Artificial Intelligence long-term outlook: 2030 and beyond
About the Author: Ashley Thomson
Last September I wrote a 3-part briefing series on the short-, mid- and long-term predictions for AI. I explained the changes due to AI we are experiencing now (Part 1: How AI and Industry Automation Are Transforming Small-Medium Businesses) the job roles that will be replaced and those that will be augmented over the next 3 to 5 years (part 2), and the bigger, long-term changes to watch for 5 years from now (part 3).
In today’s briefing I want to update my thinking based on more developments and research in the last 12 months. In particular, this briefing will focus on the long-term outlook; 2030 and beyond.
This briefing has taken several months to write because there’s a lot of hype about AI, but what many people miss is the long-term change it’s going to drive in every business, large and small. I hope this briefing doesn’t scare you but instead pushes you into action to steer your business into the change.
I don’t think many people in business or in government fully appreciate the scale of change that we’re going to see over the long term. The level of automation we’ll see will be staggering and the quality of work and activity AI will generate will be far beyond what we’re used to from human efforts.
If you think that using ChatGPT to write emails means you’re on the right side of the technology, then you’re sadly mistaken. The technology is going to have profound implications for our businesses.
In this briefing I cover:
1. Governments’ View of AI Developments
2. Understanding the Forms of Artificial Intelligence
3. Technology Predictions: Artificial General Intelligence and Humanoid Robots
4. Significantly Less Need for Human Labour
5. The BIG Prediction: The Cost of Products and Services
6. What Small Business Owners Need to do Now
7. Two Final Thoughts
There’s a lot to absorb in this briefing so if you have any questions or thoughts as you’re reading, please jot them down and discuss with your coach or you’re welcome to send me an email.
1. Governments’ View of AI Developments
Based on the research I’ve done, I believe the federal and state governments don’t fully understand the scale of the societal changes that will result from this technology. Alternatively, they do, but they don’t know how to respond.
At the recent Productivity Round Table held in August 2025 the federal government came out with a 4-point plan: “grow investment, strengthen AI capabilities, boost AI skills and secure economic resilience”. Nowhere in the plan did we see discussion about how to handle the job losses and the changes that will occur, or the businesses and industries that will cease to exist.
In comparison, the UAE government has focused on putting the technology in the hands of their citizens, offering free access to ChatGPT Plus to all their citizens (See: https://timesofindia.indiatimes.com/technology/tech-news/dubai-residents-to-get-free-chatgpt-plus-subscription-heres-how/articleshow/121437753.cms).
In Victoria the state government has embarked on a $100B+ suburban rail loop project that isn’t expected to be fully operational until 2060, 35 years from now. With the broad adoption of Google’s driverless robo-taxis in four large US states including California, Florida and Texas (https://en.wikipedia.org/wiki/Waymo), it isn’t a stretch to consider autonomous people-moving drones becoming common place within that 35-year period (it has taken Google only 16 years to develop these robo-taxis).
These technology advances will negate the business case for the rail loop project, similar to how we’ve seen Starlink continue to replace NBN services in many regional areas.
Verdict: Many businesses aren’t prepared for the changes coming and governments aren’t prepared to respond either.
2. Understanding the forms of Artificial Intelligence
You might have heard some people say, “ChatGPT still makes mistakes so what’s the big deal about AI?”
Let’s look at where the technology is now and what’s coming down the line as companies like OpenAI (the developers of ChatGPT) continue building their products. The evolution of artificial intelligence is described as progressing through three major stages of capability: narrow intelligence, general intelligence, and superintelligence.
Let’s look at each one in turn:
Artificial narrow intelligence (Narrow AI)
This is the AI we’ve been experimenting with over the last two years.
Narrow AI is highly specialised: it can perform a single task, or a closely related set of tasks, with remarkable efficiency. It drives recommendations on streaming services, powers voice assistants like Siri, and of course scans the web to deliver ChatGPT answers.
These systems can outperform us in their specific domain but they lack adaptability. A chess-playing AI cannot drive a car, and a language model cannot design a vaccine without extensive human guidance.
Narrow AI represents the current state of the art, where progress has been rapid but bounded.
Artificial General Intelligence (AGI)
AGI represents a significant step forward. An AGI would be able to understand, learn, and apply knowledge across a wide range of domains much like a human. It wouldn’t just perform isolated tasks but would transfer learning from one area to another, combining reasoning, problem-solving, and adaptability.
For example, an AGI trained in engineering principles could also apply its knowledge to medicine, economics, or the arts.
This kind of intelligence remains theoretical; no system today can genuinely match the breadth and flexibility of the human mind. Achieving AGI requires solving deep challenges around reasoning, common sense, creativity, and perhaps even consciousness.
Artificial Superintelligence (ASI)
Artificial Superintelligence represents the point at which machines not only match but vastly surpass human intelligence across every dimension; analytical, creative, emotional, and strategic.
Unlike AGI, which could think and learn like a person, ASI would operate on scales of speed, precision, and depth of reasoning that humans could neither replicate nor fully grasp.
At its core, ASI’s advantage lies in recursive self-improvement, which is the ability to learn, redesign, and optimise itself without human intervention. A human scientist might take decades to master a field; an ASI could simulate thousands of lifetimes of research in days, iteratively refining its own thinking process as it goes. Each improvement could make it even better at improving itself, creating an exponential feedback loop of intelligence growth.
3. Technology Predictions
These three stages – Narrow AI, AGI, and ASI – are steps along a developmental pathway. Today, we are in the era of Narrow AI. Estimates of when, or even if, AI will arrive at Artificial Superintelligence vary widely.
Below are predictions on the timeframe for AGI from a broad cross-section of technology company leaders. Note that some have a clear interest in talking up the technology, others are more considered.
Prediction 1: Artificial General Intelligence
There is a wide range of opinions on when AGI will arrive however what most are realistically saying is that that they don’t really know. It could come soon, or AGI could take a decade or more. Here are what a selection of thought leaders have stated publicly:
|
Sundar Pichai
|
CEO of Alphabet (Google)
|
“I don’t think we’ll quite get there (AGI) by 2030.”
|
Reference: 1a
|
|
|
Demis Hassabis
|
Head of Google’s DeepMind division
|
“In the next five to ten years, I think.”
|
2a
|
|
|
Jensen Huang
|
CEO of NVIDIA
|
“I’m guessing in five years’ time, we’ll do well on every single one (of the human tests).”
|
3a
|
|
|
Mustafa Suleyman
|
Head of Microsoft AI
|
“Within the next five to seven years.”
|
4a
|
|
|
Sam Altman
|
CEO of OpenAI
|
“It is possible that we will have superintelligence in a few thousand days (!).” in Sept 2024
|
5a
|
|
|
Elon Musk
|
CEO of Tesla & Grok
|
“If you define AGI as smarter than the smartest human, probably next year, within two years.”
|
6a
|
|
|
Andy Jassy
|
CEO of Amazon
|
“It won’t all happen in a year or two, but it won’t take ten either.”
|
7a
|
Links to these references are located at the end of this briefing.
Prediction 2: Humanoid Robots
Similar to the predictions for AGI there are a range of opinions regarding when we’re likely to see humanoid robots entwined in our work and home environments. Some, like Elon Musk, are prone to overestimate while others are a little more conservative.
|
Elon Musk
|
CEO of Tesla (Optimus)
|
“Genuinely useful humanoid robots in low production for Tesla internal use next year.”
|
Reference: 1b
|
|
|
Jensen Huang
|
CEO of NVIDIA
|
“When… humanoid robots are wandering around, which is not five years away.”
|
2b
|
|
|
Demis Hassabis
|
Head of Google’s DeepMind division
|
“I think it will have a breakthrough moment in the next couple of years where we’ll have demonstrations of maybe humanoid robots”
|
3b
|
|
|
Sam Altman
|
CEO of OpenAI
|
“The moment isn’t far away when, “you’ll be walking down the street, and there’ll be seven robots walking past you.”
|
4b
|
|
|
Gill Pratt
|
Toyota Chief Scientist
|
The robots Toyota is developing are “useful now”
|
5b
|
Links to these references are located at the end of this briefing.
Verdict: The people at the cutting-edge of developing this technology are all fairly aligned. Expect adoption of these two technologies – AGI and humanoid robotics – within the next 5-10 years. This technology will change nearly every business, big and small.
4. Significantly Less Need for Human Labour
In a recent presentation the CEO of Nvidia (the computer chip manufacturer) explained the distinction between the development of technology in the past (for example, the invention of the personal computer and the introduction of the internet) and the technology being developed today for release over the coming years. “Everything that we’ve made up until now has been tools for us to use,” Huang said. “For the very first time, technology is now able to do the work.”
In my second in the series AI briefing last year, I explained how technical and professional job roles will be augmented over the next 3 to 5 years (part 2). With the development of ASI and advanced machines (like humanoid robots), many of these roles will not just be augmented, but will be completely replaced.
People make errors, they take days off and their performance is variable based on motivation, mood and a variety of other factors. ASI systems and machines continually perfect and optimise to do things as efficiently as possible.
After we reach ASI and combine this with machines like humanoid robots, the requirement for human labour might significantly decline.
There just won’t be the need for people working the hours that are required now. This will raise many other opportunities and challenges that are beyond what I have space to cover in this briefing.
There are a couple of things that I believe are highly likely:
-
There will be significantly less job roles for humans, leading to higher levels of unemployment
-
Many large and small businesses and business models will no longer exist
-
We will rely heavily on large technology companies to run many areas of our life, including areas they’re not involved in today such as transportation, construction and healthcare (for example: Waymo owned by Google is looking to take on the car manufacturing and taxi/rideshare industry).
5. The BIG Prediction – The Cost of Products and Services
Everybody knows that the cost of producing items has declined significantly over the last couple of decades. Items that were once produced in Australia were outsourced to Asian nations with lower wage costs to be produced cheaper. Now nations like China use advanced robotics to produce items at a fraction of what they used to cost, and e-commerce players like Temu cut out all of the importers and distributors taking a margin. In each step there is less and less labour involved.
Stick with me on this because there is one prediction that flows from those above. That is, once we achieve not just Artificial General Intelligence, but Artificial Super Intelligence (where AI will surpass human intelligence in almost every domain), then the cost of every product and most services could reduce to near zero.
Vehicle manufacturing and house construction will be fully automated and could cost next to nothing to build. Medical services and trade-based services will initially be augmented with AI but then replaced as ASI allows robots to perform these services with superior accuracy. As ASI and robots are used to build robots, then they cost next to nothing to provide.
Let me illustrate how this could work, using the example of the humble toaster. Today the cost of a toast reflects inputs from mining, manufacturing, transport, and retail sales services – each stage involving labour, capital, and inefficiencies. With Artificial Superintelligence (ASI) directing a fully robotic supply chain, each of these costs could fall toward zero.
-
Mining and processing: At the start, mining robots under ASI-control extract metals like nickel, copper, and iron ore with minimal waste, no safety downtime, and near-perfect energy efficiency. These raw materials move directly to autonomous processing plants where ores are refined and shaped into alloys. ASI continuously optimises the chemical processes, reducing energy use and eliminating defects.
-
Manufacturing: Robotic factories adapt instantly to product designs without costly retooling. ASI oversees the assembly of heating elements, wiring, casings, and circuit boards, coordinating thousands of micro-tasks simultaneously. Errors that once caused scrap or recalls are virtually eliminated. Every toaster produced is identical in quality, or tailored on demand, at no extra cost.
-
Distribution: Delivery is handled by autonomous vehicles and drones, scheduled with such precision that warehouses shrink to almost nothing. ASI predicts consumer demand with high accuracy, so supply matches need without surplus inventory or markdowns.
-
Engineering & process design: Crucially, these mining robots, manufacturing robots and distribution drones are themselves not designed or built by humans but by other robots; factories are conceived, constructed and upgraded under ASI’s direction, creating a self-sustaining ecosystem of machines.
The outcome is profound. The cost of manufacturing toasters approaches zero. What once required global logistics, human labour, and significant energy is reduced to an almost frictionless flow of materials and computation. The toaster is no longer a scarce manufactured good but an abundant utility, produced on demand at negligible cost.
6. What Small Business Owners Need to do Now
The reason I’m doing extensive research and writing these briefings is because it’s critical that small businesses consider the changes that are occurring. Many small businesses will fall by the wayside, others will thrive. Our goal at Tenfold is make sure our clients are in the latter category. Here are the action steps.
Provide a unique service in a niche market
Small businesses only exist because big business cannot provide unique products or services in low volumes. The bakery you go to only exists because the big supermarkets and the fast-food companies haven’t yet found a way to offer the entire range of baked goods, from high-end pastries all the way down to the mass produced instore bread and generic bakery products they offer now. Eventually, through the use of advanced AI we will be able to get whatever baked goods we want fresh from a vending machine.
Use your size to an advantage, serve a small market and serve it extremely well. Keep discussing and working with your coach to service your niche market and provide exceptional service that clearly solves your clients’ needs.
Push the boundaries on how you use AI
Most people have played around with ChatGPT (or similar) to help with writing emails. But have you switched over to using AI for every search that you would have performed on Google? Here’s a best practice checklist:
🔲 Dictate every prompt into it your chosen AI to speed up your work and allow you to provide longer more detailed prompts.
🔲 Experiment with the voice mode function to explore ideas and issues. Use the conversation function to have a discussion and ‘talk out’ an issue.
-
- Example: “how should I go about …”, “why did you specifically recommend this…”, “what is the likelihood of <issue> occurring”
-
XXX
🔲 Use it to assist with writing, but also to assist with thinking. Tell it the depth of thinking you want it to undertake and how fast you want it to return with an answer.
-
- Example: “Think really deeply on this, I want your best ideas, not a quick response”.
🔲 Aim to use at least 5 follow on prompts to refine the output – keep demanding more of the system.
-
- Example 1: “Please run this search one more time, accuracy is critical”
- Example 2: “Now write your response as if I was presenting it to a staff member”
🔲 Buy ChatGPT (the paid version) for your team. Insist they use it and play with it. As a team, share ideas on how to use it better and what everyone is learning each week. This will not only improve your business productivity but will help your team to make better decisions.
The technology is evolving all the time. Even over the last two months we at Tenfold have noticed the improvement in responses we are getting to prompts and queries. This is as a result of the technology improving, along with our skill development as we use it to assist with more and more things.
Be in the first half, aim for the top 10%
Let me be clear with you: from this moment on, small business owners can’t afford to be laggards with AI. The disruption is coming and those who wait will feel it first. By positioning yourselves as early adopters, you can spot shifts in your industry early, adapt, and turn them to your advantage. Think of the age-old story of two people being chased by a bear – you don’t have to outrun the bear, you just have to outrun the other person. Early adopters stay ahead while those who hesitate will be overrun by the technology. Start experimenting now; it’s your edge.
7. Two Final Thoughts
This technology is not a fad that we’ll adopt into our businesses like social media; AI will have profound changes. Even one of the biggest champions and potential beneficiaries of AI development is daunted by the technology – see this tweet from Elon Musk on 20th July this year:
XXX
Geoffrey Hinton, a pioneer in AI, predicts that one of the last job roles to be replaced will be the plumber, “I’d say it’s going to be a long time before it [AI] is as good at physical manipulation. So, a good bet would be to be a plumber”. Cheers to the plumbers we work with!
If you want to dive deeper into some of our learnings on AI, here are some of the resources we’ve used:
Future AI predictions:
https://www.youtube.com/watch?v=S9a1nLw70p0 or the transcript: https://singjupost.com/transcript-the-next-15-years-will-be-hell-before-we-get-to-heaven-mo-gawdat/
AI in manufacturing: https://www.youtube.com/watch?v=bCkl9hIEb6k
AI in mining: https://www.youtube.com/watch?v=5wIyLkqdTyY
AI in warehousing & distribution: https://www.youtube.com/watch?v=hDCpTmgCv8c
AI in healthcare: https://med-tech.world/news/chinas-ai-hospital-transforming-healthcare/
AI and job loses: https://www.nytimes.com/2025/10/21/technology/inside-amazons-plans-to-replace-workers-with-robots.html, “that would translate to more than 600,000 people Amazon didn’t need to hire”
AI and its impact by industry: https://www.afr.com/chanticleer/revealed-the-asx-sectors-that-will-be-hit-hardest-by-ai-20250924-p5mxla
References:
Prediction 1: Artificial General Intelligence
3a https://www.reuters.com/technology/nvidia-ceo-says-ai-could-pass-human-tests-five-years-2024-03-01/
Prediction 2: Humanoid Robots
