AI likely to make fewer wealthy and economical inequality worst. The reality of any technology and new technology is that only a few learn to exploit it’s full potential. While, the rest of us either copy, follow, try to keep up, or bull shit our way through.

Not necessarily wishing you less business progress or create fear however the fact is only few will benefit financially tremendously from AI (artificial intelligence) or LLM or Generative AI or AGI. It’s just as there are only so much need for gold coins, so much buyers of it, so much frequency of purchase, only so much time, only so much attention, etc that not everyone will…to simply put it, not everyone “will kill well” or “eat well” from AI.

Some of you founders, business leaders, functioning supporting personnel like lawyers might have figured this out. Surely NVIDIA, Microsoft, Amazon AWS, Google, Meta, Netflix, Alibaba, AMD, OpenAI, Governments, Cities, etc realize that not everyone will reap the financial benefits from AI software and AI hardware. The incumbents with resources will be glad to sell everyone the axes, and shovels.

The brave few founders will beat a new path or adapt a path to enrich themselves. The rest of humanity not in the wealth creating process will be left to just watch or may riot.

One simple example, Lets say 100,000 people went to the same United States University and got good grades, leverage the prestige of the best association and alumni, etc …the question is how many of them will be the very best in their chosen professions? How many will be unimaginably wealthy and respected?

Another example, Almost every tech founder has access to best front-end and back-end stacks like JavaScript, CSS, Ruby on Rails, Python, Java. Even having the best models is not going to make many the next Google, SnowFlake, Slack, Netflix

Many say that the following below areas will improve business with addition of AI but when everyone is utilizing it for similar purpose then where do investors, founders, employees, financial services, wealth managers, hedge funds, software makers… find their edge? ‘cause in a capitalism world commodities don’t command a whole lot of margins.

***(BONUS On last few pages for B2B:  Over 20+ AI Use Cases & Applications)

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Let’s Begin…

AI Customer Acquisition

They hope that AI-powered products and services can assist in attracting and retaining new customers even when budgets are tight.That’s like saying cold email marketing, cold calls, cold SMS will help improve customer acquisition. Lots of people have and abused these tools so people’s guards are up. So AI likely will eventually have the same future outcome.

AI Can Streamline Operations

They hope AI can streamline operations. Few workers doing boring, repetitive jobs so more employees can spend more time delivering higher value and building customer relationships.

That sounds nice however the reality is…for one is that if majority of employers adopt this …the less people you need to produce goods and services eventually means less people can afford your products…collectively cities, suburbs could face some serious tax revenue challenges and social services challenges like San Francisco / New York City.  

Even McDonald has come to the conclusion that their prices are becoming more and more un-affordable to their main targets. McDonald  could be a luxury like meat is a luxury in some countries.

AI Generate Compelling Content

Sure not every organization prior to Generative AI could produce and distribute a whole lot of content. They usually would likely hire and pay a whole lot of human writers or video creators to scale.

Now pretty much anyone with a computer and internet can prompt a LLM tool like Open AI ChatGPT to spit out some good enough general content.

The reality today is everyone can match the best of the best in terms of content quality. Therefore, no one is special in the content production department unless you get creative in adding uncommon insights. Some distribution channels might require pay-to-play.

AI Chatbots For Prospecting / Customer Services

The tools available today and possibly in the near future will be way better because they will be well trained in terms of knowledge and relevancy accuracy. So less human workers at this level.

By automating customer interactions, capturing data, matching data small businesses can efficiently engage with more prospects and more customers with out so much human manpower.

It’s sort of like automating your email nurturing systems. You will know when to email, what message, situation awareness, probability, etc.

But when everyone has this performance improvement then you’ve got to stay up 24/7 finding out what others can’t duplicate. A website was once an advantage now pretty much everyone has one or social media page.

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AI & The Power of Mass Personalization

The days of just personalizing the customer name and contact info is over now with AI you’d be able to go further and further to mass personalize messages to anyone. Generative AI could spit out messages for your top customers and just send the message that suits your general customers. Even incorporate purchase history, preferences, behaviors, personality, etc

Everyone in your industry will be able to do this then how do you stay competitive? Cause more competition usually means you better become happy with smaller & smaller piece of a growing pie or shrinking pie.

AI Can Analyze, Develop Ideas, and Opportunities Faster

Because of AI processing and computing power it’s just faster than a human brain. Which then means B2B can quickly qualify prospects, and reduce sales cycles. There are many startups and enterprise solutions coming however the reality is not every user will deploy / use these tools to generate a significant ROI that then makes them #1 – #5 in their space. Example use, intent analysis, conversation analysis, body language analysis, customer journey analysis, etc.

It’s like if every team in the NFL had the best coaching staff, QB, Owner, Fans, etc……what happens now?

AI Helping To Forecast Better

Sure the potential is there cause of the processing and computing power. And it will save on labour cost to gather, clean, sort, analyze, present and repeat. But think about it – – Excel, Power BI, Tableau, and others are available to anyone around the world.

Who uses it well? Who is getting no use from these tools?  Who is preparing their data? Who is using bad models?

Understand Your Market & Your Position With AI

There is nothing more critical to business than knowing were you fit in the industry and how you are perceived. AI can do calculation as however it seems might be on the quantitative not qualitative areas.

Advertising With AI

Your B2B can use AI to optimize its ad placements, ensuring their ads were delivered and seen.  Just as there are good things that can come from AI so can bad. Now imaging you’ve spent thousands of dollars on ads only to find out there’s an AI that can mimic humans browsing and clicking behaviors on the internet. The humans you think are clicking on your ads are just smart AI bots. Take it further, AI can be used to duplicate your websites look and feel, can find ways to spoof your touch points and processes.

So as most point is made above, that not everyone is going to be benefiting financially from AI (Artificial Intelligence). If you didn’t read anything in this content. We hope that you study the outcome of the internet in terms wealth creation.

***More Bonus Below. Enjoy!!

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Wealth outlook for 2020-2025

Even if this report slash opinion forecast suggest upward mobility by some people around the world. It still doesn’t mean the wealth gap decreasing with the presence of AI. So based on this, AI technology still will not benefit lots of people financially that’s just the reality of Capitalism. Well unless systems or policies are created legally to take more from the wealthy to encourage development of the less fortunate.

FYI

[“According to the ‘Global wealth Report 2021’, published by Credit Suisse, global wealth is projected to rise by 39% over the next five years reaching USD 583 trillion by 2025.

Wealth per adult is also projected to increase by 31% and so is the number of global millionaires. The wealth pyramid, an infographic used to determine wealth distribution, will also change.

The bottom segment covering adults with a net worth below USD 10,000 will likely decrease by approximately 108 million over the next five years. The lower-middle segment of the pyramid containing adults with a net worth in the range of USD 10,000 and USD 100,000 is projected to rise by 237 million adults.

Most of these new members are most likely to be from lower-income countries. The upper-middle segment, consisting of adults with wealth between USD 100,000 and USD 1 million is projected to rise by 178 million adults. Most of these new members (approximately 114 million) are likely to come from upper-middle-income countries.

Number of global millionaires is also projected to increase. According to the estimates made by Credit Suisse, the number of global millionaires could exceed 84 million by 2025, a rise of almost 28 million from 2020. The increase of millionaires will not only occur in developed countries such as the USA or other developed countries in Europe, but it is also expected to rapidly increase in lower-income countries. The biggest increase is expected in China, with a change of 92.7%, which is about 4.8 million new dollar millionaires. As a consequence, the number of Ultra High Net Worth Individuals (UHNWI) with net worth exceeding USD 50 million, will also increase. “] – Global wealth report by Credit Suisse.

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BONUS:  Somethings To Consider When Getting Started With AI or AI Systems for Your B2B

• Take advantage of the wealth of online information and resources available to familiarize yourself with the basic concepts of AI
• Take some remote workshops and online courses offered by organizations such as Udacity
• Lookup learning prompts that are specific to your industry
• Consider the tasks that eat up the most time and whether AI can help streamline them

• Whatever you do have ways to verifying the information for accuracy
• Ensure any AI system you use complies with the relevant laws and regulations
• Be very alert and selective as to when to use AI or when a human needs to intervene
• Create AI policy that discloses how the business does and does not use the technology to all stakeholders
• Think about how you can add AI capabilities to your existing products and services

• You need to assess the potential business and financial value of the various possible AI use cases
• Consider what you have the ability to actually achieve within a given time frame
• Identifying what you need to acquire and any processes that need to be refined before you start
• Always start small, have project goals in mind, and, most importantly, be aware of what you know and what you don’t know about AI
• If there are team members, get them involve in a small team, maybe 4-5 people, and give tight time frame to explore and come up with pilots

• After the pilot is completed, you should be able to decide what to do next
• Remember to apply AI to a small sample of your data rather than taking on too much too soon
• Initially or during you’ll need to consider the storage / legal / finance / HR / marketing etc requirements
• You should clearly be transparent on how the tech works in the processes or workflows or formula or decision making to workers, users, managers, etc to prevent errors
• Don’t be afraid to iterate and improve as you go along
• AI systems are mathematical and cannot integrate nuance.
• Because everything needs to be concretely defined, AI are unable to comprehend a whole lot of subjects or qualitative materials

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Bonus: Over 20+ AI Use Cases & Applications

Conversational Analytics

eCommerce Analytics

Geo-Analytics

Image Recognition and Visual Analytics

Real-Time Analytics

Survey & Review Analytics

Voice Authentication

Data Cleaning & Validation Platform

Data Integration

Data Management & Monitoring

Data Preparation Platform

Data Transformation

Data Visualization

Data Labeling

Synthetic Data

Cognitive / Intelligent Automation

Robotic Process Automation (RPA) Implementation

Process Mining

Predictive Maintenance

Inventory & Supply Chain Optimization

Property Management

Digital Assistant

Retail Sales Bot

Prescriptive Sales

No code AI & App Development

Knowledge Management

Natural Language Processing

Secure Communications

Deception Security

Autonomous Cybersecurity Systems

Smart Security Systems

Machine Learning

Deep Learning

Developer Assistance

AI Consultancy

Driving Assistant

Vehicle Cybersecurity

Vision Systems

Self-Driving Cars

Automated Course creation

Personalized Tutoring

Trend analysis

Fraud Detection

Financial Analytics

AI CFO

AI CMO

AI HR

AI CIO

Credit Lending & Scoring

Robo-Advisory

Regulatory Compliance

Patient Data Analytics

Personalized Medications and Care

Drug Discovery

Early Diagnosis

Medical Imaging Insights

Healthcare Market Research

Gene Analytics and Editing

Device and Drug Comparative Effectiveness Analyze

Manufacturing Analytics

AI Collaborative Robots

Robotics