Am I Behind on AI? [2026 Survey]

If you are wondering "am I behind on AI," you are not alone, and the answer depends on who you compare yourself to. AISA asked 98 people starting the AI fluency assessment how their colleagues would describe their AI usage. The largest single group, 27.6%, said "about average." But nearly half placed themselves ahead: 23.5% chose "ahead of most" and 25.5% said they are the person everyone asks for help. Meanwhile, 23.4% placed themselves behind, choosing either "behind the curve" (7.1%) or "what's AI?" (16.3%). The spread is wide, and wherever you sit, there is a concrete way to find out for certain.

1. What's AI?16.3%16
2. Behind the curve7.1%7
3. About average27.6%27
4. Ahead of most23.5%23
5. The one everyone asks for help25.5%25

98 people answered, 14 August to 20 August 2026. Source: AISA research, aisa.to

Am I Behind on AI Compared to My Colleagues?

Most people do not think they are behind. When AISA posed the question "How would your colleagues describe your AI usage?" to 98 people, 76.6% placed themselves at average or above. Only 7.1% chose "behind the curve," and 16.3% selected "what's AI?" That means roughly three in four people believe their colleagues would see them as keeping pace or leading.

The gap between perception and reality

Self-assessment is notoriously unreliable when it comes to new skills. AISA's own research has shown that students overestimate their AI skills by 32 points on average. The same dynamic plays out in workplaces: people anchor on the one or two AI tasks they do well and assume that covers the full picture. What feels like "about average" might mean you use ChatGPT for email drafts but have never touched task decomposition, prompt chaining, or output verification.

Why the question matters right now

The stakes are rising. According to the Microsoft and LinkedIn Work Trend Index (May 2024), 66% of leaders say they would not hire someone without AI skills. Feeling behind on AI is not just an emotional state; it can have real career consequences. And yet, BCG's AI at Work 2025 report (over 10,600 workers in 11 countries) found that only 36% of employees feel adequately trained in AI use. The gap between what employers expect and what workers feel prepared for is significant.

How Do Most People Say Colleagues See Their AI Use?

The most common answer is "about average," chosen by 27.6% of the 98 people AISA asked. But the distribution does not cluster tightly around the middle. The two above-average options together account for 49.0%, while the two below-average options total 23.4%.

The confident half

Nearly half of respondents see themselves as ahead. That 49.0% combined figure for "ahead of most" and "the one everyone asks for help" is striking. It suggests that a large share of people who seek out an AI assessment already have some confidence in their abilities. If you are reading this post and worrying you are the only one not using AI, the data says you are not: 23.4% of people placed themselves in the lower two categories.

The uncertain middle

The 27.6% who chose "about average" occupy an interesting position. They are not worried enough to say they are behind, but they are not confident enough to claim they are ahead. This middle group often has the most to gain from a structured assessment, because "average" is a moving target. What counted as average AI usage six months ago may now be below the bar. Understanding where you stand on specific dimensions like prompting, critical thinking with AI, and workflow application matters more than a single label.

How Many People Are Their Team's Go-To for AI?

One in four, exactly 25.5%, said their colleagues would describe them as "the one everyone asks for help." That is the second-largest group in the data, just behind "about average."

What being the go-to person actually involves

Being the person everyone asks for help with AI typically means more than just knowing which tool to open. It usually involves understanding how to frame problems for AI, knowing when AI output needs verification, and being able to teach others. In AISA's framework, this maps across multiple dimensions: Prompting & Communication, Workflow & Application, and Critical Thinking. The AI fluency concept captures this breadth. Someone who scores well on prompting but poorly on critical evaluation is not truly the go-to person; they are just the fastest typist.

The responsibility that comes with it

If you are the AI person on your team, you are also the one setting norms. Your habits around source triangulation, data privacy, and output checking become the team's habits. That is a significant responsibility, and it is worth knowing whether your instincts are actually sound or just confident. Leaders who want to understand how their teams stack up can explore AI fluency benchmarks by persona to see what different skill profiles look like in practice.

What Does "About Average" with AI Look Like?

Being "about average" with AI means you use it, but not systematically. The 27.6% who chose this option likely have a handful of AI habits: drafting emails, summarising documents, maybe generating code snippets. What they probably lack is a structured approach to when and how to use AI across their work.

The average is shifting fast

The definition of average AI usage is not static. A year ago, knowing how to write a basic prompt was ahead of the curve. Now, with 66% of leaders saying they would not hire someone without AI skills (Microsoft and LinkedIn, May 2024), basic prompting is table stakes. Average increasingly means you can integrate AI into real workflows, not just use it for one-off tasks.

Moving from average to ahead

The gap between "about average" and "ahead of most" is often not about raw intelligence or technical background. It is about deliberate practice in specific areas. The table below maps each self-reported level to a practical next step:

What If Your Colleagues Would Say You Are Behind?

If you identify with the 7.1% who chose "behind the curve" or the 16.3% who chose "what's AI?," the most important thing to know is that this is a solvable problem. AI fluency is a skill set, not a talent. It can be learned.

Being behind is more common than it feels

The 23.4% who placed themselves in the lower two categories represent a real share of people. And remember, only 36% of employees across 11 countries feel adequately trained in AI use, according to BCG's June 2025 research. Feeling behind on AI is not a personal failing; it reflects a training gap that most organisations have not yet closed.

The advantage of knowing where you stand

Paradoxically, the people who worry most about being behind often have an advantage: they are motivated to learn. The risk is not in being behind; it is in staying there without a plan. A measured assessment gives you a specific starting point. Instead of a vague sense of "I should probably learn AI," you get a breakdown across dimensions like prompting, critical thinking, technical understanding, workflow application, and responsible use. That specificity turns anxiety into a checklist.

If you are managing a team and suspect the spread looks similar to what AISA found, understanding the AI maturity model can help you think about where your organisation sits and what the next stage looks like.

How Do You Find Out Where You Really Stand?

Self-assessment gives you a rough sense, but it is not reliable enough to act on. The data from AISA's question shows that people spread themselves across the full range, and we know from other AISA research that self-estimates can be significantly off. The only way to know where you actually stand is to measure it.

What a good AI skills measurement looks like

A useful assessment does more than give you a single number. It should break your skills into specific, actionable dimensions. AISA's assessment covers 11 criteria across 5 dimensions, with evidence-linked scoring against a published rubric. Every score is tied to something you actually said or demonstrated, not a multiple-choice guess. The result is a detailed report and certificate you can use immediately.

From score to action

Once you have a measured score, the path forward becomes concrete. If your prompting is strong but your critical thinking is weak, you know exactly where to focus. If your technical understanding is solid but your workflow application lags, you can target that gap. The how often people use AI at work data from AISA's research shows that usage frequency varies widely, and frequency alone does not equal fluency.

Whether you think your colleagues would call you "the one everyone asks for help" or "behind the curve," the question is the same: is that perception accurate? Take the AI fluency assessment to find out where you actually stand, with a score you can trust and a report that tells you exactly what to work on next.

About this research

This finding comes from AISA's own research. AISA asks a short research question of people as they start the AISA AI fluency assessment, one question at a time. The question in the chart above was asked from 14 August to 20 August 2026, worded exactly as shown and with the answers in the order shown, and 98 people answered it. Each person counts once: when someone answered more than once, their latest answer is the one counted.

More findings from this research are collected in AISA research and data.

How to cite this research: AISA (2026). "Am I Behind on AI? [2026 Survey]". AISA research. https://aisa.to/blog/am-i-behind-on-ai

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Related reading: How to Improve AI Skills: 7 Steps [2026], a practical guide to closing the gaps your score reveals.

Related reading: How Often Do People Use AI at Work? [2026], AISA research on actual AI usage frequency.

Related reading: AI Maturity Model: 5 Stages & the People Layer, where your team sits and what the next stage requires.

Frequently Asked Questions

How do I know if I am behind on AI?

The clearest way to know is to measure your skills against a structured framework rather than relying on gut feeling. AISA's research shows that self-perception varies widely: 23.4% of people placed themselves below average while 49.0% said they are ahead. A scored AI fluency assessment gives you a specific breakdown across prompting, critical thinking, technical understanding, workflow application, and responsible use, so you know exactly where you stand.

Is everyone at work better at AI than me?

Almost certainly not. When AISA asked 98 people how colleagues would describe their AI usage, 16.3% chose "what's AI?" and 7.1% said "behind the curve." Meanwhile, BCG found that only 36% of employees across 11 countries feel adequately trained in AI. The feeling that everyone else is ahead is common but rarely accurate.

How can I catch up on AI skills?

Start by identifying your specific gaps rather than trying to learn everything at once. A measured assessment breaks your AI fluency into distinct dimensions so you can prioritise. From there, focus on one area at a time: prompting skills if you struggle to get useful output, critical thinking with AI if you are not sure when to trust what AI gives you, or workflow application if you only use AI for isolated tasks.