Task+Tech Fit Check
Free · ~5 minutes
See where AI and technology fit your work, task by task
Like electricity and the internet, AI is a general-purpose technology that will underpin most work. But more AI, or even more technology, isn't always the best way to do a task. This free 5-minute check maps how your recurring tasks compare to leading economic research on the suitability of work tasks for automation, as well as other people doing similar work.
A spectrum of technologies to get work done, from automated to augmented:
You get every task mapped on one spectrum, plus a card like this for each:
How this kind of task looks in the research:
Step 1 of 3 · Your work
What tasks do you mostly do?
Pick your role to start with a list, then make it yours. Keep the 5 to 8 recurring tasks that take the most of your time.
Step 2 of 3 · Task configuration
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Step 3 of 3 · Your Task+Tech Fit snapshot
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How your work compares
Tasks ‘by hand’ are those you indicated are completed with no AI or digital tools.
Blends research on each task's suitability for automation with your answers about how you do it.
AutomatedThe machine delivers to your specifications
AugmentedYou're in the delivery, AI or technology equipped
Task design insights
Task by task
Run this with your team
See the same picture across a team: where the work sits now, where it could sit, and what it depends on people for. Free, and you get a link to share.
The task comparison uses a broad international reference. This is a first-pass self-check: a prompt for where to look. It reads how you described each task, so it reflects your own sense of the work and context.
Sources & method
Everything this tool rests on:
- Task starters
- Based on the Australian Skills Classification (Jobs and Skills Australia, 2021), used under CC BY 4.0 and modified. The ASC is being superseded by the National Skills Taxonomy.
- How-suited band (potential)
- Starts from the Suitability for Machine Learning rubric (Brynjolfsson & Mitchell, 2018), scored over O*NET task descriptions: a broad measure of how automatable/AI-suited a kind of task is.
Because that rubric predates generative AI, this tool then updates it for current capability: where the 2023 LLM-exposure study “GPTs are GPTs” (Eloundou, Manning, Mishkin & Rock; OpenAI) rates a task as more exposed to today’s large language models, its band is raised by one step (never more, and never lowered). So a task like writing or coding, which the 2018 rubric scored low but current AI tools clearly assist, reflects today’s technology rather than 2018’s. Each task records whether its band is from the rubric alone or was uplifted.
O*NET is a database of occupational characteristics and worker requirements maintained by the U.S. Department of Labor, used by international labour organisations including Jobs and Skills Australia. This tool aligns with O*NET but does not stay frozen to task framings that predate current tools. - How-used band (actual usage)
- The Anthropic Economic Index (2025), which maps real AI conversations onto the O*NET task they represent. An evidence-based read of how much AI is actually used on that kind of work. It is distinct from potential.
- How others compare
- “Typical for this role” is a modelled expected profile (reasoned from the research above). Past a size threshold it becomes a descriptive cohort of people who have used this tool in your role, self-selected, not a representative sample of the sector or workforce. Modelled figures are never mixed into Edaith’s grounded research data.
- The two streams
- The automated / augmented split follows the Anthropic Economic Index, which classifies real AI use into automation (directive, feedback) and augmentation (validation, iteration, learning). The degree positions within each stream, and the recommendation, are Edaith’s own model, being validated with practitioners.
- Why a spectrum
- AI is a general-purpose technology, like electricity and the internet, so nearly all work is tech-supported; what varies is the degree. Framing after the GPT / technology-diffusion literature (e.g. Brynjolfsson, Rock & Syverson).
- Kept current
- The suitability and usage bands move as AI capability and real usage move; Edaith refreshes them from the updating sources, and each version is dated.
- The honest claim
- This is a tool to help people better understand how daily work tasks might be reconfigured, and to offer insights that support building the capabilities people need to do well as work and roles keep changing. Even in the same role, the ideal way to deliver a task may vary due to implementation context. Treat it as a conversation starter or reflective tool to inform how you deliver your work and skills development, not an audit.
A free tool by Edaith · Building the essential human skills that help individuals and teams do their best work as AI takes on the routine · edaith.com
This tool is based on the Australian Skills Classification (Jobs and Skills Australia, 2021), CC BY 4.0.
Suitability bands draw on the Suitability for Machine Learning rubric (Brynjolfsson & Mitchell, 2018), updated for current AI with the LLM-exposure study “GPTs are GPTs” (Eloundou et al., 2023), the Anthropic Economic Index (2025) and Edaith's data.
Your tasks, then you
The Fit Check looked at your work. A Capability Profile looks at you: where you stand across every competency in a core professional skill, at your proficiency level, and the one development action with the most leverage for each.
Every profile then includes twelve months on my.edaith, where your Practice Pathway builds your five priority capabilities one at a time, with the specific tool to apply for each.