Confluent: data-related challenges are holding back AI adoption in Singapore

New research from Confluent, the data streaming provider, has found that data-related challenges are holding back AI adoption in Singapore. Nearly seven in 10 (69%) IT leaders in Singapore believe that investments in generative AI (gen AI) will trend up in the next two years, but AI rollouts have been slowed by businesses’ inability to seamlessly integrate new data sources (69%), fragmented ownership of data (68%), and insufficient skills and expertise in AI/ML management (65%).

In facing these challenges, leaders in Singapore are on par with their peers across the Asia Pacific region (APAC), Confluent said. For instance, businesses’ inability to seamlessly integrate new data sources is a challenge for 66% leaders in the region, while 68% also struggle with fragmented ownership of data across disparate systems and 66% are troubled by insufficient skills and expertise.

The findings are from the 2024 Data Streaming Report: Breaking Down the Barriers to Business Agility & Innovation*, which dives into how organisations use data streaming to innovate, accelerate AI adoption, improve business agility, power customer experiences, and overcome data accessibility and management challenges. The report is based on a survey of 4,110 IT leaders with experience of data streaming across 12 countries, including Singapore (161 respondents) and APAC (1,424 respondents).

Suvig Sharma, Area VP, ASEAN, Confluent, said: “Companies in Singapore are limiting their growth and performance if they invest in AI but not real- time data. Relevant real-time data is the fuel AI technologies need today to deliver maximum value in a timely, secure, and scalable way for organizations and their customers. Outdated or ungoverned data is not only contributing to ineffective use of AI but also poor and unreliable business decisions.” 

In 2024, 82% of Singapore respondents see data streaming as a strategic or important priority in IT investments and more than 73% believe that data streaming platforms can mitigate their AI and data-related challenges in many situations. More importantly, 93% of respondents see data streaming platforms as critical or important to achieving data and information related goals. 

Takeaways from the report include: 

Data streaming platforms power faster AI adoption 

If AI models are to generate accurate and relevant results, the data must be trustworthy, in the right format, and as real-time as possible. Data streaming enriches retrieval augmented generation (RAG)-enabled workloads with trustworthy and contextual data by tapping into a continuous stream of real- time data from systems that power the business. Data streaming can efficiently transform data into the right format to be used by vector databases for AI applications. In Singapore:

● Sixty-nine percent state investments in gen AI will trend up in the coming two years; followed by investments in data streaming and continuous flowing of data (59%). 

● Over 90% of IT leaders see data streaming platforms broaden access to different data sources to contextualise models and ensure that the data ingested meets appropriate quality standards.

Businesses in Singapore are also grappling with broader data-related challenges, such as:

● Uncertain timeliness or quality of data (68%); 

● Governance-related disjoints (65%);

● Fragmented data ownership (62%);

● Inconsistency of data sources (61%); and 

● Data silos (58%) within the organisation.

As businesses learn to do more with less, proving the ROI of tech investments has become even more critical. The 2024 Data Streaming Report shows that data streaming pays off across every industry and that organisations of all sizes are achieving value, despite limited resources. In Singapore:

● Ninety-three percent of IT leaders cite 2x to 10x return on data streaming investments. ● The same percentage state that data streaming improved or is expected to improve cybersecurity, and 96% said the same for data streaming affecting data-driven operations.

● Nine in 10 say data streaming platforms can lead to more product and service innovation in AI and ML development.

Data streaming simplifies the development of data products

Data products are live, refined, fully governed, and ready-to-use data assets that are instantly discoverable, contextualised, trustworthy, and reusable for many use cases. Data products allow organisations to reuse data across a variety of use cases to save costs and time. In Singapore:

~● 69% cite significant benefits from embracing a data product approach. ● 95% cite data products as compelling or worthwhile in enabling more confident data sharing across business units.

● 89% note more meaningful cost allocation or charging based on usage metrics. ● 90% state more robust risk management.

Rajay Rai, CIO, Trust Bank said: “Everything we do is in real time because batch processing is an old way of thinking. The longer your data waits, the less value it has. So, as data comes through, you need to be able to act on it, or enrich it quickly.”

Kamal Brar, Senior VP, APAC, Confluent, said: “The 2024 Data Streaming Report shows that IT leaders in Australia, India, Indonesia, Japan, and Singapore are realising what’s to lose and increasingly investing in continuous flowing of data alongside emerging generative AI technologies. We’re excited to work more closely with them to connect applications and systems with data that is available in real-time, everywhere it’s needed. With a solid central nervous system enabled by data streaming platforms, companies in APAC can focus on accelerating innovation instead of navigating the maze of point-to-point connections.”

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Download the 2024 Data Streaming report at https://report.confluent.io/

*The report was based on a survey from Freeform Dynamics and Radma Research with responses from 4,110 IT leaders familiar with data streaming, from companies with 500 or more employees. Respondents are from Australia, Canada, France, Germany, India, Indonesia, Japan, Singapore, Spain, the UAE, the UK, and the US. Industries polled include technology, financial services, government/public sector, manufacturing, healthcare, media/entertainment, non-profit, professional services, research/education, retail, transportation/logistics, travel/hospitality, and utilities/telecom.