target audience: TECH BUYER Publication date: Dec 2023 - Document type: Tech Buyer Presentation - Doc Document number: # AP51033823
IDC FutureScape: Worldwide Intelligent ERP 2024 Predictions — Asia/Pacific (Excluding Japan) Implications
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Abstract
This IDC Presentation assesses each of the predictions discussed on its complexity, organizational impact, and time frame expected for mainstream adoption in Asia/Pacific (excluding Japan) (APEJ). Equally important, lead analyst provides advice to technology buyers and business decision makers in their planning for a range of decision-support and decision-automation initiatives enabled by intelligent systems. The key drivers affecting IT and business decision makers as they develop or revise their strategies and create plans for resource allocation for 2024 and beyond are also outlined in detail.
IDC describes intelligent enterprise resource planning (iERP) and all associated intelligent enterprise applications as those that use ML, AI, and advanced analytics built on a large, curated data set to track, learn, route, analyze, predict, report, forecast, and manage enterprise assets and business processes. iERP and intelligent enterprise applications feature an assistive and conversational user experience (UX) and free users' time for higher-value tasks by automating high-volume repeatable tasks and augmenting the performance of novel tasks, which are infrequent, via human-machine interaction. AI and generative AI (GenAI) adoption is a critical lever for organizations to accelerate business insights –— AI using sophisticated algorithms to process large volumes of data and recognize patterns has the potential to deliver a step change in extracting value from operational data while GenAI produces text in the form of answers and recommendations to users based on the data they are trained on.
iERP and intelligent enterprise applications are capable of processing, analyzing, and acting on massive volumes of data in real time using in-memory computing (IMC). These technologies are systems that learn, thus allowing for ongoing reconfiguration to enable process refinements and UX adaptation.