Showing posts sorted by date for query technology adoption. Sort by relevance Show all posts
Showing posts sorted by date for query technology adoption. Sort by relevance Show all posts

Saturday, April 5, 2025

Embodied AI (Robots) Likely Key to Some Onshoring of U.S. Manufacturing

It is hard to avoid the conclusion that artificial intelligence, in the the form of embodied robots, will be an important part of the business case if manufacturing facilities return to the United States as part of restoring policies and firm responses, jobs will indeed be created, but not at the scale of the pre-offshoring era, it is reasonable to predict. 

Automation, particularly robots using artificial intelligence, likely will handle much of the repetitive, labor-intensive work. 


Study/Source

Estimated Job Creation

Role of Automation

Key Insights

Forbes (2025)

Hyundai's $20 billion investment expected to create 1,500 jobs in Louisiana

Automation is a major factor in reducing traditional manufacturing jobs.

Manufacturing production is high, but job creation is modest due to automation replacing manual labor.

Davron (2024)

Reshoring creates advanced manufacturing jobs requiring higher skills and wages

Advanced manufacturing relies heavily on technology, reducing reliance on manual labor.

Reshoring fosters innovation but requires a skilled workforce trained for automated processes.

Business Insider (2024)

Reshoring could add $10 trillion to the economy over the next decade

High-tech sectors benefit most, integrating automation for efficiency.

Automation is central to reshoring efforts, enhancing productivity but limiting traditional job growth.

Christian Science Monitor (2025)

AI-driven factories may add slightly more jobs than they destroy

Factories integrate AI and robotics to increase efficiency and resilience.

Human roles shift toward managing robots and AI rather than performing manual tasks.

Shoplogix (2023)

Robotics create new roles like technicians and engineers but displace manual labor jobs

Robots perform repetitive tasks faster and more accurately than humans.

Upskilling is essential as traditional roles are replaced by tech-focused positions.

LinkedIn (2025)

Manufacturing output increased 15% since 2020, employment rose only 3%

Automation reduces factory jobs while creating opportunities in high-tech roles.

Reshoring with automation boosts productivity but limits job creation in traditional sectors.



Where an existing garment factory presently operating in Southeast Asia employs X workers, a repatriated operation in the United States might require perhaps 10 percent to 20 percent of those workers. Recall that the reason such facilities moved from U.S. domestic locations to off shore is precisely lower labor rates. 


Assuming higher U.S. wage rates, the only way the economics would work is if far fewer workers were required. 


Study/Analysis

Source

Key Findings on Job Increases

Automation Consideration

Date

Reshoring Initiative Report

Reshoring Initiative

Estimated 1.6 million jobs reshored from 2010-2022, with potential for more if trends continue.

Notes automation reduces job counts; 2022 data shows 364,000 jobs added, but robotics limits scale vs. past.

2022

Oxford Economics:  How Robots Change the World

Oxford Economics

Robots could displace 20 million global manufacturing jobs by 2030, but reshoring may add some back.

Predicts automation will cap U.S. job gains; historical 1.6 jobs lost per robot suggests fewer net gains.

2019

MIT: Robots and Jobs

Acemoglu and Restrepo (NBER)

Between 1990-2007, 1 robot per 1,000 workers reduced employment by 6 workers locally.

Automation in reshored facilities could mean 50-70% fewer jobs than offshored totals due to robot density.

2017

Ball State University:  Manufacturing Study

Center for Business and Economic Research

U.S. lost 5.8 million manufacturing jobs (1980-2016), mostly to productivity automation, not trade.

Suggests reshoring creates high-skill jobs (e.g., technicians), but far fewer than original low-skill positions.

2017

McKinsey Global Institute: Future of Work

McKinsey

Automation could displace 16-20 million U.S. jobs by 2030, but reshoring may offset some losses.

Highlights that returning facilities will lean on robots/AI, creating 10-20% of original job numbers.

2017

ITIF: Robotics and Production

Information Technology and Innovation Foundation

Robotics boosts productivity, potentially adding manufacturing jobs in developed nations.

Job growth tied to engineers/tech roles; traditional labor replaced by robots, reducing total job count.

2019

Brookings: Automation and Jobs

Brookings Institution

Automation offsets job losses from trade, but reshoring impact limited by tech adoption.

Estimates 100-150 jobs per large reshored factory, vs. 500-1,000 historically, due to automated processes.

2015, 2022


Thursday, March 27, 2025

AI Scribes Produce Operational Impact, but Not Identifiable Financial Outcomes, Yet

Ambient scribes convert verbal patient-provider interactions into structured notes for clinical documentation and, eventually, medical billing. Useful, of course. The innovation saves time.  But at least one study suggests the financial impact is unclear. 


That is likely to be a recurring issue for many types of artificial intelligence features and apps. 


Peterson Health Technology 


The issue is that faster task completion, reduced human error, and streamlined workflows do not always  translate that into immediate financial gains. In fact, financial impact might be neutral to negative at first precisely because time and money has to be spent to implement the solutions. 


This perhaps is not unusual for new technology solutions. Enterprise resource planning (ERP) systems also promised efficiencies, such as the ability to generate reports faster. Still, the financial payoff wasn’t instant. As always, firms had to redesign their business processes to scale up. 


Likewise, cloud computing cut information technology overhead and boosted agility, but early adoption did not always lead to an immediate financial outcome.


Perhaps AI operational wins are the low-hanging fruit. Customer service chatbots reduce call center workload, but revenue metrics do not automatically improve. 


A 2023 Gartner report suggested 60 percent of AI projects improve process metrics, but only 30 percent show clear financial uplift within a year, for example. 


Study/Source

Operational Improvement

Potential Revenue/Profit Impact

Gartner Research

IT leaders in mature AI organizations identify business metrics early and use clear attribution strategies3

Not immediately quantifiable

Cleveland Clinic

AI used to predict patient influx and optimize staffing3

Indirect impact on efficiency, not direct revenue

Axis Bank

AI assistant handles up to 15% of calls3

Operational efficiency gain, but no direct profit mentioned

McKinsey Survey

About half of C-suite leaders describe AI initiatives as still developing or expanding9

Returns not meeting initial expectations

MIT Economics Paper

Predicted TFP gains from AI over next 10 years less than 0.55%2

Modest macroeconomic effects, not immediate profit

Virtasant Report

AI enables 24/7 customer service and reduces errors in complex processes3

Long-term strategic benefits, not immediate profit

Wednesday, March 26, 2025

Asking the Wrong Question about 5G

The claim  that "5G has failed” is in some ways an odd one. On one hand, critics tend to cite the unfulfilled promises of exciting new use cases. On the other hand, critics tend not to focus on the lower latency, faster speeds or energy efficiency that each successive network also is founded upon. 


But that might be the main point: each successive mobile generation has been successful and necessary precisely for the reasons that consumer home broadband experiences have been based on ever-increasing bandwidth, capacity and access speeds. 


So alter the question just a bit to understand the real impact. Do you ever really hear observers arguing that mobility services (mobile phone service) actually have failed? One does not hear such claims because mobile service clearly has been a raging global success. 


Some 71 percent of humans presently use a mobile phone, according to the GSMA.  


source: World Economic Forum 


So “mobility” has clearly succeeded, even if some feel particular mobile platforms have not. To be sure, proponents have touted the creation of platforms for futuristic use cases (the network will support them), not the extent of usage. Some examples can always be cited, though often not mass market adoption. 


To be sure,  every mobile generation since 3G has made such claims. And we might advance some very-practical reasons for the claims. Each mobile generation requires the allocation of additional spectrum from governments, which have to be convinced to do so.


Pointing out the new potential applications; the contribution to economic growth; educational advantages and so forth are part of the effort to secure the new spectrum. 


Also, infrastructure suppliers have a vested interest in enticing operators to create whole new networks precisely because it might be possible to create new revenue streams, or provide


Still, each successive mobile platform has promised, and delivered, latency improvements of about 10 times over the preceding generation, as well as potential bandwidth (internet access speeds) of 10 times more, and typically also energy consumption efficiencies as well. 


The practical improvements always vary from laboratory tests, though. The actual behavior of all radio waves in real-world environments is an issue. So are the realities of impediments to signal propagation (walls, trees, other obstacles) and signal interference.


Cell geometry also matters. Higher bandwidth is possible when smaller cells are used. 


Higher bandwidth is possible when channel sizes are increased (as when channels are bonded together to create a single wider channel from two or more narrower channels). 


And real-world “customer-experienced speeds” also are dependent on which actual frequencies are used widely by each mobile generation. Lower frequencies propagate better, but higher frequencies support higher speeds, all other things being equal. 


Still, the point is that observers never question the “success” of the mobile phone and mobile networks, only the “failure” of futuristic apps to emerge. 


That is not the point. The primary and essential value of each successive mobile platform comes from network performance (lower latency, higher bandwidth) and not the possible new apps, which cannot be created by mobile operators in any case, anymore than internet service providers having created Facebook. Google, Amazon, YouTube or Uber. 


Mobile operators can only create the physical infrastructure third parties can use to create new use cases. And that has been accomplished. But then innovation leading to new apps rests in the hands of entrepreneurs and investors.  


That’s the whole implication of “permissionless innovation” the internet is based upon: innovators do not have to own networks to build apps that use the networks. The entities that own the access or transport networks do not necessarily or primarily create and own the apps. 


Oddly, the reverse tends to be the case: highly-successful consumer app providers find they can vertically integrate into core network transport as a means of lowering their costs. That is why most of the world’s long distance networks (subsea, especially) are built and owned by a relative handful of big app providers such as Alphabet (Google) and Meta. 


It is fair to note that few of the futuristic apps touted for 3G, 4G or 5G networks have become mass market realities. On the other hand, lots of highly-useful apps not envisioned for any of those networks have emerged.


Net

Predicted "Futuristic" Use Cases

Unexpected "Everyday" App Developments

3G

Video conferencing, mobile TV, advanced multimedia

Mobile social media (early stages), basic GPS navigation, early app stores

4G

Immersive VR/AR, high-definition mobile gaming, remote surgery

Ride-sharing apps (Uber, Lyft), widespread video streaming (YouTube, Netflix), robust social media (Instagram, TikTok), advanced turn-by-turn navigation (Google Maps)

5G

Holographic communication, tactile internet, massive IoT deployments

Enhanced real-time location based services, very high definition mobile video streaming, cloud gaming, very reliable real time social media interactions. Increased use of live streaming services, and the further enhancement of cloud based applications.


All of which suggests we are very bad at predicting the future; innovations often emerge unexpectedly and only when users see the value. 


Consider only the industrial, commercial, medical and other applications generally centered around the use of sensors and mobile networks as the connectivity mechanism. Most have not taken off in a significant way, even if there are some instances of viable and routine deployment. 


Generation

Touted Possible New Applications

3G

- Telematics for automotive industry5


- Smart home devices (thermostats, security cameras)1


- Traffic light systems1


- Vending machines with remote monitoring1


- GPS trackers for livestock1


- Wearable devices and e-readers1


- Medical alert devices1


- Remote weather stations1

4G

- Enhanced mobile broadband for video streaming and gaming6


- Smart home applications2


- Internet of Things (IoT) connectivity2


- Remote monitoring systems2


- Vehicle communications (real-time road information, navigation)2


- VoIP calls and video conferencing6


- Mobile payments6

5G

- Telesurgery and remote medical procedures4


- Fully autonomous vehicles4


- Advanced connected homes4


- Portable Virtual Reality (VR) experiences4


- Smart city infrastructure4


- Ultra-reliable low latency communication (URLLC)3


- Massive Machine Type Communication (mMTC)3


- Industrial automation and robotics8


- Remote patient monitoring in healthcare7


- Large-scale IoT deployments in agriculture, utilities, and logistics


For the most part, the futuristic appl;ications have not developed as expected, and when they do take hold, it often is in the subsequent generation.


Many expected 3G to produce mass market usage of videoconferencing. That did happen, but only in the 4G era, with social media and other multimedia messaging apps, for example. That is a fairly common pattern: we overestimate routine adoption by at least a decade. 


Use Case Prediction

Actual Adoption (at least early stage)

Delayed Applications Likely Emerging in Later Generations

3G Expectations

(Medical devices, telematics, mobile TV)1

4G Realizations (IoT connectivity, smart meters, vehicle telematics)2

4G Concepts for 5G Era

- Advanced industrial automation3

- Mobile medical monitoring systems3

- Smart grid controls3

- HD public safety cameras3

4G Expectations

(Massive IoT, Industry 4.0)2

5G Realizations (Network slicing, enhanced mobile broadband)4

5G Concepts for 6G Era

- Holographic communications5

- Autonomous vehicle networks57

- Network-as-sensor technology5

- Microsecond-latency telesurgery7

5G Expectations

(URLLC, mMTC)34

6G Projections

- 1,000x faster latency than 5G7

- AI-optimized networks5

- Energy-efficient massive IoT6

6G Horizon

- Real-time digital twins5

- Military-grade AR simulations5

- Advanced environmental sensing5

- 8K holographic streaming


The point is that mobile services and smartphone services have proven wildly successful. In fact, nobody doubts that. What often gets criticized are the many futuristic apps that could be developed with each next-generation mobile network.


That misses the point. As fixed network home broadband has to continually extend internet access speeds and bandwidth, so too do mobile networks. The bottom line is that each successive mobile generation succeeds to the extent it does so.


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