ai & Automation use cases for knowledge workers
Remote testing, technology, automation, ai, international study
Project lead, Moderator, report writer
Bold insight
CHALLENGES
A global technology company sought to understand how enterprise users conceptualize and approach building automations and implementing AI, and whether their mental models were influenced by region or tool of choice.
"How might we explore what users automate and their mental models around ai and automation, and how can we use that knowledge to improve and differentiate ourselves from the competition?"
Process
Our team conducted 90-minute remote 1:1 in-depth interviews via video conferencing tool. We recruited 23 participants across three markets - US, Indonesia, and Brazil., with an approximately even spread across markets and tools used.
All of our participants had some direct experience with creating automations with the client's tool as well as its top two competitors, but it is important to note that most were individual contributors who had somewhat limited impact on company-wide, cross-functional implementation and adoption of automation and AI tools.
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During the remote interviews, participants were asked questions around their proficiency with automation and AI, as well as additional exploratory questions around their building process, desired features, as well as needs and expectations around testing capabilities, templates, and customization.
analysis & outcomes
Our analysis of participant feedback indicated regional differences in participants' motivation for using automation and AI, as well as their sophistication with various automation and AI tools. However, there was limited evidence that any one tool used impacted our participants' mental models around AI and automation.
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Participants in the study did not give detailed accounts of their automation building processes due to concerns with sharing company-proprietary information, but anecdotal evidence suggests that context and the type of automation being built mattered more than which tool they used to build it.
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Participants in Indonesia discovered the capabilities of automation tools anecdotally through friends, colleagues, social media and Google searches. They saw the benefit of AI and automation tools as having a "smart assistant" who could help them with personal productivity. Many relied on YouTube videos to guide them through building simple automations with existing templates.
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Participants in Brazil had a broader appreciation for the benefits that AI and automation tools could bring to help the efficiency and effectiveness of their work. Brazilian participants considered being skilled in AI and building automations to be a competitive differentiator that could help them strengthen their professional experience, which lead to recognition and promotion in the workplace.
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US participants considered AI and automation as a way to complete mundane tasks so that they could more quickly get to the higher-value analytical work. More of the US participants ' use cases involved data transfer between systems, in service of creating complete records for better business intelligence or assigning work requests.
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We were able to distill our insights and findings into six main recommendations:
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Improve the SEO of the client's tool and tutorial content in markets outside of the US to help capture early automation adopters in Indonesia and Brazil.
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Create greater discoverability of the client's tool by highlighting content, templates and tutorials.
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Ensure connection to other enterprise ecosystems that users regularly use to collaborate with their teams.
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Incorporate prioritization and triaging features into existing automation capabilities to manage workflows.
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Make simple automations accessible for those new to automation tools and AI.
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Optimize sales and lead management with automated aggregation features to activate business intelligence.
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Our client implemented these recommendations into the most recent iteration of their automation and AI tool, which went live for its users in April 2025