How it works
Task graphing
Successful AI adoption requires organisations to transform - to design workflows to utilise the different capabilities of AI in the right places, and thereby boost your workforce’s productivity.
But digital transformation is hard, which is why very few organisations have done it successfully before, and why so many will fail to reap the benefits that AI offers.
A successful digital transformation needs to be built on a detailed understanding of the work your organisation does. Arcadia IQ does in weeks what used to take months or years. We consume information on how your organisation really works - what systems are used, how people communicate and through which channels.
The background information gathered allows our structured interview chatbot, Arcadia, to interview your staff and build the task graph for your organisation, by asking detailed questions about the work they do, how they do it and who they work with on each task.
The resulting task graph maps your organisation’s workflows and is the first step in the transformation process.
Analysis of the graph
With the task graph complete, we model opportunities for using AI within your organisation. We think about this in terms of four channels:
Task automation
AI performs a task entirely, removing it from the human workload.
Task augmentation
AI assists with a task, raising quality or speed while the human remains in the loop.
Coordination compression
AI reduces the cost of splitting interdependent tasks across people, enabling tighter specialisation.
Skill-requirement reduction
AI lowers the skill threshold for certain tasks, changing which roles make economic sense.
The first two channels relate to individual tasks and are where many people start when thinking about the impact of AI. Looking across all the tasks in the graph, we can group opportunities up by the AI capability that can be deployed and start to quantify opportunities.
The second two channels are subtler. Given that tasks or coordination becomes easier in some parts of the organisation, how could work be re-organised to take advantage of these improvements?
Risks and opportunities
Introducing AI comes with costs and can introduce material risks. We help you understand these at the opportunity level. While some tools will be used for multiple tasks, the integration costs and the risks associated with that usage can vary in important ways by use case.
We measure each use case along four axes:
- Integration surface: Is this a standalone tool, or does it read from and/or write to systems?
- Engineering depth: Does it work out of the box, need configuring or need building?
- Agency: Is it assisting with a task, or being given permission to do a task?
- Consequence: What happens if something goes wrong?
Tool selection and adoption roadmap
Finally, we work with you to bring it all together into a roadmap for your AI adoption - tools, timelines, and strategies. Navigating adoption successfully could mean the difference between enjoying the gains of the AI era, and falling behind competitors and new entrants that have been able to take advantage of the productivity gains that AI offers.
| Tool | Time saved | Addressable | Integration | Engineering | Agency | Consequence |
|---|---|---|---|---|---|---|
| Writing & drafting assistant | 44h | 100h | ||||
| Data analysis & charts assistant | 20h | 45h | ||||
| Knowledge & self-serve info | 18h | 25h | ||||
| Meeting assistant | 13h | 44h | ||||
| Status & alignment hub | 13h | 32h | ||||
| Record-keeping automation | 11h | 21h | ||||
| Workflow / handoff automation | 10h | 20h | ||||
| Coordination & project-tracking tool | 8h | 22h | ||||
| Review & quality-check assistant | 8h | 27h | ||||
| Knowledge-lookup assistant | 7h | 19h | ||||
| Other | 5h | 13h |
Integration: Self-contained · Connected (read) · Connected (read/write)
Engineering: Switch-on · Configured · Engineered
Agency: Advisory · Acts w/ approval · Autonomous
Consequence: Low · Moderate · High.
Hover a tool name for the suggested product.
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