Can technology better support your work?

Almost all work is now supported by technology — the real question isn't if, but how. Whether it be digital platforms, process automation or generative capabilities of AI technologies, work has long been an endeavour enabled and supported by machines.

This tool shows how your task configuration compares to leading economic research on the suitability of work tasks for automation, as well as other people doing similar work.

Two streams: A spectrum of technologies to get work done

Automated

The machine delivers to your specifications.

Hands-off · Overseen

Augmented

You're in the delivery, equipped with AI and digital tools.

You revise · Co-created · You deliver

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 5–8 recurring tasks that take the most of your time.

Your role

Step 2 of 3 · Task configuration

Task 1

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Almost there · Your snapshot is ready

Where should we send it?

Your snapshot opens on the next screen. Add your email to keep a copy.

Step 3 of 3 · Your Task+Tech Fit snapshot

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How your work compares

AutomatedThe machine delivers to your specifications

Hands-off — runs to your specifications; you check in occasionally.

Overseen — a technology or AI does it; you verify or steer.

AugmentedYou're in the delivery, AI or technology equipped

AI-led — AI does the bulk; you check and revise.

Co-created — you and AI build it back-and-forth.

You deliver, tech-equipped — you deliver (often in person), supported by current technologies and tools.

◄ More automatedMore personal ►

How your tasks run now

Tasks ‘by hand’ are those you indicated are completed with no AI or digital tools.

Where they could sit

Based on the Suitability for Machine Learning rubric, scored over O*NET task descriptions.

Task design insights

How each of your tasks relate to benchmarks.

Opportunity · could lean more on tech

Waste · potential heavier AI use than needed

Risk · may be too automated for the judgement

Working as is

Task by task

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. The task comparison uses a broad international reference.

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): 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.

O*NET is a database of occupational characteristics and worker requirements information across the U.S. economy regularly updated by the U.S. Department of Labor. It is a key benchmark used by international labour organisations including Jobs and Skills Australia and broadly in economic research.
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 provide insights to navigate task redesign for individual roles. 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 · Guides and self-assessments for the key human capabilities 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), the Anthropic Economic Index (2025) and Edaith's data.