IDC predicts that by 2026, 30 per cent of AI models in Asia/Pacific would use several data modalities to increase learning effectiveness.

AI models in the Asia/Pacific region will use multiple modalities of data to improve effectiveness and address knowledge gaps.

FREMONT, CA: According to IDC, by 2026, 30 per cent of AI models will use several modalities of data to enhance learning efficiency and overcome the existing deficiencies in single-modality AI solutions related to general knowledge. The study IDC FutureScape: Global Artificial Intelligence and Automation 2023 Forecasts—Asia/Pacific (Excluding Japan) Implications has several predictions.

Due to the pandemic, the market dynamics in the APAC region have changed, compelling organisations to adopt a disciplined approach to scaling AI initiatives and driving better business outcomes. To fully realise the potential of AI in the region, there is a need for more focused business use cases and a stronger data ecosystem. Multimodal AI, which combines various types of data, such as images, text, speech, and numerical data, with multiple processing algorithms, can bridge the gap between human and computer intelligence and achieve superior performance.

AI systems are increasingly utilising multiple data sources, and multimodal AI is proving to be more effective than single-modal AI in providing precise outcomes across various applications. Instead of investing in significant transformation programs, organisations are focusing on maximising returns from their existing technology investments. AI is being used to enhance employee productivity, optimise supply chains, and improve customer experience.

The research paper outlines the ten most significant forecasts for Artificial Intelligence (AI) and automation initiatives until 2028. The impact of each prediction is evaluated based on the cost and complexity involved in implementing it. The time frame for each forecast to reach the anticipated adoption level is also analysed. Additionally, the paper provides insights into the impact of these predictions on IT and offers guidance for technology buyers on each prediction's implications.

The following 10 predictions represent the expected trends with potential impact on AI and automation initiatives.

1: Talent Gap: More than half of IT organisations will invest in AI skills by 2023 due to persistent talent shortages. These investments will be aimed at running automated IT operations and supporting business end-users in adopting AI and automation solutions.

2: Embedded AI: AI-drive features will be embedded across business technology categories by 2026, and without relying on technical talent AI talent 65 per cent of organisations will actively use such features to achieve better outcomes.

3: AI for Risk Management: Until 2026, as AI models become more strategic, modern risk and governance will demand more attention from businesses. About 60 per cent of CFOs of 2000 Asia-based organisations  will include AI risks in their enterprise risk programs.

4: Low-Code/No-Code Adoption Accelerates: In 2023, it is expected that a significant number of organisations will utilise development tools that do not require coding for approximately 30 per cent of their automation and artificial intelligence (AI) projects. This approach is anticipated to aid in the expansion of digital transformation efforts and make AI more accessible to a wider range of individuals

5: Foundation Models: The use of foundation models with over one trillion parameters, for applications such as natural language processing [NLP] and AI-generated images, will be commonplace by 2026 and only the largest vendors will be able to provide them as standard industry utilities.

6: Multimodal AI: By 2026, more than 30 per cent of AI models will utilise multiple data modalities to enhance learning effectiveness and overcome the current limitations of single-modality AI solutions in addressing everyday knowledge gaps.

7: AI/ML as the Big Flip: The componentization of applications and advancements in AI/ML will lead to 25 per cent of companies having applications assembled by AI by 2027, which will disrupt traditional developer roles.

8: Multimodal Collaborative Automation Platforms: By 2025, around 30 per cent of organisations will embrace intelligent business execution strategies to accelerate the development of automation and maximise benefits by leveraging AI throughout the entire automation life cycle.

9: AI-infused Operations: By 2026, a majority of large enterprises in the Asia/Pacific region, approximately 75 per cent will use processes infused with AI to improve the efficiency of their assets, streamline supply chains, and enhance product quality in diverse and distributed environments.

10: Sustainable AI: By 2024, approximately 25 per cent of organisations will implement tools to measure, forecast, and optimise the cost-benefit of their AI life cycle in response to concerns regarding sustainability and economic uncertainty.

There will be a significant shift towards using multiple modalities of data in AI models in the Asia/Pacific region. This approach is expected to improve the effectiveness of AI learning and overcome the limitations of single-modality AI solutions in addressing knowledge gaps.