Recognized AI expert and industry analyst to share insights and recommendations for operationalizing AI in upcoming webinar
CHICAGO – InRule Technology®, provider of the leading decision platform for automating mission-critical business decisions, today announced the availability of a new commissioned research study conducted by Forrester Consulting on behalf of InRule that explores key myths related to effective AI implementation that permeate today’s enterprises.
According to the study, 67% of decision-makers expect their AI/ML use cases to increase at least slightly over the next 18 to 24 months. However, silos, data challenges and a lack of resources stand in the way. Forrester found that AI decision-makers see operationalizing AI as critical to gaining essential insights about customers and markets to improve business outcomes.
Forrester Vice President and Principal Analyst Mike Gualtieri will join InRule as a guest speaker for a webinar that will explore the research findings and present recommendations for how to overcome the myths that hold enterprises back from AI success. Register for the June 24 webinar here.
To evaluate the commonly held myths that prevent enterprises from successfully operationalizing AI, Forrester conducted an online survey of 302 US-based application development and delivery decision-makers, as well as three, in-depth live interviews. The research also evaluated how firms could change their perceptions of these myths in order to operationalize AI faster and more effectively.
Key findings identified top challenges including:
- Data overload: More than half of decision-makers surveyed say their organizations have too much data to make collaboration efficient, hindering AI project success.
- The “black box” problem is real: 64% of decision-makers indicated that it is “critical” or “important” for their organization to defend or prove the efficacy of its digital decisions. However, nearly 60% said it is challenging to do so.
- Set it and forget it: Almost one in three organizations surveyed do not routinely monitor and retrain their machine learning models to ensure peak performance.
The research yielded five key recommendations that companies should consider in order to expedite AI success. According to the study, “AI is a critical source of industry competitiveness. The fastest path to AI solutions is to formulate and execute a strategy to scale AI use cases based on reality unencumbered by myths.”
Download the full thought leadership paper and study results here.