Despite challenging overall market conditions in 2023, continuing investments in frontier technologies promise substantial future growth in enterprise adoption. Generative AI (gen AI) has been a standout trend since 2022, with the extraordinary uptick in interest and investment in this technology unlocking innovative possibilities across interconnected trends such as robotics and immersive reality. While the macroeconomic environment with elevated interest rates has affected equity capital investment and hiring, underlying indicators—including optimism, innovation, and longer-term talent needs—reflect a positive long-term trajectory in the 15 technology trends we analyzed.
These are among the findings in the latest McKinsey Technology Trends Outlook, in which the McKinsey Technology Council identified the most significant technology trends unfolding today. This research is intended to help executives plan ahead by developing an understanding of potential use cases, sources of value, adoption drivers, and the critical skills needed to bring these opportunities to fruition.
Our analysis examines quantitative measures of interest, innovation, investment, and talent to gauge the momentum of each trend. Recognizing the long-term nature and interdependence of these trends, we also delve into the underlying technologies, uncertainties, and questions surrounding each trend. (For more about new developments in our research, please see the sidebar “What’s new in this year’s analysis”; for more about the research itself, please see the sidebar “Research methodology.”)
New and notable
The two trends that stood out in 2023 were gen AI and electrification and renewables. Gen AI has seen a spike of almost 700 percent in Google searches from 2022 to 2023, along with a notable jump in job postings and investments. The pace of technology innovation has been remarkable. Over the course of 2023 and 2024, the size of the prompts that large language models (LLMs) can process, known as “context windows,” spiked from 100,000 to two million tokens. This is roughly the difference between adding one research paper to a model prompt and adding about 20 novels to it. And the modalities that gen AI can process have continued to increase, from text summarization and image generation to advanced capabilities in video, images, audio, and text. This has catalyzed a surge in investments and innovation aimed at advancing more powerful and efficient computing systems. The large foundation models that power generative AI, such as LLMs, are being integrated into various enterprise software tools and are also being employed for diverse purposes such as powering customer-facing chatbots, generating ad campaigns, accelerating drug discovery, and more. We expect this expansion to continue, pushing the boundaries of AI capabilities. Senior leaders’ awareness of gen AI innovation has increased interest, investment, and innovation in AI technologies, such as robotics, which is a new addition to our trends analysis this year. Advancements in AI are ushering in a new era of more capable robots, spurring greater innovation and a wider range of deployments.
Electrification and renewables was the other trend that bucked the economic headwinds, posting the highest investment and interest scores among all the trends we evaluated. Job postings for this sector also showed a modest increase.
Although many trends faced declines in investment and hiring in 2023, the long-term outlook remains positive. This optimism is supported by the continued longer-term growth in job postings for the analyzed trends (up 8 percent from 2021 to 2023) and enterprises’ continued innovation and heightened interest in harnessing these technologies, particularly for future growth.
In 2023, technology equity investments fell by 30 to 40 percent to approximately $570 billion due to rising financing costs and a cautious near-term growth outlook, prompting investors to favor technologies with strong revenue and margin potential. This approach aligns with the strategic perspective leading companies are adopting, in which they recognize that fully adopting and scaling cutting-edge technologies is a long-term endeavor. This recognition is evident when companies diversify their investments across a portfolio of several technologies, selectively intensifying their focus on areas most likely to push technological boundaries forward. While many technologies have maintained cautious investment profiles over the past year, gen AI saw a sevenfold increase in investments, driven by substantial advancements in text, image, and video generation.
Despite an overall downturn in private equity investment, the pace of innovation has not slowed. Innovation has accelerated in the three trends that are part of the “AI revolution” group: gen AI, applied AI, and industrializing machine learning. Gen AI creates new content from unstructured data (such as text and images), applied AI leverages machine learning models for analytical and predictive tasks, and industrializing machine learning accelerates and derisks the development of machine learning solutions. Applied AI and industrializing machine learning, boosted by the widening interest in gen AI, have seen the most significant uptick in innovation, reflected in the surge in publications and patents from 2022 to 2023. Meanwhile, electrification and renewable-energy technologies continue to capture high interest, reflected in news mentions and web searches. Their popularity is fueled by a surge in global renewable capacity, their crucial roles in global decarbonization efforts, and heightened energy security needs amid geopolitical tensions and energy crises.
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The talent environment largely echoed the investment picture in tech trends in 2023. The technology sector faced significant layoffs, particularly among large technology companies, with job postings related to the tech trends we studied declining by 26 percent—a steeper drop than the 17 percent decrease in global job postings overall. The greater decline in demand for tech-trends-related talent may have been fueled by technology companies’ cost reduction efforts amid decreasing revenue growth projections. Despite this reduction, the trends with robust investment and innovation, such as gen AI, not only maintained but also increased their job postings, reflecting a strong demand for new and advanced skills. Electrification and renewables was the other trend that saw positive job growth, partially due to public sector support for infrastructure spending.
Even with the short-term vicissitudes in talent demand, our analysis of 4.3 million job postings across our 15 tech trends underscored a wide skills gap. Compared with the global average, fewer than half the number of potential candidates have the high-demand tech skills specified in job postings. Despite the year-on-year decreases for job postings in many trends from 2022 to 2023, the number of tech-related job postings in 2023 still represented an 8 percent increase from 2021, suggesting the potential for longer-term growth (Exhibit 1).
Exhibit 1
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Despite a one-year drop in job postings, demand for jobs in many technology trends has increased over two years.
Tech trend job postings,1 millions
aaaBESbswyBESbswyBESbswyBESbswyBESbswyBESbswyBESbswyBESbswyBESbswy
2021–23 cumulative change, %
2021–23 annual change, %
Despite a one-year drop in job postings, demand for jobs in many technology trends has increased over two years.
Tech trend job postings,1 millions
Enterprise technology adoption momentum
The trajectory of enterprise technology adoption is often described as an S-curve that traces the following pattern: technical innovation and exploration, experimenting with the technology, initial pilots in the business, scaling the impact throughout the business, and eventual fully scaled adoption (Exhibit 2). This pattern is evident in this year’s survey analysis of enterprise adoption conducted across our 15 technologies. Adoption levels vary across different industries and company sizes, as does the perceived progress toward adoption.
Exhibit 2
We see that the technologies in the S-curve’s early stages of innovation and experimenting are either on the leading edge of progress, such as quantum technologies and robotics, or are more relevant to a specific set of industries, such as bioengineering and space. Factors that could affect the adoption of these technologies include high costs, specialized applications, and balancing the breadth of technology investments against focusing on a select few that may offer substantial first-mover advantages.
As technologies gain traction and move beyond experimenting, adoption rates start accelerating, and companies invest more in piloting and scaling. We see this shift in a number of trends, such as next-generation software development and electrification. Gen AI’s rapid advancement leads among trends analyzed, about a quarter of respondents self-reporting that they are scaling its use. More mature technologies, like cloud and edge computing and advanced connectivity, continued their rapid pace of adoption, serving as enablers for the adoption of other emerging technologies as well (Exhibit 3).
Exhibit 3
The process of scaling technology adoption also requires a conducive external ecosystem where user trust and readiness, business model economics, regulatory environments, and talent availability play crucial roles. Since these ecosystem factors vary by geography and industry, we see different adoption scenarios playing out. For instance, while the leading banks in Latin America are on par with their North American counterparts in deploying gen AI use cases, the adoption of robotics in manufacturing sectors varies significantly due to differing labor costs affecting the business case for automation.
As executives navigate these complexities, they should align their long-term technology adoption strategies with both their internal capacities and the external ecosystem conditions to ensure the successful integration of new technologies into their business models. Executives should monitor ecosystem conditions that can affect their prioritized use cases to make decisions about the appropriate investment levels while navigating uncertainties and budgetary constraints on the way to full adoption (see the “Adoption developments across the globe” sections within each trend or particular use cases therein that executives should monitor). Across the board, leaders who take a long-term view—building up their talent, testing and learning where impact can be found, and reimagining the businesses for the future—can potentially break out ahead of the pack.
The 15 tech trends
This report lays out considerations for all 15 technology trends. For easier consideration of related trends, we grouped them into five broader categories: the AI revolution, building the digital future, compute and connectivity frontiers, cutting-edge engineering, and a sustainable world. Of course, there’s significant power and potential in looking across these groupings when considering trend combinations.
To describe the state of each trend, we developed scores for innovation (based on patents and research) and interest (based on news and web searches). We also sized investments in relevant technologies and rated their level of adoption by organizations.
1
2
3
4
5
250
150
75
Color = adoption level, score
(1 = frontier innovation;
5 = fully scaled)
Size = equity investment, $ billion
The AI revolution
Generative AI
Generative AI describes algorithms (such as ChatGPT) that take unstructured data as input (for example, natural language and images) to create new content, including audio, code, images, text, simulations, and videos. It can automate, augment, and accelerate work by tapping into unstructured mixed-modality data sets to generate new content in various forms.
In 2019, the interest score for Generative AI was 0.01 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.01 on the same scale. The adoption rate was scored at 4. The investment in 2019 was 4 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 4 billion dollars. By 2023, the interest score for Generative AI was 0.64. The innovation score was 0.08. The investment was 36 billion dollars. Job postings within this trend changed by 111 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$36
billion
equity investment,2023
+111%
job postings
difference,2022–23
Industries affected
Aerospace and defense
Agriculture
Automotive and assembly
Aviation, travel, and logistics
Business, legal, and professional services
Chemicals
Consumer packaged goods
Construction and building materials
Education
Electric power, natural gas, and utilities
Financial services
Healthcare systems and services
Information technology and electronics
Media and entertainment
Metals and mining
Oil and gas
Pharmaceuticals and medical products
Public and social sectors
Real estate
Retail
Semiconductors
Telecommunications
Aerospace and defense, Agriculture, Automotive and assembly, Aviation, travel, and logistics, Business, legal, and professional services, Chemicals, Consumer packaged goods, Construction and building materials, Education, Electric power, natural gas, and utilities, Financial services, Healthcare systems and services, Information technology and electronics, Media and entertainment, Metals and mining, Oil and gas, Pharmaceuticals and medical products, Public and social sectors, Real estate, Retail, Semiconductors, Telecommunications,
The AI revolution
Applied AI
Applied AI technologies and techniques use models trained through machine learning to solve classification, prediction, and control problems in order to automate activities, add or augment capabilities and offerings, and improve decision making.
In 2019, the interest score for Applied AI was 0.26 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.49 on the same scale. The adoption rate was scored at 4. The investment in 2019 was 57 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 57 billion dollars. By 2023, the interest score for Applied AI was 0.5. The innovation score was 0.98. The investment was 86 billion dollars. Job postings within this trend changed by -29 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$86
billion
equity investment,2023
–29%
job postings
difference,2022–23
Industries affected
Aerospace and defense
Agriculture
Automotive and assembly
Aviation, travel, and logistics
Business, legal, and professional services
Chemicals
Construction and building materials
Consumer packaged goods
Education
Electric power, natural gas, and utilities
Financial services
Healthcare systems and services
Information technology and electronics
Media and entertainment
Metals and mining
Oil and gas
Pharmaceuticals and medical products
Public and social sectors
Real estate
Retail
Semiconductors
Telecommunications
Aerospace and defense, Agriculture, Automotive and assembly, Aviation, travel, and logistics, Business, legal, and professional services, Chemicals, Construction and building materials, Consumer packaged goods, Education, Electric power, natural gas, and utilities, Financial services, Healthcare systems and services, Information technology and electronics, Media and entertainment, Metals and mining, Oil and gas, Pharmaceuticals and medical products, Public and social sectors, Real estate, Retail, Semiconductors, Telecommunications,
The AI revolution
Industrializing machine learning
The industrializing machine learning trend encapsulates a rapidly evolving ecosystem of software and hardware solutions that enable the acceleration and derisking of the development, deployment, and maintenance of machine learning solutions.
In 2019, the interest score for Industrializing machine learning was 0.02 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.13 on the same scale. The adoption rate was scored at 3. The investment in 2019 was 37 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 37 billion dollars. By 2023, the interest score for Industrializing machine learning was 0.04. The innovation score was 0.31. The investment was 3 billion dollars. Job postings within this trend changed by -36 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$3
billion
equity investment,2023
–36%
job postings
difference,2022–23
Industries affected
Aerospace and defense
Agriculture
Automotive and assembly
Aviation, travel, and logistics
Business, legal, and professional services
Chemicals
Consumer packaged goods
Education
Electric power, natural gas, and utilities
Financial services
Healthcare systems and services
Information technology and electronics
Media and entertainment
Metals and mining
Oil and gas
Pharmaceuticals and medical products
Public and social sectors
Real estate
Retail
Semiconductors
Telecommunications
Aerospace and defense, Agriculture, Automotive and assembly, Aviation, travel, and logistics, Business, legal, and professional services, Chemicals, Consumer packaged goods, Education, Electric power, natural gas, and utilities, Financial services, Healthcare systems and services, Information technology and electronics, Media and entertainment, Metals and mining, Oil and gas, Pharmaceuticals and medical products, Public and social sectors, Real estate, Retail, Semiconductors, Telecommunications,
Building the digital future
Next-generation software development
Next-generation software development includes tools and technologies that enable modern code deployment pipelines and automated code generation, testing, refactoring, and translation. These can improve application quality and development processes.
In 2019, the interest score for Next-generation software development was 0.03 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.14 on the same scale. The adoption rate was scored at 3. The investment in 2019 was 54 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 54 billion dollars. By 2023, the interest score for Next-generation software development was 0.03. The innovation score was 0.2. The investment was 17 billion dollars. Job postings within this trend changed by -37 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$17
billion
equity investment,2023
–37%
job postings
difference,2022–23
Industries affected
Advanced industries
Business, legal, and professional services
Consumer packaged goods
Financial services
Healthcare systems and services
Information technology and electronics
Manufacturing
Media and entertainment
Telecommunications
Advanced industries, Business, legal, and professional services, Consumer packaged goods, Financial services, Healthcare systems and services, Information technology and electronics, Manufacturing, Media and entertainment, Telecommunications,
Building the digital future
Digital trust and cybersecurity
The digital trust and cybersecurity trend encompasses the technologies behind trust architectures and digital identity, cybersecurity, and Web3. These technologies enable organizations to build, scale, and maintain the trust of stakeholders.
In 2019, the interest score for Digital trust and cybersecurity was 0.18 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.11 on the same scale. The adoption rate was scored at 3. The investment in 2019 was 25 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 25 billion dollars. By 2023, the interest score for Digital trust and cybersecurity was 0.41. The innovation score was 0.18. The investment was 34 billion dollars. Job postings within this trend changed by -34 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$34
billion
equity investment,2023
–34%
job postings
difference,2022–23
Industries affected
Aerospace and defense
Aviation, travel, and logistics
Consumer packaged goods
Education
Electric power, natural gas, and utilities
Financial services
Healthcare systems and services
Information technology and electronics
Media and entertainment
Pharmaceutical and medical products
Public and social sectors
Retail
Telecommunications
Aerospace and defense, Aviation, travel, and logistics, Consumer packaged goods, Education, Electric power, natural gas, and utilities, Financial services, Healthcare systems and services, Information technology and electronics, Media and entertainment, Pharmaceutical and medical products, Public and social sectors, Retail, Telecommunications,
Compute and connectivity frontiers
Advanced connectivity
Advanced connectivity covers wireless low-power networks, 5G and 6G cellular, Wi-Fi 6 and 7, low-Earth-orbit satellites, and other telecommunications technologies.
In 2019, the interest score for Advanced connectivity was 0.17 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.49 on the same scale. The adoption rate was scored at 4. The investment in 2019 was 37 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 37 billion dollars. By 2023, the interest score for Advanced connectivity was 0.23. The innovation score was 0.63. The investment was 29 billion dollars. Job postings within this trend changed by -24 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$29
billion
equity investment,2023
–24%
job postings
difference,2022–23
Industries affected
Aerospace and defense
Agriculture
Automotive and assembly
Aviation, travel, and logistics
Construction and building materials
Electric power, natural gas, and utilities
Financial services
Healthcare systems and services
Information technology and electronics
Media and entertainment
Manufacturing
Metals and mining
Oil and gas
Retail
Telecommunications
Aerospace and defense, Agriculture, Automotive and assembly, Aviation, travel, and logistics, Construction and building materials, Electric power, natural gas, and utilities, Financial services, Healthcare systems and services, Information technology and electronics, Media and entertainment, Manufacturing, Metals and mining, Oil and gas, Retail, Telecommunications,
Compute and connectivity frontiers
Immersive-reality technologies
Immersive-reality technologies enable real-time interactions in three-dimensional virtual worlds (that could incorporate the actual physical world). A virtual world can range from a fully computer-generated space in virtual reality (VR), to mixed reality (MR), all the way to augmented reality (AR), where computer-generated objects are superimposed on the real world. These technologies leverage spatial computing to interpret physical space (for example, by leveraging sensors and cameras such as in a VR headset to recognize gestures) and simulate the addition of data, objects, and people to the virtual world.
In 2019, the interest score for Immersive-reality technologies was 0.09 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.15 on the same scale. The adoption rate was scored at 2. The investment in 2019 was 5 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 5 billion dollars. By 2023, the interest score for Immersive-reality technologies was 0.12. The innovation score was 0.24. The investment was 6 billion dollars. Job postings within this trend changed by -36 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$6
billion
equity investment,2023
–36%
job postings
difference,2022–23
Industries affected
Aerospace and defense
Automotive and assembly
Aviation, travel, and logistics
Construction and building materials
Consumer packaged goods
Education
Electric power, natural gas, and utilities
Financial services
Healthcare systems and services
Information technology and electronics
Media and entertainment
Real estate
Retail
Aerospace and defense, Automotive and assembly, Aviation, travel, and logistics, Construction and building materials, Consumer packaged goods, Education, Electric power, natural gas, and utilities, Financial services, Healthcare systems and services, Information technology and electronics, Media and entertainment, Real estate, Retail,
Compute and connectivity frontiers
Cloud and edge computing
Cloud and edge computing refers to workloads that are distributed across locations, such as hyperscale remote data centers, regional centers, and local nodes, to optimize for latency, data-transfer costs, adherence to data sovereignty regulations, autonomy over data, security considerations, etcetera.
In 2019, the interest score for Cloud and edge computing was 0.04 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.14 on the same scale. The adoption rate was scored at 4. The investment in 2019 was 50 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 50 billion dollars. By 2023, the interest score for Cloud and edge computing was 0.05. The innovation score was 0.2. The investment was 54 billion dollars. Job postings within this trend changed by -38 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$54
billion
equity investment,2023
–38%
job postings
difference,2022–23
Industries affected
Aerospace and defense
Automotive and assembly
Aviation, travel, and logistics
Business, legal, and professional services
Chemicals
Electric power, natural gas, and utilities
Financial services
Healthcare systems and services
Information technology and electronics
Manufacturing
Media and entertainment
Pharmaceuticals and medical products
Retail
Semiconductors
Telecommunications
Aerospace and defense, Automotive and assembly, Aviation, travel, and logistics, Business, legal, and professional services, Chemicals, Electric power, natural gas, and utilities, Financial services, Healthcare systems and services, Information technology and electronics, Manufacturing, Media and entertainment, Pharmaceuticals and medical products, Retail, Semiconductors, Telecommunications,
Compute and connectivity frontiers
Quantum technologies
Quantum-based technologies make use of the unique properties of quantum mechanics to execute certain complex calculations exponentially faster than classical computers, secure communication networks, and produce sensors with higher sensitivity levels than their classical counterparts.
In 2019, the interest score for Quantum technologies was 0.01 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.02 on the same scale. The adoption rate was scored at 1. The investment in 2019 was 0 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 0 billion dollars. By 2023, the interest score for Quantum technologies was 0.02. The innovation score was 0.04. The investment was 1 billion dollars. Job postings within this trend changed by -17 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$1
billion
equity investment,2023
–17%
job postings
difference,2022–23
Industries affected
Aerospace and defense
Automotive and assembly
Aviation, travel, and logistics
Chemicals
Financial services
Information technology and electronics
Pharmaceuticals and medical products
Telecommunications
Aerospace and defense, Automotive and assembly, Aviation, travel, and logistics, Chemicals, Financial services, Information technology and electronics, Pharmaceuticals and medical products, Telecommunications,
Cutting-edge engineering
Future of robotics
The future of robotics covers the advancement of robots from handling fixed-purpose and preprogrammed tasks to being capable of adapting to new, real-life inputs with increasing degrees of autonomy and dexterity.
In 2019, the interest score for Future of robotics was 0.01 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.03 on the same scale. The adoption rate was scored at 2. The investment in 2019 was 3 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 3 billion dollars. By 2023, the interest score for Future of robotics was 0.01. The innovation score was 0.05. The investment was 6 billion dollars. Job postings within this trend changed by -20 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$6
billion
equity investment,2023
–20%
job postings
difference,2022–23
Industries affected
Agriculture
Automotive and assembly
Chemicals
Consumer packaged goods
Information technology and electronics
Manufacturing
Metals and mining
Oil and gas
Pharmaceutical and medical products
Retail
Semiconductors
Telecommunications
Agriculture, Automotive and assembly, Chemicals, Consumer packaged goods, Information technology and electronics, Manufacturing, Metals and mining, Oil and gas, Pharmaceutical and medical products, Retail, Semiconductors, Telecommunications,
Cutting-edge engineering
Future of mobility
Mobility technologies cover autonomous and electric vehicles, urban air mobility, and autonomous-driving, connectivity, electrification, and shared-mobility (ACES) technologies, with the aim to improve the efficiency and sustainability of land and air transportation.
In 2019, the interest score for Future of mobility was 0.29 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.19 on the same scale. The adoption rate was scored at 2. The investment in 2019 was 151 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 151 billion dollars. By 2023, the interest score for Future of mobility was 0.49. The innovation score was 0.33. The investment was 83 billion dollars. Job postings within this trend changed by -5 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$83
billion
equity investment,2023
–5%
job postings
difference,2022–23
Industries affected
Automotive and assembly
Aviation, travel, and logistics
Electric power, natural gas, and utilities
Financial services
Metals and mining
Oil and gas
Public and social sectors
Retail
Automotive and assembly, Aviation, travel, and logistics, Electric power, natural gas, and utilities, Financial services, Metals and mining, Oil and gas, Public and social sectors, Retail,
Cutting-edge engineering
Future of bioengineering
Bioengineering is the application of engineering principles to biology, utilizing technological advancements to improve health and human performance, transform food value chains, and create innovative offerings.
In 2019, the interest score for Future of bioengineering was 0.13 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.39 on the same scale. The adoption rate was scored at 2. The investment in 2019 was 97 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 97 billion dollars. By 2023, the interest score for Future of bioengineering was 0.14. The innovation score was 0.52. The investment was 62 billion dollars. Job postings within this trend changed by -23 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$62
billion
equity investment,2023
–23%
job postings
difference,2022–23
Industries affected
Agriculture
Chemicals
Consumer packaged goods
Healthcare systems and services
Pharmaceuticals and medical products
Agriculture, Chemicals, Consumer packaged goods, Healthcare systems and services, Pharmaceuticals and medical products,
Cutting-edge engineering
Future of space technologies
Space technologies cover satellites, launchers, and habitation technologies that enable innovative space operations and services.
In 2019, the interest score for Future of space technologies was 0.12 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.07 on the same scale. The adoption rate was scored at 1. The investment in 2019 was 5 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 5 billion dollars. By 2023, the interest score for Future of space technologies was 0.17. The innovation score was 0.09. The investment was 9 billion dollars. Job postings within this trend changed by -9 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$9
billion
equity investment,2023
–9%
job postings
difference,2022–23
Industries affected
Aerospace and defense
Agriculture
Aviation, travel, and logistics
Telecommunications
Aerospace and defense, Agriculture, Aviation, travel, and logistics, Telecommunications,
A sustainable world
Electrification and renewables
The electrification and renewables trend encompasses the entire energy production, storage, and distribution value chain. Technologies include renewable sources, such as solar and wind power; clean firm-energy sources, such as nuclear and hydrogen, sustainable fuels, and bioenergy; and energy storage and distribution solutions such as long-duration battery systems and smart grids.
In 2019, the interest score for Electrification and renewables was 0.52 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.29 on the same scale. The adoption rate was scored at 3. The investment in 2019 was 160 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 160 billion dollars. By 2023, the interest score for Electrification and renewables was 0.73. The innovation score was 0.36. The investment was 183 billion dollars. Job postings within this trend changed by 1 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$183
billion
equity investment,2023
+1%
job postings
difference,2022–23
Industries affected
Agriculture
Automotive and assembly
Aviation, travel, and logistics
Chemicals
Construction and building materials
Electric power, natural gas, and utilities
Metals and mining
Oil and gas
Real estate
Agriculture, Automotive and assembly, Aviation, travel, and logistics, Chemicals, Construction and building materials, Electric power, natural gas, and utilities, Metals and mining, Oil and gas, Real estate,
A sustainable world
Climate technologies beyond electrification and renewables
Climate technologies (beyond electrification and renewables) center on solutions that mitigate the negative effects of resource consumption on the climate, either by removing CO2 from the atmosphere or by producing existing materials and inputs with lower carbon equivalents.
In 2019, the interest score for Climate technologies beyond electrification and renewables was 0.2 on a scale from 0 to 1, where 0 is low and 1 is high. The innovation score was 0.15 on the same scale. The adoption rate was scored at 2. The investment in 2019 was 51 on a scale from 1 to 5, with 1 defined as “frontier innovation” and 5 defined as “fully scaled.” The investment was 51 billion dollars. By 2023, the interest score for Climate technologies beyond electrification and renewables was 0.25. The innovation score was 0.2. The investment was 68 billion dollars. Job postings within this trend changed by -11 percent from 2022 to 2023
1
2
3
4
5
adoption score, 2023
(1 = frontier innovation;
5 = fully scaled)
$68
billion
equity investment,2023
–11%
job postings
difference,2022–23
Industries affected
Agriculture
Automotive and assembly
Aviation, travel, and logistics
Chemicals
Construction and building materials
Electric power, natural gas, and utilities
Metals and mining
Oil and gas
Real estate
Agriculture, Automotive and assembly, Aviation, travel, and logistics, Chemicals, Construction and building materials, Electric power, natural gas, and utilities, Metals and mining, Oil and gas, Real estate,
The AI revolution group
The AI revolution group
The AI revolution group
Building the digital future group
Building the digital future group
Compute and connectivity frontiers group
Compute and connectivity frontiers group
Compute and connectivity frontiers group
Compute and connectivity frontiers group
Cutting-edge engineering group
Cutting-edge engineering group
Cutting-edge engineering group
Cutting-edge engineering group
A sustainable world group
A sustainable world group
00.20.40.60.81.0Interest, score (0 = lower; 1 = higher)00.20.40.60.81.0 Innovation, score (0 = lower; 1 = higher)201920192019201920192019201920192019201920192019201920192019202320232023202320232023202320232023202320232023202320232023Generative AIApplied AIIndustrializing machine learningNext-generation software developmentDigital trust and cybersecurityAdvanced connectivityImmersive-reality technologiesCloud and edge computingQuantum technologiesFuture of roboticsFuture ofmobilityFuture of bioengineeringFuture of space technologiesElectrificationand renewablesClimate technologies beyondelectrification and renewables
Trends
Generative AI
1
Applied AI
2
Industrializing machine learning
3
Next-generation software development
4
Digital trust and cybersecurity
5
Advanced connectivity
6
Immersive-reality technologies
7
Cloud and edge computing
8
Quantum technologies
9
Future of robotics
10
Future of mobility
11
Future of bioengineering
12
Future of space technologies
13
Electrification and renewables
14
Climate tech beyond
electrification and renewables
15
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About the author(s)
Lareina Yee is a senior partner in McKinsey’s Bay Area office, where Michael Chui is a McKinsey Global Institute partner, Roger Roberts is a partner, and Mena Issler is an associate partner.
The authors wish to thank the following McKinsey colleagues for their contributions to this research: Aakanksha Srinivasan, Ahsan Saeed, Alex Arutyunyants, Alex Singla, Alex Zhang, Alizee Acket-Goemaere, An Yan, Anass Bensrhir, Andrea Del Miglio, Andreas Breiter, Ani Kelkar, Anna Massey, Anna Orthofer, Arjit Mehta, Arjita Bhan, Asaf Somekh, Begum Ortaoglu, Benjamin Braverman, Bharat Bahl, Bharath Aiyer, Bhargs Srivathsan, Brian Constantine, Brooke Stokes, Bryan Richardson, Carlo Giovine, Celine Crenshaw, Daniel Herde, Daniel Wallance, David Harvey, Delphine Zurkiya, Diego Hernandez Diaz, Douglas Merrill, Elisa Becker-Foss, Emma Parry, Eric Hazan, Erika Stanzl, Everett Santana, Giacomo Gatto, Grace W Chen, Hamza Khan, Harshit Jain, Helen Wu, Henning Soller, Ian de Bode, Jackson Pentz, Jeffrey Caso, Jesse Klempner, Jim Boehm, Joshua Katz, Julia Perry, Julian Sevillano, Justin Greis, Kersten Heineke, Kitti Lakner, Kristen Jennings, Liz Grennan, Luke Thomas, Maria Pogosyan, Mark Patel, Martin Harrysson, Martin Wrulich, Martina Gschwendtner, Massimo Mazza, Matej Macak, Matt Higginson, Matt Linderman, Matteo Cutrera, Mellen Masea, Michiel Nivard, Mike Westover, Musa Bilal, Nicolas Bellemans, Noah Furlonge-Walker, Obi Ezekoye, Paolo Spranzi, Pepe Cafferata, Robin Riedel, Ryan Brukardt, Samuel Musmanno, Santiago Comella-Dorda, Sebastian Mayer, Shakeel Kalidas, Sharmila Bhide, Stephen Xu, Tanmay Bhatnagar, Thomas Hundertmark, Tinan Goli, Tom Brennan, Tom Levin-Reid, Tony Hansen, Vinayak HV, Yaron Haviv, Yvonne Ferrier, and Zina Cole.
They also wish to thank the external members of the McKinsey Technology Council for their insights and perspectives, including Ajay Agrawal, Azeem Azhar, Ben Lorica, Benedict Evans, John Martinis, and Jordan Jacobs.
Special thanks to McKinsey Global Publishing colleagues Barr Seitz, Diane Rice, Kanika Punwani, Katie Shearer, LaShon Malone, Mary Gayen, Nayomi Chibana, Richard Johnson, Stephen Landau, and Victor Cuevas for making this interactive come alive.
