcher at France’s École Normale Supérieure; Wy Ming Lin, a doctoral student at the University of Tübingen; Laura Gwilliams, an NYU doctoral student at the time of the study; and David Poeppel, a professor in NYU’s Department of Psychology and managing director of the Ernst Strüngmann Institute for Neuroscience in Frankfurt, Germany.

The research was supported by a grant from the National Science Foundation (2043717).

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Study Bibles: A Shield against Misinterpreting Scripture

This update is related to the Crossway Global Ministry Fund campaign.

Breaking the Trend

When someone we trust tells us something of importance, we’re likely to believe them. And when someone we trust is in a position of authority, we’re even more likely to believe what they tell us. But Isaac Odeyemi, a pastor in Lagos, Nigeria, has identified that though local pastors are well-meaning, many don’t preach the full truth of the gospel. This is due to the simple reality that they were never taught the full gospel truth in the first place.

How might one break this vicious cycle? Through the Global Ministry Fund , donors to Crossway made it possible for Isaac to receive an ESV Global Study Bible . Ministry partner Lux in Tenebris (LIT) provides training and resources for pastors throughout Nigeria to support gospel work, and through partnership with Crossway they have received ESV Global Study Bibles to give to pastors and seminary students like Isaac.

We recently talked with Isaac about his experience of coming to a fuller understanding of the Bible, and how he now lives and serves in light of God’s Word.

How did you come to know Jesus as your Lord and Savior?

I was born into a Christian home in Lagos, Nigeria. It was normal for my family to go to church while I was growing up. But until I was 18, I went to church just because my parents required me to. Just after high school someone invited me to a different church from the one I had always attended. This church was different from the church where I grew up. My church weekly preached a message and prayed, but they never preached with an invitation for people to be born again. I had never heard of this concept. But when I went to this new church I encountered it for the first time. At the end of the message the pastor explained that in order to know Christ you must be born again. On that day my faith journey started. Shortly after that, I applied and was accepted to a seminary where I embarked on my life’s calling to pastoral work for the Lord.

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Why did you feel the Lord calling you to pastoral ministry?

In Nigeria, it’s difficult to find a church that preaches the truth. But from my experience, most church attendees don’t know this. I’ve now been involved in the life of the church for decades, and during that time I’ve seen many different ideas that people call “truth.” A very popular message preached in Nigeria is a mixture of truth and falsehood, which makes it hard and confusing to understand the real truth. So receiving the opportunity to attend the seminary connected to Sovereign Grace Bible Church was an incredible answer to prayer. When I look back at the place I was at theologically before attending seminary, I realize that I really didn’t fully understand what it meant to be a Christian.

I know of a friend who could clearly see this mixture of truth and falsehood was being taught in his church. He wasn’t comfortable with this, so he left the church and started his own Bible study. But after months of doing this without important biblical structures of a church, he stopped believing. He’s no longer a Christian. He didn’t have people coming alongside him as he was studying God’s Word to encourage and challenge him and to hold him accountable. He’s one example of what happens to many people. I pray that the Spirit would strengthen me to preach the truth so that these scenarios don’t happen.

Access to God’s Word is important to understand and point out the difference between this mixture of truth and falsehood. Do Nigerians have access to either text-only or study Bibles?

It’s not difficult for a Nigerian in Lagos to find a Bible if he has money. There are some Christian bookshops where he could purchase one. But many are resistant or hesitant to get a Bible, so it is common for me to go into a church to preach and many of the congregants don’t have a personal copy of the Bible.

But study Bibles are very rare. Most Nigerians won’t have a clue what a study Bible is if you asked. As a seminary teacher now, I have many students also who don’t know what a study Bible is. I encourage them to try to find a study Bible if they are able, because I think it is very important that each pastor has access to one of these study Bibles.

How has the Global Study Bible impacted your understanding of God’s Word?

I was given my Global Study Bible about one year ago. It has been very helpful for me in both my personal faith walk and in my work as a teacher in the seminary.

Personally, when I first received my Global Study Bible , two things stood out to me. First, this study Bible is a great size while still including all of the study notes, maps, and many helpful articles that help us as pastors. I can put it in my bag to bring with me to church, class, or visiting a congregant. Second, it has personally encouraged me in my walk with the Lord. I personally read it during my own study and devotional times. It’s my goal to read through all the books of the Bible using the Global Study Bible . It will help me to be able to interpret every passage correctly, especially when I have questions about what I’m reading and studying. In the churches I’ve attended, there are often misinterpretations of Scripture, especially in the way it is applied by the pastor. But this is a resource that will help the pastor and any congregants who have a study Bible to stay in line with what God’s Word is saying.

As a teacher, whenever I go to class, I bring my study Bible with me because I’ve found that it helps me to be able to answer questions with theological accuracy. Students will often ask questions to clarify their interpretation of a Scripture passage. If I don’t know the answer or want to be sure that my answer is theologically accurate, I read the study Bible notes.

Do you see a need in your ministry context for study Bibles?

Absolutely. When my students see me using my Global Study Bible , they will often ask, “how can I get a Global Study Bible ?” I have not answered them because I can’t promise that I would be able to get a study Bible for them. It would come as a great surprise if I came to a class with a Global Study Bible that I could distribute to each student because, like I said earlier, many people—seminary students and the general public—don’t know what a study Bible is, let alone how to get one. Many people, when they read a particular passage of Scripture, don’t have any idea what it means or how to apply it. That means they’re limited to learning about God’s Word from what the pastor says and not really what the Bible says.

By God’s grace, donors to Crossway continue to support the Global Ministry Fund , allowing resources like the ESV Global Study Bible to be distributed to Isaac and other pastors, church leaders, and lay believers in their faith. You’re invited to support this work as we continue to care for the spiritual needs of believers around the world by providing them with theologically sound books and ESV Bibles. The Lord is at work in the lives of believers everywhere, so join us as we take part in what the Lord is doing!

Pray for Isaac’s faith to continue to grow and be an example for his students and others in his spheres of influence.

Pray for the ministry of LIT as they continue to support gospel work and equip pastors throughout Nigeria with Bibles. Pray that the gospel would go forth, even when the spiritual environment is challenging.

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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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