User Adoption is the ability to integrate a new product, system or solution into existing processes and ways of working leading up to the creation of new value streams. What does adoption look like? People are not executing a task in a system, they are “collaborating” with the technology to do things differently.
Why is User Adoption hard? The more complex technology is, the more resistance will be displayed by users. Why? Because people have limited attention and willpower and rely on shortcuts, i.e. heuristics and biases, to “get the job done”.
The HumanTech approach puts people and behaviors at the center of adoption design. Whether it’s for organizational design, technology adoption, or articulating a service offering meaningfully.
There are three core components to creating HumanTech adoption strategies:
We seek information that supports our existing beliefs and ignore what doesn’t
Users are more inclined to use an AI-generated output when it confirms their preexisting beliefs.
We fixate on initial impressions and experiences, which affects our judgment of everything after that.
When an initial experience is positive, we significantly increase the likelihood of adoption, while a negative first encounter discourages it.
We pay a disproportionately higher value on something we’ve helped to create.
Allowing users to be involved in creating a product leads to a powerful emotional connection and drives adoption.
We tend to stick with our previous choices, even if the alternatives might be better.
Status Quo hinders the adoption of new technologies that are not perceived as needed: if it’s not broken, why fix it?
We hate losing more than we like gaining.
Avoiding loss impacts our decision-making, attitude toward risk, and ability to explore new things.
We’re unable to let go of past bad investments, even if it makes sense to do so.
When we’ve invested time and money in building our own tools (spreadsheets, anyone?), we find it hard to accept the lost effort and move on to better tools.
Pattern of interactions that link technology, tasks, and human components to achieve organizational goals.
Data and Analytics tools often fail to accelerate decision-making in a matrix-structured organization.
How individuals make decisions and process information.
When facing identical AI inputs, individuals make entirely different choices based on their own decision-making style.
The collective values, beliefs, attitudes, and behaviors.
Artificial Intelligence-powered tools are often underutilized in an organizational culture that values consensus-building.
Whether it’s looking for help with a design workshop, developing an adoption strategy, or looking for inspiration through a speaking engagement we’d love to partner with you.
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