The biggest obstacles to technology adoption often are not technical. This is especially true for organizations considering use of artificial intelligence / machine learning (AI / ML) in enterprise performance management (EPM) software.
Our data show that the majority of EPM users either will resist adoption of AI / ML models in EPM solution due to its hard-to-explain (“black-box”) nature, or fail to see how AI / ML would improve EPM processes sufficiently to justify its deployment and use.
With these perceptions, organizations that try to deploy AI / ML in EPM without first developing and communicating a business case for it likely will fail to reach intended goals, and likely will encounter significant obstacles to its adoption and regular use.
By collaboratively creating and socializing a business case for AI / ML in EPM—long before establishing any schedule for deployment—data leaders can proactively address the skepticism and eliminate potential obstacles to future adoption and use. When the business case results from a collaborative process, the project or program generally becomes more easily accepted and implemented because key stakeholders view themselves as involved and included, rather than uninvolved and overlooked.
You do not have permission to access this document. Make sure you are logged in and/or please contact Danielle with further questions.