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AI progress can stall when end users resist adoption. Developers must think beyond a project’s business benefits and ensure that end users’ workflow concerns are addressed.
Some of the biggest challenges in AI implementation can arise when a tool is ready to roll out to end users — and those users resist adoption. That’s typically because the project’s business sponsors are not the people expected to use the tool — and they have failed to address the needs and priorities of end users.
However, research by Kate Kellogg, Mark Sendak, and Suresh Balu finds that when developers address end users’ concerns about workflow and autonomy, they can reconcile conflicting stakeholder interests and ensure ready adoption of AI tools.
In this webinar, you will learn:
- How end-user resistance stems from three main conflicts of interest between AI project sponsors and the individuals meant to use the decision support tool.
- Why it’s critical to make space for end-user autonomy in new, AI-augmented processes.
- Proven ways for AI project leaders to better understand the end-user perspective so that new tools address their workflow challenges rather than solving only other stakeholders’ business problems.
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