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Special Report

McKinsey Technology Trends Outlook 2023

(81 pages)

After a tumultuous 2022 for technology investment and talent, the first half of 2023 has seen a resurgence of enthusiasm about technology’s potential to catalyze progress in business and society. Generative AI deserves much of the credit for ushering in this revival, but it stands as just one of many advances on the horizon that could drive sustainable, inclusive growth and solve complex global challenges.

To help executives track the latest developments, the McKinsey Technology Council  has once again identified and interpreted the most significant technology trends unfolding today. While many trends are in the early stages of adoption and scale, executives can use this research to plan ahead by developing an understanding of potential use cases and pinpointing the critical skills needed as they hire or upskill talent to bring these opportunities to fruition.

Our analysis examines quantitative measures of interest, innovation, and investment to gauge the momentum of each trend. Recognizing the long-term nature and interdependence of these trends, we also delve into underlying technologies, uncertainties, and questions surrounding each trend. This year, we added an important new dimension for analysis—talent. We provide data on talent supply-and-demand dynamics for the roles of most relevance to each trend. (For more, please see the sidebar, “Research methodology.”)

All of last year’s 14 trends remain on our list, though some experienced accelerating momentum and investment, while others saw a downshift. One new trend, generative AI, made a loud entrance and has already shown potential for transformative business impact.

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Research methodology

To assess the development of each technology trend, our team collected data on five tangible measures of activity: search engine queries, news publications, patents, research publications, and investment. For each measure, we used a defined set of data sources to find occurrences of keywords associated with each of the 15 trends, screened those occurrences for valid mentions of activity, and indexed the resulting numbers of mentions on a 0–1 scoring scale that is relative to the trends studied. The innovation score combines the patents and research scores; the interest score combines the news and search scores. (While we recognize that an interest score can be inflated by deliberate efforts to stimulate news and search activity, we believe that each score fairly reflects the extent of discussion and debate about a given trend.) Investment measures the flows of funding from the capital markets into companies linked with the trend. Data sources for the scores include the following:

Patents. Data on patent filings are sourced from Google Patents.

Research. Data on research publications are sourced from the Lens (www.lens.org).

News. Data on news publications are sourced from Factiva.

Searches. Data on search engine queries are sourced from Google Trends.

Investment. Data on private-market and public-market capital raises are sourced from PitchBook.

Talent demand. Number of job postings is sourced from McKinsey’s proprietary Organizational Data Platform, which stores licensed, de-identified data on professional profiles and job postings. Data is drawn primarily from English-speaking countries.

In addition, we updated the selection and definition of trends from last year’s study to reflect the evolution of technology trends:

The generative-AI trend was added since last year’s study.

We adjusted the definitions of electrification and renewables (previously called future of clean energy) and climate technologies beyond electrification and renewables (previously called future of sustainable consumption).

Data sources were updated. This year, we included only closed deals in PitchBook data, which revised downward the investment numbers for 2018–22. For future of space technologies investments, we used research from McKinsey’s Aerospace & Defense Practice.

This new entrant represents the next frontier of AI. Building upon existing technologies such as applied AI and industrializing machine learning, generative AI has high potential and applicability across most industries. Interest in the topic (as gauged by news and internet searches) increased threefold from 2021 to 2022. As we recently wrote, generative AI and other foundational models  change the AI game by taking assistive technology to a new level, reducing application development time, and bringing powerful capabilities to nontechnical users. Generative AI is poised to add as much as $4.4 trillion in economic value from a combination of specific use cases and more diffuse uses—such as assisting with email drafts—that increase productivity. Still, while generative AI can unlock significant value, firms should not underestimate the economic significance and the growth potential that underlying AI technologies and industrializing machine learning can bring to various industries.

Investment in most tech trends tightened year over year, but the potential for future growth remains high, as further indicated by the recent rebound in tech valuations. Indeed, absolute investments remained strong in 2022, at more than $1 trillion combined, indicating great faith in the value potential of these trends. Trust architectures and digital identity grew the most out of last year’s 14 trends, increasing by nearly 50 percent as security, privacy, and resilience become increasingly critical across industries. Investment in other trends—such as applied AI, advanced connectivity, and cloud and edge computing—declined, but that is likely due, at least in part, to their maturity. More mature technologies can be more sensitive to short-term budget dynamics than more nascent technologies with longer investment time horizons, such as climate and mobility technologies. Also, as some technologies become more profitable, they can often scale further with lower marginal investment. Given that these technologies have applications in most industries, we have little doubt that mainstream adoption will continue to grow.

Organizations shouldn’t focus too heavily on the trends that are garnering the most attention. By focusing on only the most hyped trends, they may miss out on the significant value potential of other technologies and hinder the chance for purposeful capability building. Instead, companies seeking longer-term growth should focus on a portfolio-oriented investment across the tech trends most important to their business. Technologies such as cloud and edge computing and the future of bioengineering have shown steady increases in innovation and continue to have expanded use cases across industries. In fact, more than 400 edge use cases across various industries have been identified, and edge computing is projected to win double-digit growth globally over the next five years. Additionally, nascent technologies, such as quantum, continue to evolve and show significant potential for value creation. Our updated analysis for 2023 shows that the four industries likely to see the earliest economic impact from quantum computing—automotive, chemicals, financial services, and life sciences—stand to potentially gain up to $1.3 trillion in value by 2035. By carefully assessing the evolving landscape and considering a balanced approach, businesses can capitalize on both established and emerging technologies to propel innovation and achieve sustainable growth.

Tech talent dynamics

We can’t overstate the importance of talent as a key source in developing a competitive edge. A lack of talent is a top issue constraining growth. There’s a wide gap between the demand for people with the skills needed to capture value from the tech trends and available talent: our survey of 3.5 million job postings in these tech trends found that many of the skills in greatest demand have less than half as many qualified practitioners per posting as the global average. Companies should be on top of the talent market, ready to respond to notable shifts and to deliver a strong value proposition to the technologists they hope to hire and retain. For instance, recent layoffs in the tech sector may present a silver lining for other industries that have struggled to win the attention of attractive candidates and retain senior tech talent. In addition, some of these technologies will accelerate the pace of workforce transformation. In the coming decade, 20 to 30 percent of the time that workers spend on the job could be transformed by automation technologies, leading to significant shifts in the skills required to be successful. And companies should continue to look at how they can adjust roles or upskill individuals to meet their tailored job requirements. Job postings in fields related to tech trends grew at a very healthy 15 percent between 2021 and 2022, even though global job postings overall decreased by 13 percent. Applied AI and next-generation software development together posted nearly one million jobs between 2018 and 2022. Next-generation software development saw the most significant growth in number of jobs (exhibit).

Image description:

Small multiples of 15 slope charts show the number of job postings in different fields related to tech trends from 2021 to 2022. Overall growth of all fields combined was about 400,000 jobs, with applied AI having the most job postings in 2022 and experiencing a 6% increase from 2021. Next-generation software development had the second-highest number of job postings in 2022 and had 29% growth from 2021. Other categories shown, from most job postings to least in 2022, are as follows: cloud and edge computing, trust architecture and digital identity, future of mobility, electrification and renewables, climate tech beyond electrification and renewables, advanced connectivity, immersive-reality technologies, industrializing machine learning, Web3, future of bioengineering, future of space technologies, generative AI, and quantum technologies.

End of image description.

This bright outlook for practitioners in most fields highlights the challenge facing employers who are struggling to find enough talent to keep up with their demands. The shortage of qualified talent has been a persistent limiting factor in the growth of many high-tech fields, including AI, quantum technologies, space technologies, and electrification and renewables. The talent crunch is particularly pronounced for trends such as cloud computing and industrializing machine learning, which are required across most industries. It’s also a major challenge in areas that employ highly specialized professionals, such as the future of mobility and quantum computing (see interactive).

Michael Chui is a McKinsey Global Institute partner in McKinsey’s Bay Area office, where Mena Issler is an associate partner, Roger Roberts  is a partner, and Lareina Yee  is a senior partner.

The authors wish to thank the following McKinsey colleagues for their contributions to this research: Bharat Bahl, Soumya Banerjee, Arjita Bhan, Tanmay Bhatnagar, Jim Boehm, Andreas Breiter, Tom Brennan, Ryan Brukardt, Kevin Buehler, Zina Cole, Santiago Comella-Dorda, Brian Constantine, Daniela Cuneo, Wendy Cyffka, Chris Daehnick, Ian De Bode, Andrea Del Miglio, Jonathan DePrizio, Ivan Dyakonov, Torgyn Erland, Robin Giesbrecht, Carlo Giovine, Liz Grennan, Ferry Grijpink, Harsh Gupta, Martin Harrysson, David Harvey, Kersten Heineke, Matt Higginson, Alharith Hussin, Tore Johnston, Philipp Kampshoff, Hamza Khan, Nayur Khan, Naomi Kim, Jesse Klempner, Kelly Kochanski, Matej Macak, Stephanie Madner, Aishwarya Mohapatra, Timo Moller, Matt Mrozek, Evan Nazareth, Peter Noteboom, Anna Orthofer, Katherine Ottenbreit, Eric Parsonnet, Mark Patel, Bruce Philp, Fabian Queder, Robin Riedel, Tanya Rodchenko, Lucy Shenton, Henning Soller, Naveen Srikakulam, Shivam Srivastava, Bhargs Srivathsan, Erika Stanzl, Brooke Stokes, Malin Strandell-Jansson, Daniel Wallance, Allen Weinberg, Olivia White, Martin Wrulich, Perez Yeptho, Matija Zesko, Felix Ziegler, and Delphine Zurkiya.

They also wish to thank the external members of the McKinsey Technology Council.

This interactive was designed, developed, and edited by McKinsey Global Publishing’s Nayomi Chibana, Victor Cuevas, Richard Johnson, Stephanie Jones, Stephen Landau, LaShon Malone, Kanika Punwani, Katie Shearer, Rick Tetzeli, Sneha Vats, and Jessica Wang.

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Special Report. McKinsey Technology Trends Outlook 2023. (81 pages) After a tumultuous 2022 for technology investment and talent, the first half of 2023 has seen a resurgence of enthusiasm about technology’s potential to catalyze progress in business and society. Generative AI deserves much of the credit for ushering in this revival, but it stands as just one of many advances on the horizon that could drive sustainable, inclusive growth and solve complex global challenges. To help executives track the latest developments, the McKinsey Technology Council  has once again identified and interpreted the most significant technology trends unfolding today. While many trends are in the early stages of adoption and scale, executives can use this research to plan ahead by developing an understanding of potential use cases and pinpointing the critical skills needed as they hire or upskill talent to bring these opportunities to fruition. Our analysis examines quantitative measures of interest, innovation, and investment to gauge the momentum of each trend. Recognizing the long-term nature and interdependence of these trends, we also delve into underlying technologies, uncertainties, and questions surrounding each trend. This year, we added an important new dimension for analysis—talent. We provide data on talent supply-and-demand dynamics for the roles of most relevance to each trend. (For more, please see the sidebar, “Research methodology.”) All of last year’s 14 trends remain on our list, though some experienced accelerating momentum and investment, while others saw a downshift. One new trend, generative AI, made a loud entrance and has already shown potential for transformative business impact. Share. Research methodology. To assess the development of each technology trend, our team collected data on five tangible measures of activity: search engine queries, news publications, patents, research publications, and investment. For each measure, we used a defined set of data sources to find occurrences of keywords associated with each of the 15 trends, screened those occurrences for valid mentions of activity, and indexed the resulting numbers of mentions on a 0–1 scoring scale that is relative to the trends studied. The innovation score combines the patents and research scores; the interest score combines the news and search scores. (While we recognize that an interest score can be inflated by deliberate efforts to stimulate news and search activity, we believe that each score fairly reflects the extent of discussion and debate about a given trend.) Investment measures the flows of funding from the capital markets into companies linked with the trend. Data sources for the scores include the following: Patents. Data on patent filings are sourced from Google Patents. Research. Data on research publications are sourced from the Lens (www.lens.org). News. Data on news publications are sourced from Factiva. Searches. Data on search engine queries are sourced from Google Trends. Investment. Data on private-market and public-market capital raises are sourced from PitchBook. Talent demand. Number of job postings is sourced from McKinsey’s proprietary Organizational Data Platform, which stores licensed, de-identified data on professional profiles and job postings. Data is drawn primarily from English-speaking countries. In addition, we updated the selection and definition of trends from last year’s study to reflect the evolution of technology trends: The generative-AI trend was added since last year’s study. We adjusted the definitions of electrification and renewables (previously called future of clean energy) and climate technologies beyond electrification and renewables (previously called future of sustainable consumption). Data sources were updated. This year, we included only closed deals in PitchBook data, which revised downward the investment numbers for 2018–22. For future of space technologies investments, we used research from McKinsey’s Aerospace & Defense Practice. This new entrant represents the next frontier of AI. Building upon existing technologies such as applied AI and industrializing machine learning, generative AI has high potential and applicability across most industries. Interest in the topic (as gauged by news and internet searches) increased threefold from 2021 to 2022. As we recently wrote, generative AI and other foundational models  change the AI game by taking assistive technology to a new level, reducing application development time, and bringing powerful capabilities to nontechnical users. Generative AI is poised to add as much as $4.4 trillion in economic value from a combination of specific use cases and more diffuse uses—such as assisting with email drafts—that increase productivity. Still, while generative AI can unlock significant value, firms should not underestimate the economic significance and the growth potential that underlying AI technologies and industrializing machine learning can bring to various industries. Investment in most tech trends tightened year over year, but the potential for future growth remains high, as further indicated by the recent rebound in tech valuations. Indeed, absolute investments remained strong in 2022, at more than $1 trillion combined, indicating great faith in the value potential of these trends. Trust architectures and digital identity grew the most out of last year’s 14 trends, increasing by nearly 50 percent as security, privacy, and resilience become increasingly critical across industries. Investment in other trends—such as applied AI, advanced connectivity, and cloud and edge computing—declined, but that is likely due, at least in part, to their maturity. More mature technologies can be more sensitive to short-term budget dynamics than more nascent technologies with longer investment time horizons, such as climate and mobility technologies. Also, as some technologies become more profitable, they can often scale further with lower marginal investment. Given that these technologies have applications in most industries, we have little doubt that mainstream adoption will continue to grow. Organizations shouldn’t focus too heavily on the trends that are garnering the most attention. By focusing on only the most hyped trends, they may miss out on the significant value potential of other technologies and hinder the chance for purposeful capability building. Instead, companies seeking longer-term growth should focus on a portfolio-oriented investment across the tech trends most important to their business. Technologies such as cloud and edge computing and the future of bioengineering have shown steady increases in innovation and continue to have expanded use cases across industries. In fact, more than 400 edge use cases across various industries have been identified, and edge computing is projected to win double-digit growth globally over the next five years. Additionally, nascent technologies, such as quantum, continue to evolve and show significant potential for value creation. Our updated analysis for 2023 shows that the four industries likely to see the earliest economic impact from quantum computing—automotive, chemicals, financial services, and life sciences—stand to potentially gain up to $1.3 trillion in value by 2035. By carefully assessing the evolving landscape and considering a balanced approach, businesses can capitalize on both established and emerging technologies to propel innovation and achieve sustainable growth. Tech talent dynamics. We can’t overstate the importance of talent as a key source in developing a competitive edge. A lack of talent is a top issue constraining growth. There’s a wide gap between the demand for people with the skills needed to capture value from the tech trends and available talent: our survey of 3.5 million job postings in these tech trends found that many of the skills in greatest demand have less than half as many qualified practitioners per posting as the global average. Companies should be on top of the talent market, ready to respond to notable shifts and to deliver a strong value proposition to the technologists they hope to hire and retain. For instance, recent layoffs in the tech sector may present a silver lining for other industries that have struggled to win the attention of attractive candidates and retain senior tech talent. In addition, some of these technologies will accelerate the pace of workforce transformation. In the coming decade, 20 to 30 percent of the time that workers spend on the job could be transformed by automation technologies, leading to significant shifts in the skills required to be successful. And companies should continue to look at how they can adjust roles or upskill individuals to meet their tailored job requirements. Job postings in fields related to tech trends grew at a very healthy 15 percent between 2021 and 2022, even though global job postings overall decreased by 13 percent. Applied AI and next-generation software development together posted nearly one million jobs between 2018 and 2022. Next-generation software development saw the most significant growth in number of jobs (exhibit). Image description: Small multiples of 15 slope charts show the number of job postings in different fields related to tech trends from 2021 to 2022. Overall growth of all fields combined was about 400,000 jobs, with applied AI having the most job postings in 2022 and experiencing a 6% increase from 2021. Next-generation software development had the second-highest number of job postings in 2022 and had 29% growth from 2021. Other categories shown, from most job postings to least in 2022, are as follows: cloud and edge computing, trust architecture and digital identity, future of mobility, electrification and renewables, climate tech beyond electrification and renewables, advanced connectivity, immersive-reality technologies, industrializing machine learning, Web3, future of bioengineering, future of space technologies, generative AI, and quantum technologies. End of image description. This bright outlook for practitioners in most fields highlights the challenge facing employers who are struggling to find enough talent to keep up with their demands. The shortage of qualified talent has been a persistent limiting factor in the growth of many high-tech fields, including AI, quantum technologies, space technologies, and electrification and renewables. The talent crunch is particularly pronounced for trends such as cloud computing and industrializing machine learning, which are required across most industries. It’s also a major challenge in areas that employ highly specialized professionals, such as the future of mobility and quantum computing (see interactive). Michael Chui is a McKinsey Global Institute partner in McKinsey’s Bay Area office, where Mena Issler is an associate partner, Roger Roberts  is a partner, and Lareina Yee  is a senior partner. The authors wish to thank the following McKinsey colleagues for their contributions to this research: Bharat Bahl, Soumya Banerjee, Arjita Bhan, Tanmay Bhatnagar, Jim Boehm, Andreas Breiter, Tom Brennan, Ryan Brukardt, Kevin Buehler, Zina Cole, Santiago Comella-Dorda, Brian Constantine, Daniela Cuneo, Wendy Cyffka, Chris Daehnick, Ian De Bode, Andrea Del Miglio, Jonathan DePrizio, Ivan Dyakonov, Torgyn Erland, Robin Giesbrecht, Carlo Giovine, Liz Grennan, Ferry Grijpink, Harsh Gupta, Martin Harrysson, David Harvey, Kersten Heineke, Matt Higginson, Alharith Hussin, Tore Johnston, Philipp Kampshoff, Hamza Khan, Nayur Khan, Naomi Kim, Jesse Klempner, Kelly Kochanski, Matej Macak, Stephanie Madner, Aishwarya Mohapatra, Timo Moller, Matt Mrozek, Evan Nazareth, Peter Noteboom, Anna Orthofer, Katherine Ottenbreit, Eric Parsonnet, Mark Patel, Bruce Philp, Fabian Queder, Robin Riedel, Tanya Rodchenko, Lucy Shenton, Henning Soller, Naveen Srikakulam, Shivam Srivastava, Bhargs Srivathsan, Erika Stanzl, Brooke Stokes, Malin Strandell-Jansson, Daniel Wallance, Allen Weinberg, Olivia White, Martin Wrulich, Perez Yeptho, Matija Zesko, Felix Ziegler, and Delphine Zurkiya. They also wish to thank the external members of the McKinsey Technology Council. This interactive was designed, developed, and edited by McKinsey Global Publishing’s Nayomi Chibana, Victor Cuevas, Richard Johnson, Stephanie Jones, Stephen Landau, LaShon Malone, Kanika Punwani, Katie Shearer, Rick Tetzeli, Sneha Vats, and Jessica Wang. Explore a career with us. Search Openings.