Asia-Pacific has embraced AI and is on track to one single goal—leadership. The region likely recognizes the benefit of pouring heart, soul, and investment into making world-changing artificial intelligence. The response has been overwhelming. Here is what we’re expecting from AI in APAC in the coming years.
More funding means more breakthroughs
According to research from IDC, the spending on AI in APAC will almost double by 2025. This investment comes from the banking industry first, where funding for better AI programs will help reduce fraud and mitigate risk. This could put the region into a leading position as global firms decide where to shift their own spending.
Following banking, governments are investing heavily in AI to transform how citizens receive and interact with public services. State and local governments are increasing spending on emergency deployment as well. Business closely follows the government. Industries are making serious investments in customer service applications, mirroring the government’s focus on creating quality, convenient access to services.
APAC is setting the foundation for the next era of technology. Here, businesses and governments leverage AI to create powerful, seamless experiences for citizens and customers. This, combined with investments from finance industries to lower risk, could incentivize even more international businesses to start looking at the region with possibility.
Focused, strategic initiatives lay the foundation
A 2021 study from Cognizant demonstrated the commitment APAC region businesses showed in the wake of pandemic disruption. A majority—and a higher percentage than both Europe and the Americas—of the study’s respondents stated that AI is a vital piece of their future. Although broad adoption is still at an early stage, they’re taking strategic steps towards deployment.
Businesses in the region believe in taking a holistic approach, with the end goal being a total transformation of business operations. Leaders in AI can help guide their counterparts through this transformation. The gains from implementation are already starting to show in overall worker productivity and customer satisfaction.
While the infrastructure side is still in the works, the region is beginning to pour resources into building better internet access for citizens and ensuring that data moves more freely. Once this happens, AI deployments should take off even more strongly than now.
Internal initiatives remain a priority
IDC also predicts that pandemic disruption has increased APAC businesses’ interest in expanding data initiatives beyond the enterprise. AI shines in the realm of big data. Freeing data between an industry ecosystem is a massive boost to what AI can do for the region.
Some IDC predictions for the coming years that will have the most significant effect on AI:
- Increased focus on streaming data: By 2025, 40% of spending on data capture will focus on streaming data pipelines. When AI has access to high-quality, real-time data, companies will be able to leverage it for DataOps across the board.
- Increased willingness to share data: By 2025, 40% of companies will form data-sharing partnerships with external companies. These partnerships could also accelerate AI deployment throughout the business as companies find pathways for data-hungry applications.
- Intelligent document processing: One of the only explicit AI predictions in the document—by 2026, 70% of companies are predicted to digitize documents and actively leverage AI processing to glean insights from them.
- Video content could be a significant catalyst: The report predicted that while a majority of businesses would use video in a majority of employee and customer interactions, far fewer would apply video analysis to interpretative decision-making. This could mark a significant opportunity for developers as they sense a need for better, easier-to-use tools.
Some examples of current initiatives
Here are some things companies are doing right now to further AI in the region:
- Singapore has launched two national AI initiatives designed to encourage further adoption and scale in the finance industry and the public sector. They’ve provided 180 million in funding so far.
- Japan has launched the Advanced Integrated Intelligence Program platform. It’s designed to bring together researchers to promote R&D and innovation. Current spending sits at around 50 million to 100 million yen.
- China’s new AI governance initiatives have the potential to shape not only how algorithms are regulated within the country but around the globe. International researchers and developers are watching closely to see how these regulations play out.
- The Australian Government has pledged $124.1 million to strengthen AI in the country with its Artificial Intelligence Action Plan. The initiative includes several action prongs, such as educating a future AI workforce and catalyzing opportunities regionally.
- Pakistan has launched a presidential initiative to reach and train future leaders in AI—the Presidential Initiative for Artificial Intelligence and Computing. The goal is to increase Pakistan’s standing in the technology world and offer easier access for students to break into the field.
- According to research from the Brookings Institute, the country of India is among the top ten nations in the world for AI adoption. The nation joins technology heavy-hitters the US, China, Japan, and France on the list.
This list is not exhaustive of what the region is accomplishing in AI development and deployment. Because the focus on AI continues to grow, the region remains a critical one to watch as AI continues to revolutionize our world.
Learn more about AI in APAC at ODSC APAC 2022
Coming virtually this September 7th-8th, ODSC APAC will showcase everything trending in AI and data science, specifically around the APAC region. At this virtual event, you’ll have the chance to hear talks from some of the leading experts in data science and AI in the region, and even attend virtual training sessions with hands-on instruction on in-demand topics. Some highlighted training sessions include:
- Route Optimization using Reinforcement Learning and Metaheuristics
- Interpretable AI : Making Black Box Models Explainable
- Use of Transfer Learning in Computer Vision
- Key Design Principles for the Modern Data Engineering Stack
- Advanced NLP: Deep Learning and Transfer Learning for Natural Language Processing
- Microsoft’s Accelerator for MLOps