By 2022, IDC predicts that algorithm opacity, decision bias, malicious use of AI, and data regulations will result in doubling of spending on relevant governance and compliance staff and explainability teams in region. Credit: Yeshi Kangrang Today, 8 January, IDC unveiled its top 10 predictions to impact analytics and artificial intelligence (AI) initiatives of Asia Pacific excluding Japan (APEJ) organisations through 2023. The forecast shows an increase in synthetic AI training data, business process redesign, and data/model governance investment and discussion to ensure the sustainability of these technology-driven transformations. Data processing, IT operation automation and AI-enabled user interface (UI) redesign also have a relevant place in these predictions. SUBSCRIBE TO OUR NEWSLETTER From our editors straight to your inbox Get started by entering your email address below. Please enter a valid email address Subscribe By 2022, IDC anticipates that algorithm opacity, decision bias, malicious use of AI, and data regulations will result in doubling of spending on relevant governance and compliance staff and explainability teams in APEJ. “To get beyond isolated proofs of concepts for AI, Asia Pacific organisations need to aggressively develop an enterprise ecosystem that leverages the technology innovations that are now available,” says Dr Chris Marshall, Associate Vice President for Analytics and AI Research at IDC Asia Pacific. According to Dr Marshall, these technology innovations are summarised in the following 10 predictions impacting technology buyers and suppliers in analytics and AI in APAC over the next 48 months. Below are the full predictions: #1: Insight as a Service: By 2022, commoditisation of ever higher layers of analytics and AI technology will result in 15% of the current spend on these items being replaced by spend on insights as a service in APEJ. #2: Process Redesign: By 2023, annual 15% rise in AI-based IT implementation projects automation will drive a new wave of business process redesign, requiring services from firms with deep industry and functional expertise in APEJ. #3: Trust and Governance: By 2022, algorithm opacity, decision bias, malicious use of AI, and data regulations will result in doubling of spending on relevant governance and compliance staff and explainability teams in APEJ. #4: Localised Data Processing: By 2022, reflecting the need for localised data processing and enabled by 5G, 30% of endpoint devices and systems will contain AI algorithms, driving 2/3 of the total annually shipped compute power in APEJ. #5: UI Redesign: By 2023, AI-enabled human computer interfaces and business process automation will replace a third of today’s screen-based B2B and B2C applications in APEJ. #6: Event-Driven Architecture: By 2022, 50% of new spending in analytics will use an event-driven architecture and streaming pipelines to ingest data, process it, evaluate and score predictions, make decisions and initiate actions in APEJ. #7 Multimodel Databases: By 2023, growth in demand for the management of data in multiple formats will cause spending on multi-model databases to represent 25% of the spending on NoSQL databases in APEJ. #8 AI Training Data: By 2023, synthetic AI model training data created using small amounts of actual data and large amounts of simulated data, will be available via data markets, doubling new AI models’ development speed in APEJ. #9 Affective AI: By 2023, effective computing (emotion AI) will include vision and voice technologies and see an increase of 20% in real-world application in APEJ. #10 IT Ops Automation: By year 2022, 75% of IT Operations will be supplanted by AI or analytics-driven automation, resulting in over 25% operating expense (OpEx) savings in APEJ. 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