Showing posts sorted by date for query consumer spending. Sort by relevance Show all posts
Showing posts sorted by date for query consumer spending. Sort by relevance Show all posts

Thursday, April 3, 2025

AI Assistant Revenue Upside Mostly Will be Measured Indirectly

Amazon expects Rufus, its AI shopping assistant, to indirectly contribute over $700 million in operating profits this year, Business Intelligence says. 


The expected upside would come in the form of "downstream impact," a metric Amazon uses to measure a product or service's potential to generate additional consumer spending across Amazon's vast offerings. Rufus, as such, generates no direct revenue, of course. 


Rufus product recommendations might lead to more purchases on Amazon's marketplace, for example. The value of advertising embedded in Rufus content are another way indirect revenue upside is measured. 


By 2027, however, it is expected to reach $1.2 billion in DSI profit contributions, according to Amazon. 


“From broad research at the start of a shopping journey such as ‘what to consider when buying running shoes?’ to comparisons such as ‘what are the differences between trail and road running shoes?’ to more specific questions such as ‘are these durable?’, Rufus meaningfully improves how easy it is for customers to find and discover the best products to meet their needs, Amazon says. 


That is likely a way most firms are going to have to rely upon to quantify their LLM assistant revenue gains. 


Use Case

Description

Revenue Impact

Customer Support Automation

AI chatbots handle FAQs and troubleshooting, reducing customer service costs.

Lowers operational costs and improves customer retention.

Lead Generation,  Qualification

AI assistants engage website visitors, collect data, and qualify leads.

Increases conversion rates and enhances sales pipeline efficiency.

E-commerce Upselling,  Cross-Selling

AI recommends relevant products based on user behavior and preferences.

Boosts average order value and sales.

Content & SEO Optimization

AI generates blog posts, product descriptions, and metadata for SEO.

Increases organic traffic, improving brand visibility and sales.

Personalized Marketing, Retargeting

AI-driven chatbots deliver personalized offers and recommendations.

Enhances engagement, conversion rates, and repeat purchases.

Employee Productivity Enhancement

AI automates repetitive tasks (e.g., email drafting, summarization, scheduling).

Saves time, allowing employees to focus on high-value tasks.

Market Research,  Insights

AI collects and analyzes customer feedback for business insights.

Improves decision-making and product-market fit.

Training, Onboarding

AI-based interactive training modules for new employees.

Reduces onboarding time and training costs.

Subscription, Membership Services

AI chatbots engage users to promote premium subscriptions.

Increases subscription revenue and customer lifetime value.

Reducing Churn,  Customer Retention

AI proactively engages users before they disengage or cancel services.

Lowers customer acquisition costs by improving retention rates.


Thursday, March 20, 2025

"AI Edge Computing" is Multiple Markets, Not One

AI edge computing refers to the deployment of artificial intelligence algorithms at the "edge" of a network, closer to where data is generated, rather than relying solely on centralized cloud infrastructure. 


But there is a huge difference between “on-device” and “at a remote site” implementations, value chains and markets. 


For example,, on-device edge AI is about smartphones, IoT sensors, wearables or autonomous vehicles. 


Remote edge AI is about data centers, cloud computing, servers and other “enterprise” or “business” computing functions. 


Lumping everything together in one big “AI edge computing” category obscures as much as it illuminates. 


Category

Metric

On-Device Edge AI

Remote Edge AI

Source/Assumption

Market Size (2025)

Financial (USD Billion)

$15 billion

$10 billion

Based on edge AI market growth (e.g., Grand View Research, 21.7% CAGR from $20.78B in 2024)

Market Size (2030)

Financial (USD Billion)

$50 billion

$35 billion

Extrapolated from "device" and "data center" forecasts

Usage (2025)

Devices/Deployments

20 billion devices (smartphones, wearables)

500,000 edge nodes (e.g., servers, gateways)

Statista IoT, IDC edge spending forecasts

Compute Cycles (2025)

Avg. Cycles per Task

10^6 cycles (lightweight models, e.g., NLP)

10^9 cycles (complex models, e.g., video analytics)

Hardware capability estimates

Financial Implication

Revenue Driver

Hardware sales (AI chips, $500 billion smartphone market)

Infrastructure and services , perhaps $450 billion per year

On-device chips, smartphones for "on-device" mkt., connectivity and servers for "remote"

Growth Rate (2025-2030)

CAGR

27%

23%

Higher consumer device adoption vs. enterprise


As you can see, “edge AI” markets are largely contained within other existing device and data center markets. Looking at chip content alone, in either edge device or data center markets is helpful, but doesn’t show the full value chain for either type of product.


Monday, February 24, 2025

AI Job Impact will be Asymmetric

We will be debating AI job impact for quite some time, though the likely outcome is not so difficult to predict. Assuming AI represents a general-purpose technology, it absolutely will significantly rearrange the way work gets done in the economy.


But it likely also will be true that the job losses will be easy to quantify but relatively small in magnitude, while  the job gains will be large in magnitude but more diffuse across the whole economy. A GPT tends to do that. 


A general-purpose technology (GPT) is a technology that has broad applications across multiple industries, significantly enhances productivity, and serves as a foundation for further innovations. Think electricity, computing, steam power, the internet. 


GPTs both create whole new categories of jobs even as they reduce the need for legacy work. So, yes, jobs will be reshaped and eliminated. But many new categories also will be created. And the magnitudes of job destruction and creation are likely to be asymmetrical. 


The lost jobs might be easier to enumerate than the jobs created or sustained. To the extent AI affects jobs because of task automation, it will tend to be “quantitative” in impact: tasks might require fewer people than in the past.


But jobs created will happen for “qualitative” reasons: new things will be possible that were either technologically or economically “impossible” before. Ride hailing services were unthinkable before ubiquitous smartphone adoption, for example. So were all manner of location-based services, apps and use cases. 


General-Purpose Technology (GPT)

Jobs That Shrunk

Jobs That Were Created

Steam Engine (Industrial Revolution)

Artisans, Hand-weavers, Blacksmiths

Factory Workers, Mechanical Engineers, Railway Operators

Electricity

Gas Lamp Lighters, Telegraph Operators

Electrical Engineers, Electricians, Radio Technicians

Automobile

Horse Carriage Drivers, Blacksmiths (for horseshoes)

Auto Mechanics, Assembly Line Workers, Road Construction Workers

Telecommunication (Telephone, Radio, TV)

Telegraph Operators, Messengers

Call Center Agents, Broadcast Technicians, Media Producers

Computers & Automation (20th Century)

Typists, File Clerks, Switchboard Operators

Software Developers, IT Support Specialists, Data Analysts

Internet & Digital Revolution

Print Journalists, Travel Agents, Retail Cashiers

Web Developers, Digital Marketers, E-commerce Specialists

Artificial Intelligence & Robotics

Data Entry Clerks, Factory Line Workers, Customer Service Representatives (basic inquiries)

AI Specialists, Machine Learning Engineers, Automation Consultants

Biotechnology & Genetic Engineering

Manual Lab Technicians in Some Fields

Bioinformatics Scientists, Genetic Counselors, Biotech Engineers


The larger point might be the GPT impact on industry fortunes, as legacy industries often are replaced by newer industries that displace them. 


General-Purpose Technology (GPT)

Industries That Shrunk

Industries That Were Created or Expanded

Steam Engine (Industrial Revolution)

Cottage Textile Production, Manual Agriculture

Large-Scale Manufacturing, Railroads, Mining

Electricity

Gas Lighting, Water-Powered Mills

Power Generation, Electrical Appliance Manufacturing, Telecommunications

Automobile

Horse Carriage Manufacturing, Blacksmithing, Rail Passenger Transport (relative decline)

Auto Manufacturing, Oil & Gas, Road Infrastructure, Logistics

Telecommunication (Telephone, Radio, TV)

Telegraph Services, Door-to-Door Messaging

Broadcasting, Call Centers, Advertising & Mass Media

Computers & Automation (20th Century)

Typewriting & Clerical Work, Physical File Storage & Archiving

IT Services, Software Development, Cybersecurity

Internet & Digital Revolution

Print Publishing, Traditional Retail Stores, Physical Banking Services

E-commerce, Social Media, Online Banking, Cloud Computing

Artificial Intelligence & Robotics

Low-Skill Manufacturing, Data Entry Services, Basic Customer Support

AI Research & Development, Autonomous Vehicles, Personalized Healthcare

Biotechnology & Genetic Engineering

Traditional Farming (relative decline), Some Chemical-Based Drug Development

Biopharmaceuticals, Genetic Medicine, Precision Agriculture


At a wider level, studies of automation impact (among the likely ways AI will reshape jobs) suggest both job displacement and creation; job redefinition and emphasis on new skills. 


Automation, by definition, is the use of technology, machinery, and software to perform tasks with minimal human intervention. So we replace human labor with machine labor. By clear implication, that means fewer jobs in the areas we automate, even as new jobs are created in other areas. 


And GPTs have had a disproportionate impact on both job creation and destruction. Some GPTs create vastly more jobs than they displace, for example. 


GPTs that enable new industries (such as electricity, computers, and the internet) tend to create the most jobs. On the other hand, many GPTs arguably displace relatively few jobs in relation to jobs they create. 


Electricity displaced water-driven mills and gas lighting, but how many people actually worked in gas lighting or small water-powered mills, compared to the number of people whose work was enabled by electricity? 


GPT job losses might be highly concentrated in a few areas, whereas the job gains might be widely distributed across an entire economy. 


Title

Year Published

Publisher

Key Conclusions

"Automation's Impact on Agriculture: Opportunities, Challenges, and Economic Effects"

2024

MDPI Robotics Journal

Explores the potential of automation and robotics in farming practices, discussing socio-economic effects and providing strategic recommendations. Highlights that while automation can enhance productivity and reduce labor costs, it may also lead to job displacement and requires careful implementation to balance benefits and social impacts. mdpi.com

"Automation and Social Impacts: Winners and Losers"

2023

Food and Agriculture Organization (FAO)

Examines how labor-saving agricultural technologies affect employment and wages. Concludes that the impact of automation depends largely on market signals and the drivers behind farm automation, with potential benefits including increased efficiency and challenges such as labor displacement. openknowledge.fao.org

"Trends Driving Automation on the Farm"

2023

McKinsey & Company

Discusses how automation can reduce the environmental impact of farming and help growers adapt to financial challenges posed by climate change. Emphasizes the spectrum of autonomous farming solutions, from semi-automated technologies to fully automated systems, and their potential to enhance productivity. mckinsey.com

"The Impact of Automated Farming on the Agriculture Industry"

2023

Plug and Play Tech Center

Highlights that automation increases productivity and production rates, leading to reduced consumer costs. Notes improvements in labor efficiency and the potential for automation to address labor shortages in agriculture. plugandplaytechcenter.com

"Automation, Climate Change, and the Future of Farm Work"

2023

National Center for Biotechnology Information (NCBI)

Explores the dual challenges of rapid automation and climate change on agricultural workers' safety and well-being. Suggests that while automation can mitigate some climate-related challenges, it also raises concerns about job security and the need for new skills among farm workers. pmc.ncbi.nlm.nih.gov

"A New Study Measures the Actual Impact of Robots on Jobs. It's Significant"

2017

MIT Sloan School of Management

Found that for every robot added per 1,000 workers in the U.S., wages decline by 0.42% and the employment-to-population ratio decreases by 0.2 percentage points, equating to approximately 400,000 job losses. The impact is more pronounced in areas where robots are deployed, with one additional robot reducing employment by six workers in that area. mitsloan.mit.edu

"The Impact of Automation on Manufacturing"

2017

Scott Technology

Discusses varying predictions regarding job losses due to automation, citing estimates ranging from 400 million to 800 million jobs worldwide by 2030. Highlights that while automation can lead to job displacement, it also enhances competitiveness and reduces production costs. scottautomation.com

"Understanding the Impact of Automation on Workers, Jobs, and Wages"

2020

Brookings Institution

Argues that automation often creates as many jobs as it displaces over time. Workers collaborating with machines become more productive, leading to reduced costs and prices, increased consumer spending, and the creation of new jobs. brookings.edu

"Technology and Jobs: A Systematic Literature Review"

2022

arXiv.org

Finds that while technological change can displace workers, compensating mechanisms often offset job losses. However, low-skill, production, and manufacturing workers have been adversely affected, emphasizing the need for effective upskilling and reskilling strategies. arxiv.org

"Applications and Societal Implications of Artificial Intelligence in Manufacturing: A Systematic Review"

2023

arXiv.org

Explores AI applications in manufacturing, such as predictive maintenance and process control. Discusses uncertain societal implications, including workforce impact, job upskilling and deskilling, cybersecurity vulnerabilities, and environmental consequences. Emphasizes that beneficial AI integration depends on choices by stakeholders, including firms, technology developers, and governments. arxiv.org

"Automation in Retail: An Executive Overview for Getting Ready"

2019

McKinsey & Company

Discusses how automation is reshaping retail business models and the broader value chain, leading to organizations with fewer layers and a better-trained workforce empowered by real-time data and analytics. Emphasizes the need for retailers to understand these implications and act swiftly to adapt. mckinsey.com

"Retail Employment and Automation: Good or Bad for Jobs?"

2020

Digit Research

Explores the dual impact of labor-enhancing and labor-replacing technologies on retail employment. Highlights that while some lower-skilled jobs may be replaced, there is a simultaneous need to upskill staff to adapt to rapid technological changes. digit-research.org

"Understanding the Impact of Automation on Workers, Jobs, and Wages"

2020

Brookings Institution

Examines the potential for automation to eliminate millions of jobs in sectors like retail. Discusses the balance between job displacement and the creation of new opportunities, emphasizing the importance of education and skill development to mitigate negative impacts. brookings.edu

"Which Workers Are the Most Affected by Automation and What Could Help Them Get New Jobs"

2021

U.S. Government Accountability Office

Identifies that workers performing routine tasks, such as cashiers, are at higher risk of job loss due to automation. Estimates that 9% to 47% of jobs could be automated in the future, underscoring the need for retraining programs to assist displaced workers. gao.gov

"The Future of Retail: How Automation is Revolutionizing the Industry"

2023

Scripted

Highlights that up to 65% of retail jobs could be automated by 2025 due to rising costs and wages, tight labor markets, and reduced consumer demand. Discusses the potential for job displacement and emphasizes the importance of strategic planning to address these challenges. script


The point is that all the discussions we will keep having about job losses from AI will tend to outweigh the discussions of new jobs created, in large part because the losses will be highly concentrated and quantifiable, where the job gains will be highly distributed and often harder to quantify. 


When one tries to understand jobs “created by electricity,” we often quantify only “jobs in the electricity production industry.” But that does not include all other jobs in the economy that are impossible without the use of electricity. And that arguably is nearly all jobs. 


Another way of putting matters is that job losses will tend to be particular, while job gains will tend to be general. 


AI Assistant Revenue Upside Mostly Will be Measured Indirectly

Amazon expects Rufus , its AI shopping assistant, to indirectly contribute over $700 million in operating profits this year, Business Intel...