Advancements in Artificial Intelligence (AI) and automation are fronted by new technologies and higher quality data, and the capabilities of such tools to produce meaningful output are growing accordingly, too.
Organizations had previously compartmentalised these tools for specific business operations such as IT and cybersecurity, but advancements in AI and automation have enabled them to be utilized more commonly across horizontal business functions.
Strategic planning, decision making, and problem-solving, as well as other functions that were conventionally reliant on human labour (and thus subjected to fatigue and error), are reaping the benefits of leveraging on AI.
When human expertise consults AI and ML technologies to monitor, analyse, and customize machine-led processes, AI-powered recommendations can reduce unplanned downtime, increase efficiencies in planning and strategizing, more accurately detect potential roadblocks, make better predictions and decision-making.
In addition to addressing current states of business, AI technology has the potential to identify new business opportunities. To meet the demands of organizations, more vendors are creating single unified platforms that combine diverse types of automation technologies that support line-of-business digital enablement programs.
While AI use cases and projects are increasingly commonplace in the business markets as organizations begin to recognise the advantages AI and automation technologies can offer, AI utilization and regulation vary in different parts of the world.
The European Union (EU) is developing regulations to control the use of AI, while Asia has yet to perceive it as a public issue. Asia Pacific (excluding Japan) views them as strategic opportunities rather than ethical issues and has heavily invested to improve competencies and position them well in the global market.
“AI is rapidly outgrowing its preliminary notion as the add-on service to business practices and coming on strong as a game-changer in the way organizations can leverage on the technology. Its successful adoption requires a mammoth transformation of not only the organization but its employees, balanced with capabilities to secure increasingly complex datapaths,” said Christopher Lee Marshall, associate vice president for IDC Asia Pacific.
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IDC’s 2022 predictions for AI in APEJ
Prediction 1: Regulation trajectory and impact: By 2025, the emergence of distinct AI regulations in Europe, United States, and Asia will encourage regional AI solutions and capabilities but delay and complicate AI rollouts for 20% of A2000 firms.
Prediction 2: Machine-human augmented foresight: By 2026, 90% of enterprises in APEJ will combine human expertise with AI, ML, NLP, and pattern recognition to augment foresight across the organization, making workers 30% more productive and effective.
Prediction 3: Automation platform consolidation: By 2024, 60% of A2000 investments in business automation will be for multimodal codeless automation platforms that support digital enablement by both professional developers and business users.
Prediction 4: Breadth of horizontal use cases: By 2024, 70% of A2000 will expand the use of AI/ML across all business-critical horizontal functions like marketing, legal, HR, procurement, and supply chain logistics.
Prediction 5: Process mining control plane: The 35% of APEJ enterprises that adopt process mining as a controlling layer for end-to-end business processes by 2023 will be at least 20% more profitable than peers that do not.
Prediction 6: MLOps to AIOps: By 2024, 50% of APEJ enterprises will have operationalized their ML workflows through MLOps/ModelOps capabilities and AI-infused their IT infrastructure operations through AIOps capabilities.
Prediction 7: Continuous innovation with conversational AI: By 2022, 60% of the A2000 will have deployed conversational AI applications in a wide range of use cases in multiple languages, with 20% based on advanced language models such as BERT and GPT-3.
Prediction 8: Climate risk AI: By 2027, 30% of the A2000 organizations will invest in neural networks-powered climate hazard assessment, adaptation, and identification of opportunities, driving 25% profit growth.
Prediction 9: Technology wave cloud-edge: In 2025, nearly 10% of IoT systems in APEJ will support AI, compared with nearly 30% of edge infrastructure systems, over 45% of datacentre systems, and nearly 90% of IT (phone/tablet/PC) client systems.
Prediction 10: Commoditization of computer vision: By 2024, 75% of APEJ companies using their computer vision will use a pretrained model in a low-code environment that either fits their need or can be adopted with transfer learning from sparse data sets.
