TheDinarian
News • Business • Investing & Finance
A guide to modernizing payments in the financial sector
May 29, 2023
post photo preview

Canada must act swiftly to remain on track with modernizing its financial sector policies that affect how consumers make payments. Other countries are adopting fintech innovation at a much faster pace, leaving Canadians with limited consumer choice and competition among financial service providers compared with other parts of the world. This is largely due to the Canadian market being long dominated by an oligopoly that has a strong hold on the movement of money. 

Canada’s big six banks control nearly 90 per cent of the country’s banking assets, which dictates how money moves through Payments Canada. This is the system that operates the clearing and settlement systems that power the Canadian economy. The same big six are also major shareholders of Interac, the only option for debit card payments and email money transfers. Banks are also the leading issuers of Visa and Mastercard credit cards. As a result, the movement of money occurs largely between these big banks via the networks of Visa, Interac, Mastercard and Payments Canada. 

Even with other financial institutions and burgeoning fintechs, these six banks act as the middleman for processing payments. Fintechs still cannot freely access essential financial infrastructure such as payments systems or user banking details. 

To fully modernize payments and enable open banking, Canada must mirror the successes of others – including the United Kingdom, the European Union, Singapore and Australia – in enabling innovation, growth and competition in the market. Those jurisdictions have demonstrated the benefits of fostering an open and competitive fintech ecosystem while Canada has only taken baby steps. 

One of the first chapters of the 2023 federal budget, “Making Life More Affordable and Supporting the Middle Class,” would have been a perfect fit for payments modernization initiatives that will ultimately help lower costs on Canadian consumers and small businesses. Unfortunately, none of these policies received a direct mention, which is a missed opportunity.

One positive action contained in the budget is the commitment to explore the elimination of junk fees (hidden fees).  This must be paired with the four key payment modernization policy initiatives that will allow financial service providers to reduce costs and increase convenience and speed.  

These four policy initiatives are the implementation of instant payments through the Real-Time Rail system; establishing the modern licencing framework and market conduct rules in the Retail Payment Activities Act; amending the Canadian Payments Act; and expanding banking to embrace open banking.  

Together, these payments modernization initiatives will result in lower payment costs, increased innovation and competition, and enhanced financial stability.   

Instant payments:  

More than 60 countries around the world already have real-time payments systems (the Real-Time Rail system), which allow for payments to be processed within seconds rather than waiting for several minutes to hours. Canada was set to join that list in 2022, but Payments Canada has delayed the launch of the Real-Time Rail system twice with no definitive timeline in sight, referencing the need to validate and test the system’s components and end-to-end integration.  

But to be clear, Payments Canada’s Real-Time Rail system will utilize the global data standard (ISO 20022) for payments messaging and a common language for financial institutions around the world. 

Canadians deserve faster payments. A failure to deliver on this promise is a setback for businesses and does not give consumers the peace of mind that a payment has settled, especially during a cost-of-living crisis. 

Modern payments licence: 

In 2021, Canada established a new payments licence under the Retail Payment Activities Act. Aside from Quebec, Canada didn’t have money transmission or payments licensing requirements until now as payments companies only had to register with FinTRAC. With the Retail Payment Activities Act now law, the Bank of Canada is the primary regulator of payments companies. While seemingly simple, the overall process is ongoing.  

Retail Payment Activities regulations were published in 2023 after consulting the industry, which is a major step in the right direction, but the Bank of Canada must still create a payments supervision team. The likeliest next step will be the registration of payments companies this year, with oversight starting in 2024. 

This new payments regime brings Canada up to speed with other jurisdictions that have been at the forefront of payments innovation, such as the UK and the EU – both of which are referenced in the Retail Payment Activities Act

Canadian policymakers have understood that bringing payment firms into a clear regulatory environment will even the playing field for all players in the financial sector, thereby being beneficial for consumers, industry and broader financial stability. While Retail Payment Activities Act will enable fintechs and others to invest with certainty in Canada, it will also ensure customer funds are protected and firms have proper governance and risk management structures, among other requirements.  

Non-bank access to the payments system: 

Along with the Retail Payment Activities Act, the government has consulted on proposals to expand access to its payments system to non-banks. This means fintechs could become members of Payments Canada and directly clear and settle payments, unlocking lower-cost payments, increasing the speed of payments and reducing the reliance on bank partners.   

This is in line with global momentum toward expanded access to payments systems. The Financial Stability Board’s G20 Roadmap for Enhancing Cross-border Payments includes this as one of its recommendations. Other governments including the UK, Singapore, Hungary, Australia and Brazil have already moved in this direction and soon the broader EU is expected to do so with the Payment Services Directive 2 

How the Big Five banks control how money moves in Canada 

Open banking is an opportunity, not a threat 

At Wise, we have already demonstrated the benefits of expanded access. Wise was the first non-bank to directly connect with the Bank of England’s Faster Payment System in 2018. Once granted, we immediately lowered fees for those customers by 20 per cent and increased the average payment speed from 15 minutes to less than 20 seconds. The UK’s Faster Payment System is a great example of the Real-Time Rail system and non-bank access working together in practice. When access was granted more broadly, the total number of Faster Payment System participants went from primarily banks (18) to several fintechs (33). It resulted in increased competition, consumer adoption and ultimately lower costs. 

But this goes beyond cost and speed. It also speaks to stability. With the growth of newer entrants and fintech scale-ups in financially challenging times, the systemic risk to the financial system is higher when direct access is not available to payments companies. Payment companies are clustered around a limited number of banks able to provide an indirect link to the payment system. This means that if one of those banks wobbles, all the payment companies depending on that bank for access wobble, too. That’s why direct access should be democratized while applying risk-based, objective criteria. 

Amendments to the Canadian Payments Act will be necessary for this change, and that was not included in the last two federal budgets. Even with those amendments in place, direct access likely won’t be granted to payments companies until after the Bank of Canada’s supervision of payments under the Retail Payment Activities Act begins, which likely means 2024 or 2025. 

Open banking:  

Open banking has been one of the most talked-about initiatives of Canada’s payments modernization. It will give consumers the right to their own financial data in a secure manner, so that they can make better financial decisions and utilize new products, such as budgeting tools.   

In March 2022, former PwC director Abraham Tachjian was appointed as Canada’s open banking lead by the federal government and tasked with the development of the open banking framework. Canada is now consulting with the industry, regulators and consumer representatives.  

Notably, open banking as a way-to-pay can become a cheaper alternative to traditional payment methods such as credit and debit cards, delivering more competition in payment methods for Canadians and ultimately driving costs down.  

These four initiatives have the power to fix slow, opaque and costly financial services – specifically payments – and usher Canada’s payments infrastructure into the present and future. Without them, Canada will be stuck in the era of payments past to the detriment of its consumers and businesses.  

Link

 

 

community logo
Join the TheDinarian Community
To read more articles like this, sign up and join my community today
0
What else you may like…
Videos
Podcasts
Posts
Articles
🤖 AI Won't Destroy Jobs—It Will Create a Labor Shortage! 📉

While most headlines focus on AI-driven displacement, Groq Founder and CEO Jonathan Ross offers a fascinating, contrarian perspective. He argues that instead of mass unemployment, we are heading toward a massive labor shortage driven by three tectonic shifts:

1. Massive Deflationary Pressure: Efficiency gains from automated farming, robotics, and streamlined supply chains will drive down the cost of everyday essentials—from coffee to housing—meaning people will ultimately need less money to thrive. ☕️🏠

2. The Great Economic Opt-Out: As living costs drop and productivity skyrockets, humans will choose to work fewer hours, fewer days a week, and retire much earlier because their lifestyles will be easier to support. ⏳🌴

3. Unimaginable New Industries: Just as agriculture dropped from 98% of the US workforce a century ago to just 2%—paving the way for entirely new careers like software development and content creation—tomorrow's jobs are literally ...

00:02:00
🔵 The most important shape nobody talks about 🔵

Heinz Hopf discovered this in 1931. Roger Penrose called it "an element of the architecture of our world.' Eric Weinstein brought it up on Joe Rogan - and the silence in the room said everything.
The Hopf fibration maps a 4D hypersphere onto a regular sphere using circles that never intersect but each links through every other exactly once. It shows up in at least 8 areas of physics - including the Bloch sphere geometry that every qubit in a quantum computer lives on.

00:09:42
🌐 Institutional Access Meets Dcentralized AI! 🤖📈

The bridge between traditional capital markets and the decentralized AI economy is expanding. Through investment vehicles like the Grayscale Bittensor Trust ($GTAO), traditional market participants gain regulated exposure to the native asset powering decentralized machine learning.

No wallet setups, no complex custody hurdles—just direct tracking of the infrastructure driving open-source intelligence.👇

00:05:18
🚨 Chutes is being framed as a Hyperliquid-style breakout for decentralized AI inference, with live revenue, verified GPU infrastructure, and a direct challenge to centralized cloud AI 🚨

Chutes is gaining attention as a decentralized AI inference platform that claims to combine real usage, cryptographic verification, confidential computing, and open-source infrastructure into a working production system. The thesis is simple: instead of trusting Big Tech clouds with AI workloads, users get a distributed compute layer built around verification and privacy.

🔑 Key points

🔹 Chutes is live in production and reportedly scaled to more than 1,170 active GPU nodes, including large numbers of Nvidia H200s and Blackwell-class hardware.

🔹 The platform says it has processed nearly 38 trillion tokens since launch across 53 deployed applications and more than 700,000 registered users.

🔹 The team reportedly cut unprofitable usage programs, reduced total token volume, and still improved revenue efficiency, with revenue per GPU rising sharply after removing subsidized traffic.

🔹 Chutes is using post-quantum cryptography, trusted execution environments, and Nvidia confidential ...

🚨 Chutes is being framed as a Hyperliquid-style breakout for decentralized AI inference, with live revenue, verified GPU infrastructure, and a direct challenge to centralized cloud AI 🚨
🚨 JPMorgan’s criticism of the CLARITY Act is fueling a fresh power struggle over who gets to write America’s crypto rules 🚨

A new clash is emerging between legacy finance and crypto legislation after JPMorgan CEO Jamie Dimon reportedly warned that the CLARITY Act could let crypto firms offer bank-like products without bank-level oversight. The dispute is quickly turning into a larger fight over regulation, competitiveness, and who controls the future architecture of digital finance in the United States.

🔑 Key points

🔹 Jamie Dimon reportedly called the CLARITY Act a threat to the financial system, arguing it could allow crypto firms to offer yield-like products while avoiding the capital, reserve, and oversight burdens traditional banks face.

🔹 Senator Cynthia Lummis pushed back publicly, framing the issue as a global strategic race and warning that if the U.S. does not set digital asset standards, other powers will.

🔹 The core tension is whether the bill creates legitimate regulatory clarity or simply opens the door to regulatory arbitrage for crypto platforms operating outside the traditional banking...

🚨 JPMorgan’s criticism of the CLARITY Act is fueling a fresh power struggle over who gets to write America’s crypto rules 🚨
👉 Coinbase just launched an AI agent for Crypto Trading

Custom AI assistants that print money in your sleep? 🔜

The future of Crypto x AI is about to go crazy.

👉 Here’s what you need to know:

💠 'Based Agent' enables creation of custom AI agents
💠 Users set up personalized agents in < 3 minutes
💠 Equipped w/ crypto wallet and on-chain functions
💠 Capable of completing trades, swaps, and staking
💠 Integrates with Coinbase’s SDK, OpenAI, & Replit

👉 What this means for the future of Crypto:

1. Open Access: Democratized access to advanced trading
2. Automated Txns: Complex trades + streamlined on-chain activity
3. AI Dominance: Est ~80% of crypto 👉txns done by AI agents by 2025

🚨 I personally wouldn't bet against Brian Armstrong and Jesse Pollak.

👉 Coinbase just launched an AI agent for Crypto Trading
The Government Is Tracking Your Silver...

Hippius (hippius.com) offers storage at a lower price per terabyte than Google Drive, iCloud, and Dropbox.

1/100th the cost (!)

Only possible on Bittensor $TAO

Now with a Dropbox-like desktop storage app as well as an S3-compatible API.

post photo preview
🚨 BREAKING: XRP JUST GOT PLUGGED DIRECTLY INTO THE U.S. FEDERAL RESERVE’S FEDNOW SYSTEM 😳

Volante’s Ripple integration just unlocked $XRP for INSTANT FedNow payments.
Banks can now settle through XRP on the same rails the Fed uses for 24/7 real-time transfers.

This is the quiet infrastructure move nobody saw coming… until now.

The bridge is LIVE.

https://x.com/pumpius/status/2091584402107314186

Irrespective of which tokens are utilized on the XRP Ledger for FedNow transactions, the underlying mechanism that burns XRP remains constant. 🔥 This sustained reduction in supply underpins a long-term bullish thesis for XRP holders. 📈📈🚀

post photo preview
post photo preview
🤖Can Decentralized AI Stop Big Tech from Owning the Future of Robotics?🤖
The race to build the future of robotics is no longer just about robots. It's about who controls the intelligence behind them.
 
Over the last three years, a small group of companies has emerged as the backbone of the AI revolution. Microsoft provides cloud infrastructure. NVIDIA supplies the chips. Google, OpenAI, Anthropic, Meta, and others develop the models. Together, they control much of the compute, data, and software stack powering modern AI.
 
Now that AI is moving into the physical world, many are asking a bigger question:
 
Will these same companies end up controlling robotics too?
 
It's a valid concern.
 
The latest generation of robots relies on enormous amounts of compute, simulation, training data, and foundation models. Many robotics startups today are built on infrastructure provided by large technology companies. NVIDIA's Omniverse is becoming a key simulation environment for robot training. Microsoft Azure is powering the training of robotics foundation models. Physical AI startups increasingly depend on hyperscale cloud infrastructure to train and deploy intelligent systems. Recent partnerships across the industry show just how central Big Tech has become to robotics development.
But while Big Tech is building the highways, another movement is trying to ensure it doesn't own every destination.
 
That movement is decentralized AI.
 
Why Decentralized AI Exists
 
The idea behind decentralized AI is simple. Instead of a handful of companies owning the models, compute infrastructure, data pipelines, and intelligence networks, these resources are distributed across thousands of participants.
 
This means anyone can contribute compute, contribute models, validate outputs and can participate.
The most visible example today is the decentralized AI network known as Bittensor (@bittensor). The network has evolved into a large ecosystem of specialized AI markets called subnets, where participants compete to provide useful machine intelligence and are rewarded based on performance. Rather than relying on a single company, intelligence is generated and validated by a distributed network of miners and validators.
 
Think of it as an attempt to build an open marketplace for AI instead of a world where intelligence is rented from a few centralized providers.
 
Why This Matters for Robotics
 
Robotics has a unique problem. Unlike chatbots, robots operate in the physical world. They need to perceive environments, make decisions, move safely and they need to learn continuously.
 
The challenge is that collecting and training on real-world robotic data is incredibly expensive. That's one reason large companies have such an advantage. They can afford the compute, simulation environments, and data infrastructure needed to train robotics models at scale.
 
This is where decentralized systems become interesting.
 
Instead of one company collecting all the data and training all the models, decentralized networks could allow thousands of contributors to participate in building robotic intelligence.
 
Imagine a future where:
  • Warehouse robots contribute operational data.
  • Delivery robots contribute navigation data.
  • Factory robots contribute manipulation data.
  • Developers contribute models.
  • Validators evaluate performance.
The resulting intelligence becomes a shared network rather than a proprietary asset.
 
That vision is beginning to emerge.
 
Bittensor's Move Toward Physical AI
 
While many people associate Bittensor (@bittensor) with language models and AI services, parts of the ecosystem are increasingly exploring embodied intelligence and robotics.
 
One example is Kinitro, a subnet focused on incentivizing the training and evaluation of embodied AI systems. The goal is to create competitive environments where developers build robotic intelligence and are rewarded based on performance.
 
The broader Bittensor ecosystem has also expanded into compute marketplaces, distributed inference systems, bandwidth infrastructure, and AI coordination layers that could eventually support robotics workloads. Several subnets now focus on decentralized compute, confidential inference, data transfer, and model training, critical components for future robotic systems.
 
In other words, the pieces are starting to appear.
 
Not a decentralized robot network yet.
 
But the infrastructure that could support one.
 
Beyond Bittensor: The Rise of Physical AI Networks
 
Bittensor isn't alone.
 
Across the industry, researchers and builders are experimenting with decentralized approaches to physical AI.
 
New research published in 2026 introduced the concept of DAO-enabled decentralized physical AI, or DePAI. The idea combines robotics, decentralized infrastructure, AI models, governance systems, and human oversight into a single framework. Instead of centralized control, robots and physical infrastructure could be coordinated through transparent rules and distributed ownership models.
 
At the same time, developers are exploring decentralized operating systems for robots that allow machines to communicate directly with each other and with distributed compute resources. These architectures are designed to make robotic systems more resilient and less dependent on a single cloud provider.
 
The goal is not simply decentralization for its own sake.
 
The goal is resilience.
 
If one server fails, the system continues.
 
If one company disappears, the network survives.
 
If one participant leaves, innovation continues.
 
But Here's the Reality
 
Decentralized AI faces the same challenge every decentralized technology faces.
 
Big Tech has resources. A lot of resources.
 
Training advanced robotics models requires enormous compute budgets, sophisticated simulation environments, access to specialized hardware, and vast amounts of real-world data.
 
That's why many robotics startups still partner with major cloud providers and AI companies. It's often the fastest path to deployment.
 
And there are legitimate concerns about whether decentralized networks can maintain quality, reliability, and security at the scale required for industrial robotics. Even researchers studying decentralized AI systems have highlighted risks around concentration, incentives, governance, and network security.
 
The challenge isn't just decentralizing intelligence.
 
It's decentralizing intelligence while maintaining performance.
 
That's much harder.
 
The Most Likely Outcome
 
The future probably won't be fully centralized. And it probably won't be fully decentralized either. Instead, we're likely heading toward a hybrid model.
 
Large technology companies will continue providing chips, cloud infrastructure, simulation platforms, and foundational research.
 
At the same time, decentralized AI networks will emerge as alternative coordination layers where intelligence, data, and economic value can be shared more openly.
 
The companies building robots may use NVIDIA hardware.
 
Train on Azure.
 
Run foundation models from OpenAI.
 
But they may also participate in decentralized data networks, decentralized compute markets, and decentralized intelligence protocols.
 
The future of robotics could end up looking less like a monopoly and more like an ecosystem.
 
The Bigger Question
 
The real question isn't whether decentralized AI can eliminate Big Tech.
 
It can't.
 
At least not anytime soon.
 
The real question is whether decentralized AI can prevent a future where a handful of companies control every robot, every model, every dataset, and every decision made by the machines operating around us.
 
As robots become workers, assistants, delivery drivers, factory operators, and even economic agents, that question becomes increasingly important.
 
Because the battle for the future of robotics is no longer about hardware.
 
It's about who owns the intelligence.
 
And that battle is just getting started.
 
 

🙏To support my work, Helping to keep the signal high and the noise low:

👉 Cashapp: $thedinarian

👉 Buy me a coffee: https://buymeacoffee.com/thedinarian

👉 PayPal: Scan the QR code below 📲 or Click Here

👇 Crypto Donations 👇

XRP: r9pid4yrQgs6XSFWhMZ8NkxW3gkydWNyQX
XLM: GDMJF2OCHN3NNNX4T4F6POPBTXK23GTNSNQWUMIVKESTHMQM7XDYAIZT
XDC: xdcc2C02203C4f91375889d7AfADB09E207Edf809A6

Read full Article
post photo preview
Navigating the world of blockchain 🧭
Navigating the world of blockchain can feel like learning a completely foreign language. Between technical jargon and fast-moving Web3 terminology, getting started can be overwhelming.

Whether you are exploring digital assets, building on-chain, or simply trying to understand decentralized technology, here is your foundational glossary of essential blockchain terms every beginner should know.

🏛️ 1. Core Architecture: The Base Layer

  • Blockchain: A distributed, immutable digital ledger that records transactions across a peer-to-peer network of computers. Once data is written to a block and added to the chain, it cannot be altered without altering all subsequent blocks.
  • Block: A collection of verified transactions grouped together. Once filled, the block is cryptographically linked to the previous one, forming a chronological "chain."
  • Node: An individual computer connected to a blockchain network that helps validate transactions, store ledger data, and maintain network consensus.
  • Consensus Mechanism: The set of rules and algorithms that network nodes use to agree on the validity of transactions.

    • Proof of Work (PoW): Requires miners to solve complex mathematical puzzles using computational power (e.g., Bitcoin).
    • Proof of Stake (PoS): Requires validators to lock up ("stake") native tokens as collateral to participate in block validation (e.g., Ethereum).

🔑 2. Ownership & Security: Wallets and Keys

  • Public Key (Address): An alphanumeric string that acts like your bank account number or email address. It is safe to share publicly so others can send you digital assets.
  • Private Key: A secret cryptographic passphrase or key that grants full access and control over your wallet assets. Never share your private key or seed phrase with anyone.
  • Seed Phrase (Recovery Phrase): A sequence of 12 to 24 random words generated when you set up a wallet. It acts as the master backup key to restore your wallet and access your funds on any device.
  • Hot Wallet vs. Cold Wallet:

    • Hot Wallet: A software-based crypto wallet connected to the internet (e.g., browser extensions, mobile apps), making it convenient for frequent transactions but higher risk.
    • Cold Wallet: An offline hardware device (e.g., Ledger, Coldcard) designed to isolate private keys from internet-connected threats.

⚙️ 3. Execution & Functionality: Smart Contracts and Apps

  • Smart Contract: Self-executing code stored on a blockchain that automatically enforces agreement terms once predetermined conditions are met—eliminating the need for intermediaries.
  • dApp (Decentralized Application): Applications built on top of a blockchain network that run via smart contracts rather than centralized cloud servers.
  • Gas Fees: Network transaction fees paid to validators or miners to cover the computational energy required to process actions on a blockchain.
  • Layer 1 vs. Layer 2:

    • Layer 1 (L1): The underlying primary blockchain network (e.g., Bitcoin, Ethereum, Solana) that handles base security and finality.
    • Layer 2 (L2): Secondary frameworks or companion networks built on top of an L1 to increase transaction speeds and lower gas fees (e.g., Arbitrum, Optimism, Base).

💰 4. Financial & Market Concepts

  • Tokenomics: The economic design, supply dynamics, utility, and distribution model of a cryptocurrency or token project.
  • DeFi (Decentralized Finance): Financial services—such as lending, borrowing, trading, and earning interest—built on smart contracts without traditional banks or financial intermediaries.
  • Liquidity: The ease with which an asset can be bought or sold in a market without significantly impacting its price.
  • DYOR (Do Your Own Research): A foundational golden rule in the Web3 space reminding users to independently verify technical code, whitepapers, and team backgrounds before making any capital commitments.

💡 Quick Cheat Sheet

"Not your keys, not your coins."

If you do not hold the private keys or seed phrase to your digital wallet, you do not truly own the assets inside it—a centralized entity or exchange does. Always prioritize security first as you explore the space.

🙏To support my work, Helping to keep the signal high and the noise low:

👉 Cashapp: $thedinarian

👉 Buy me a coffee: https://buymeacoffee.com/thedinarian

👉 PayPal: Scan the QR code below 📲 or Click Here

👇 Crypto Donations 👇

XRP: r9pid4yrQgs6XSFWhMZ8NkxW3gkydWNyQX
XLM: GDMJF2OCHN3NNNX4T4F6POPBTXK23GTNSNQWUMIVKESTHMQM7XDYAIZT
XDC: xdcc2C02203C4f91375889d7AfADB09E207Edf809A6

Read full Article
post photo preview
AI Is Coming for Your Job Title

Artificial intelligence may or may not take your job, but it has already broken into the human resources department and vandalized the org chart.

The evidence is all over LinkedIn, where perfectly serviceable occupations now arrive wearing titles such as “forward-deployed and agentic AI architect.” That person may be building sophisticated software. They may also be helping a chatbot remember what happened three prompts ago. Either way, somebody approved the business cards.

The expanding AI lexicon offers a useful counterpoint to the darker debate about technology and employment. Most discussion centers on how many jobs AI will eliminate. Hiring data presents a more complicated picture that includes a weak overall labor market containing a small but rapidly growing neighborhood of AI-related work.

Indeed Hiring Lab found that the number of postings on Indeed mentioning AI surged 134% from its February 2020 level by the end of 2025, even as total postings stood only 6% above that benchmark. AI appeared in a record 4.2% of Indeed postings in December.

AI, in other words, is not merely changing work. It is adding syllables to it.

The Titles Employers Actually Want

The undisputed champion is AI engineer, which ranked No. 1 on LinkedIn’s 2026 Jobs on the Rise list. The ranking, based on growth during the previous three years, also highlighted AI consultants and strategists, AI and machine-learning researchers and data annotators.

The title is popular partly because it is wonderfully accommodating. An AI engineer might build applications around large language models, connect corporate data to an AI system, improve model performance or spend Thursday afternoon persuading a customer service bot not to offer refunds for products the company doesn’t sell.

Indeed’s data showed the terminology spreading beyond Silicon Valley. Nearly 45% of data and analytics postings contained an AI-related term at the end of 2025, along with roughly 15% of marketing postings and 9% of human resources listings. A more recent Indeed analysis reported by Business Insider found that the number of frequently advertised job titles explicitly referencing AI rose from 264 in 2022 to 822 in the first quarter of 2026. Nearly two-thirds were outside traditional technology fields.

That produces titles such as AI marketing manager, AI learning specialist, responsible AI counsel and AI transformation lead. These are not always new occupations. Frequently, they are familiar jobs that have discovered a highly effective résumé keyword.

LinkedIn data cited by the World Economic Forum estimated that AI investment has supported 1.3 million positions, including AI engineers, data annotators and forward-deployed engineers, plus more than 600,000 AI-enabled data center jobs. The server racks, unlike the chatbots, still need electricians.

The Jobs With the Science-Fiction Salaries

At the upper end, AI has created a compensation market that resembles professional sports, except the competitors wear hoodies and discuss inference latency.

Syracuse University review put chief AI officer compensation between $200,000 and more than $500,000, while specialized roles can exceed $400,000 after bonuses and equity. Frontier research engineers, AI infrastructure specialists and engineers who can train or deploy advanced models command some of the largest packages.

Then there is the forward-deployed engineer, an old Palantir title that the AI boom has placed on a rocket sled. These engineers embed with customers, translating an executive’s desire to “do something with AI” into software that works. The Next Web reported that Indeed postings for the role were about 19 times higher in January than a year earlier.

CTO guide from the blog Signal Through the Noise placed forward-deployed engineer compensation between $238,000 and $700,000, research-engineering packages as high as $1.4 million and chief AI officer compensation above $1 million in some cases. It also made a less flattering observation: Many lavishly differentiated titles describe the same three basic functions. People build AI products, train models or keep the infrastructure from catching fire.

The Department of Unnecessary Titles

AI has created some genuinely new work. Evals engineers design tests to determine whether models perform reliably. AI red teamers try to make systems fail before customers do. Model behavior engineers study why an AI system responds as it does. AI governance leaders manage risks involving data, bias, security and regulation.

Other titles seem to have escaped from a brainstorming retreat.

There is the Claude Evangelist, whose mission apparently combines product education with the traditional duties of an apostle. There are vibe coders, who build software by describing what they want and accepting AI-generated code with varying degrees of supervision. “Vibe engineer” is the more respectable version, roughly equivalent to putting on a blazer before asking the machine to fix the login page.

“Context engineer” is a real discipline involving the data, instructions, memory and tools supplied to AI models. “Prompt engineer,” once advertised as a possible six-figure profession for gifted chatbot whisperers, is increasingly treated as one skill inside a broader AI role.

The CTO guide also identified “builder,” “AI-native developer,” “RAG engineer,” “agentic AI engineer” and “principal agentic GenAI forward-deployed context architect,” the last of which appears to require both technical proficiency and exceptional lung capacity.

Has AI created entirely new jobs? Absolutely. Some occupations, including AI safety, evaluation and model governance, exist because modern generative systems introduced new technical and business problems. However, many job titles are old jobs with fresh vocabulary, higher salary bands and a sudden aversion to the words “software developer.”

That may be the safest prediction about AI and employment. The machines will automate some tasks, generate others and force companies to rethink the division of labor. Before any of that is settled, however, corporate America will form a steering committee, appoint a chief agentic transformation evangelist and schedule a meeting to determine what that person does.

Source

🙏 Donations Accepted, Thank You For Your Support 🙏

If you find value in my content, consider showing your support via:

🙏 Cashapp: $thedinarian

🙏 Buy me a coffee: https://buymeacoffee.com/thedinarian

🙏 PayPal: Scan the QR code below 📲 or Click Here

🙏 Crypto Donations 👇
XRP: r9pid4yrQgs6XSFWhMZ8NkxW3gkydWNyQX
XLM: GDMJF2OCHN3NNNX4T4F6POPBTXK23GTNSNQWUMIVKESTHMQM7XDYAIZT
XDC: xdcc2C02203C4f91375889d7AfADB09E207Edf809A6

Read full Article
See More
Available on mobile and TV devices
google store google store app store app store
google store google store app tv store app tv store amazon store amazon store roku store roku store
Powered by Locals