New Study Debunks Five Common Myths Holding Enterprises Back From AI Success
- Recognized AI expert and industry analyst to share insights and recommendations for operationalizing artificial intelligence in upcoming webinar
InRule Technology, provider of the leading decision platform for automating mission-critical business decisions, announced the availability of a new commissioned research study conducted by Forrester Consulting on behalf of InRule that explores key myths related to effective artificial intelligence implementation that permeate today’s enterprises.
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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 artificial intelligence decision-makers see operationalizing artificial intelligence 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.
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To evaluate the commonly held myths that prevent enterprises from successfully operationalizing artificial intelligence, Forrester conducted an online survey of 302 U.S.-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 artificial intelligence 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, “artificial intelligence is a critical source of industry competitiveness. The fastest path to artificial intelligence solutions is to formulate and execute a strategy to scale artificial intelligence use cases based on reality unencumbered by myths.”