How the Machine Economy is Accelerating ??????

What is the Machine Economy? ??????

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How significant is the software revolution of the current decade? And where does it lead?

Hey Everyone,

We are a society always moving forwards. Our software and technology is changing how we do business each decade.

With labor supply challenges and supply-chain issues, the current period has seen an uptake in automation and digital transformation.

The M2M, or machine-to-machine, economy is one where the smart, autonomous, networked and economically independent machines or devices act as the participants, carrying on the necessary activities of production, distribution, and allocation with little to no human intervention.

For data science and data engineering this also changes how organizations need to upgrade in order to keep up.

70% of GDP growth in the global economy between now and 2030 will be driven by the machines, according to PwC.

In the current period, ?$7 trillion dollar contribution to U.S. GDP based around the combined production from artificial intelligence, machine learning, robotics, and embedded devices. This is the rise of a new machine economy.

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As a futurist I’m often asking myself?how and what life will be like?ten or twenty years from now. It’s 2022, but there’s an acceleration coming.

• Will there be?more robots?
• Will?software be smarter?
• How will new startups impact my healthcare and financial well-being?with artificial intelligence?
• How will low-code, RPA and better tools improve how companies use the Cloud?

I came across this concept of the “Machine Economy” that I found very appealing. It summarizes a lot of my own ideas.

TimeXTender?says that:

• AI,?machine learning,?and?smart automation?will drive?70% of GDP growth?over?the next decade.
• By 2030, AI will contribute an estimated?$15.7 trillion?to the global economy, more than the current output of China and India combined.?
• 62% of business leaders?are?putting plans in place to succeed in a world filled with smart automation and connected machines – 16% are already investing and performing strongly.

According to?Micah Horner, in this new "Machine Economy", organizations will increasingly use these smart technologies to automate tasks, streamline operations, make better decisions, deliver superior customer experiences, and quickly gain market share over traditional players.

According to?Tech Monitor, AI in call centers could save businesses $80bn with A.I. effectively replacing one in three humans in the next decade.

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How is A.I. Evolving?

We know that the multi-modal LLM Convergence will lead to new kinds of A.I, even as low-code and RPA platforms increase their capabilities.

RPA stands for?robotic process automation. I’ve been watching the trend closely: Robotic process automation is a form of business process automation technology based on metaphorical software robots or on artificial intelligence /digital workers. It is sometimes referred to as software robotics.

The Machine Economy to me is a convergence of many trends in technology that accelerates automation to the point where smart cities can to some extent run by themselves. The adoption of drones to the delivery of consumer goods is an example of a pillar of the Machine Economy.

How I see the Emergence of the Machine Economy

The Machine Economy is less about AI-generated art as it is about the evolution of the Cloud, software and A.I. and the services it can provide to other companies and that foster new kinds of startups that ultimately benefit consumer convenience.

The Machine economy is what evolves as data becomes the new oil. This takes a few decades to manifest.

A Machine economy manifests when a society decides to put artificial intelligence and software transformation at the core of their agenda. This allows a?software transformation boom?to occur that leads to more efficiency, productivity and innovation as well as more automation of repetitive tasks for humans.

According to Gartner, Microsoft, Salesforce and a bunch of startups and other companies might be in the lead pioneering robotic process automation. I’d suspect that in low-code platforms, it’s much the same. You can read my post about?Microsoft’s Power Apps?and what this actually means.

Here is what I expect:

• Robotics becomes more practical
• Logistics and supply chains become more efficient and more automated
• Geopolitical uncertainty causes better and more decentralized chip manufacturing ($52 Billion Chips?bill)
• Low-code and RPA platforms improve drastically although slow to reach a tipping point
• LLMs become more impressive as supercomputing continues to scale
• The A.I. R&D advantage of BigTech continues and remains significant
• Software becomes smarter and digital transformation spreads ubiquitously
• Automation and the augmentation of tasks by A.I. becomes the new normal
• The Machine Economy creates new jobs and new kinds of jobs
• Some workers are disrupted as their repetitive tasks and even some of their white collar tasks changes supply-demand factors in the labor force

Automation becomes more primary as:

1. Labor supply chain supply-demand?breakage continues (e.g. more automation in the hotel, travel and hospitality industries)
2. Demographic changes occur?with aging populations (e.g. China)
3. Capitalism continues?being and becoming even more top-heavy due to impact of BigTech with digital transformation monopolies and duopolies. (Cloud, Ads, software, search, EVs, E-commerce, etc.…)
4. As monopoly Capitalism leaders?encroach more on?financial services industries (e.g. Banks) and healthcare.
5. As Cloud leaders namely AWS and Azure separate themselves even further from the rest. Google Cloud, Alibaba and others are not catching up.
6. Industry leaders in R&D around A.I. such as Google and Microsoft will also acquire leading quantum computing companies especially those involved in software and?Quantum machine learning?space.

If software has been eating the world in the 2010 to 2022 period, we haven’t seen anything yet, the 2022 to 2034 period will be far more transformative and impactful for how cities, companies and consumers will upgrade (and augment themselves) in the 21st century.

Robotic Process Automation - RPA Leaders 2021

Which is the leading RPA tool?

What are the leading RPA tools in the market?

If we do not count the obvious utility of Microsoft and Salesforce to dominate this domain, some of the contemporary leaders listed on the web typically are:

1. UiPath
2. Automation Anywhere
3. Blue Prism
4. NICE
5. Softomotive
6. Kryon
7. Intellibot
8. Servicetrace
9. Nividous
10. HelpSystems
11. 11. Automation Edge
12. Datamatics
13. Jacada
14. Appian
15. Perpetuuiti

Slow Moving Trends in the Machine Economy

There are many other areas of the Machine Economy that we sometimes neglect our focus on:

• IoT: internet of things
• Ambient computing
• Self-learning Robots (e.g.?UC Berkley)

• Industrial A.I.?(See?Baidu?here)
• Facial recognition embedded into smart cities (including biometric payments)
• The emergence of the Robo-Taxi industry
• Self-driving trucks in logistics
• Drone delivery in E-commerce fulfillment
• E-commerce warehouse automation
• Robotics integrated into the services especially the food and restaurant industry.
• Software evolution in the future EV and hydrogen smart car.
• And so many others.

A Small Note for Investors

For investors, RPA and quantum computing stocks may be worth watching. I am a bit surprised?Automation Anywhere?has not gone public yet. SoftBank is one of Automation Anywhere’s major investors, with Vision Fund investing $300 million in 2018. The company was valued at $6.8 billion in 2019, according to data provider PitchBook.?

Automation Anywhere has raised about $849.3 million in funding from investors such as General Atlantic, New Enterprise Associates, Salesforce Ventures and Goldman Sachs Group Inc., PitchBook data show.?UiPath was very impacted by the Ukraine invasion. The stock is down 63% YTD, for more stock analysis see my?Newsletter. Automation Anywhere is an enterprise-grade, cognitive Robotic Process Automation (RPA) platform.

A bit like?how Cathie Wood?is bullish on the genomics sector, I’m more bullish on companies that directly impact the Machine Economy. RPA and low-code platforms are just an obvious example.

As an independent journalists interested in the future, meta-trends and following nascent industries is what I am all about: I’m convinced that a “futurist” needs to be versed in the following:

• Quantum computing
• A.I. in the news
• The Stock market
• Startups, venture capital and innovation cycles
• Economics and geopolitical trends

What do you think about the Machine Economy and the prospect of more automation in society in the next 30 years?

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