Author: IRPA AI Senior Analyst, Kieran Gilmurray
This article explores how quickly AI capability has accelerated, why most people are still using today’s tools with yesterday’s habits, and what practical shifts matter most as 2026 begins for anyone aiming to Master AI rather than merely experiment with it.
After reading this article, you will understand why AI progress feels invisible until it suddenly feels overwhelming, how tools like ChatGPT have quietly changed under the surface, and what concrete actions matter more than chasing every new model if your goal is to Master AI in real work and decision making.
Introduction: The Year AI Stopped Waiting
It is tempting to treat 2026 as more of the same. You still open ChatGPT. You still mostly use AI for writing or quick answers. The revolution, if it happened, feels oddly quiet. For many, the assumption is that true AI mastery is still some way off.
That feeling is misleading. The problem is not that AI progress slowed down. The problem is that human intuition is terrible at sensing exponential change, especially when the interface stays familiar while the engine underneath is replaced. This is exactly why those who master AI early gain disproportionate advantage.
Why AI Feels Slow Until It Suddenly Is Not
To understand the disconnect, it helps to look backward. The first widely known chatbot model, GPT 1 in 2019, was crude by today’s standards. It had no internet access, no images, no reliable code, and no ability to adapt to a user’s tone or preferences.
At the time, that seemed impressive. In hindsight, it looks almost unusable. The gap between then and now is not incremental improvement. It is a different category of tool, and mastering that category requires different behaviour, not better prompts.
The same pattern appears in image generation. One widely used image generation model progressed through seven major versions between early 2022 and April 2025. In that short window, output quality moved from obvious novelty to images that could plausibly appear in advertising, rewarding those who chose to master the tools rather than dismiss them.
The uncomfortable implication is simple. AI did not creep forward. It sprinted, while most people glanced at it occasionally and assumed nothing fundamental had changed.
Speed as the Defining Feature of the AI Era
The real story of AI is not any single model. It is the speed at which improvement compounds, and the speed at which those who master AI workflows pull ahead.
According to data published by Epoch AI, the pace of AI capability improvement nearly doubled starting in April 2024. Before that point, performance improved at 8.3 points per year. Afterward, the rate jumped to 15.4 points per year, a 1.85x acceleration in a single year. Mastery under these conditions is less about prediction and more about adaptation.
Benchmarks show the same pattern. The MATH benchmark, which tests high level mathematical reasoning, saw accuracy rise from 6.9% in 2021 to 84.3% by 2024 when GPT 4 used code tools. When GPT 5.2 reached 100%, the MATH benchmark itself became obsolete, reinforcing how quickly mastery targets move.
Cost curves reinforce this trend. According to the 2025 AI Index from Stanford HAI, training compute now doubles roughly every five months, while inference costs fell 280 fold between November 2022 and October 2024.
Better, faster, and cheaper is not a slogan. It is the operating environment anyone serious about mastering AI must work within.
The Tool You Are Using Is Not the Tool You Think It Is
One of the most important ideas to internalise for 2026 is that ChatGPT is not a static product. The version you opened in early 2025 is not the one you are using now, even if the interface looks identical. Mastery begins with recognising this shift.
Several foundational changes have already occurred, including reasoning on difficult tasks, memory, projects, web browsing, canvas, and custom GPTs. ChatGPT now reasons before answering on difficult tasks, memory allows it to retain preferences and tone across conversations, and projects enable dedicated workspaces with instructions and files. At the same time, web browsing brings real time information into responses, canvas supports collaborative document editing, and custom GPTs allow task specific assistants. Most users have access to all of this, yet still rely on a single blank chat, delaying real mastery.
Why Prompt Obsession Is the Wrong Focus
Early AI use rewarded clever prompting. In 2022, knowing how to phrase requests felt like a superpower. That knowledge still matters, but it is no longer the bottleneck for those aiming to master AI in practice.
Systems now matter more than sentences. Context engineering, memory, files, and iterative workflows consistently outperform single perfect prompts. Prompt libraries and generators exist precisely because manual prompt crafting is no longer the highest leverage activity for mastery.
This shift mirrors earlier software transitions. Knowing keyboard shortcuts matters, but understanding how to structure work matters more if the goal is to master the tool rather than merely use it.
What AI Progress Curves Actually Suggest
OpenAI has described its internal framework for tracking AI progress in stages. Level one focuses on chatbots that talk. Level two introduces reasoning at advanced levels. Level three adds agents that take actions. Level four focuses on innovation, and level five on organisational autonomy.
The key insight is not the labels. It is the timing. The move from level one to level two has taken roughly three years. The next jump may take closer to twelve months. Mastering AI before that curve steepens again is the real opportunity.
This pattern aligns with the broader idea known as the Law of Accelerating Returns, often associated with Ray Kurzweil. Technological progress compounds, meaning future change happens faster than past change, even when it feels implausible in the moment. Mastery compounds in the same way.
Preparing for 2026 Means Changing Behaviour, Not Predictions
Speculation about future models is entertaining, but it rarely changes outcomes. Action does, especially for those intent on mastery.
One practical shift is to stop expecting AI to produce fully polished outputs in one step. Long form video generation, for example, is still limited to short clips and narrow use cases. Expecting finished five minute videos today leads to frustration rather than leverage, and slows mastery.
Another shift is to stop assuming your style is impossible to replicate. Writing voice, tone, and structure can already be mirrored with high fidelity using tools like Claude when styles are set up deliberately. The barrier is not uniqueness. It is configuration, and configuration is a core mastery skill.
Finally, stop treating AI as a novelty tool and start treating it as infrastructure. Consistent daily use within defined systems compounds skill just as surely as the models themselves improve, accelerating mastery.
Planning Like the Future Is Coming Faster Than You Expect to Master
One of the most useful mental models comes from outside technology. Shohei Ohtani famously used a structured goal matrix as a teenager, breaking an ambitious long term goal into specific habits and traits.
The lesson is not about baseball. It is about planning for non linear growth. Ohtani did not wait to see what happened. He built capacity years in advance, the same mindset required to master AI before it becomes unavoidable.
AI mastery in 2026 follows the same logic. The people who benefit most will not be those chasing every release. They will be the ones who built workflows, habits, and judgement before the curve steepened again.
Conclusion: Use the Curve or Be Used by It
AI progress is not slowing down to match human comfort. Interfaces will stay familiar while capability leaps forward underneath.
The practical choice for 2026 is simple. Either continue using powerful tools as if they were unchanged, or deliberately update how you work to master what they have already become. The advantage will not come from knowing what is next. It will come from mastering what is already here.
Featured Image by ‘Markus Winkler’ on Unsplash
About Kieran Gilmurray:
Kieran is a globally recognized authority on AI, automation, and digital transformation, having authored multiple influential books and hundreds of articles that have earned him prestigious accolades, including being named a Top 50 Global Thought Leader and Influencer on Generative AI in 2024, a Best LinkedIn Influencer for AI and Marketing, Top 50 Global Thought Leaders and Influencers on Manufacturing 2024, Top 14 people to follow in data and one of the World’s Top 200 Business and Technology Innovators.
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Originally posted on 2026-02-26 in the IRPA AI Network — Announcements & Updates