Ambition vs. Reality: The State of Data and Analytics in Singapore & Indonesia

As agentic AI ushers in unprecedented productivity, customer connection, and growth, there’s a sense of urgency for organisations to reinvent themselves to realise the opportunities this brings. However, the vast majority of organisations lack the data foundations to fully achieve their AI ambitions.

In fact, 95% of technical leaders in Indonesia and 91% in Singapore say they need to overhaul their data strategies for their AI strategies to succeed. These findings come from Salesforce’s 2nd Edition of the State of Data & Analytics Report, which surveyed 3,800 data and analytics leaders and 3,852 cross-functional business leaders worldwide. 

The report reveals essential insights into: 

• The current state of data and analytics in ASEAN and the opportunities ahead
• How to build a solid data foundation for analytics and AI 
• Why safeguarding the future requires stronger governance 

Here’s what you need to know.

State of data maturity in ASEAN impacting AI progress

There is a clear disconnect in how regional businesses view their relationship with data. More than half (54%) of business leaders in Singapore and nearly 8 out of 10 (78%) in Indonesia describe their organisations as data-driven. Yet, when you dig deeper, the reality tells a different story: 63% of data and analytics leaders in Singapore and 90% in Indonesia say their companies struggle to drive business priorities with data.

Pressure is mounting to close the gap between perceptions of data maturity and reality, and AI is a primary driver. In fact, Singapore respondents to our survey cited building AI capabilities as their number one data priority, while Indonesia respondents ranked it number two, just behind providing access to real-time insights.

To meet these ambitions, organisations must first address their data foundations. Data quality is a major issue, impacting AI outputs and progress. 

So just how does data quality impact AI adoption in Singapore and Indonesia? 

Our State of Data & Analytics Report revealed eight out of ten data and analytics leaders in Singapore and Indonesia with AI in production, say they’ve experienced inaccurate or misleading AI outputs. Furthermore, 66% of leaders in Singapore and 46% in Indonesia at companies that are training or fine-tuning their own AI models report that they’ve wasted significant resources doing so with bad data.

Data quality also impacts trust and confidence. For instance, 34% of data and analytics leaders in Indonesia say their companies occasionally or even frequently draw incorrect conclusions from data with poor business context. This percentage is even higher amongst data and analytics leaders in Singapore — with over half (59%) experiencing similar issues with trust and confidence in data.

Building a better data foundation for the agentic enterprise

A new model of work is emerging where AI doesn’t just automate tasks; it elevates human potential. In an agentic enterprise, human employees and intelligent AI agents work together to achieve a level of productivity and creativity that neither could reach alone.

To realise the opportunities this brings, businesses must revisit how data is accessed, used, and stored. Unfortunately, data silos in ASEAN enterprises remain a key issue, with data and analytics leaders in Indonesia and Singapore estimating that around one-fifth (17% and 21% respectively) of their companies’ data is siloed, inaccessible, or otherwise unusable.

Another challenge is that the vast majority of enterprise data is unstructured — lacking the formatting or organisation necessary to be analysed with traditional business intelligence methods. Currently, 70% of data and analytics leaders believe the most valuable insights for their organisations are trapped in this unstructured data.

To mitigate trapped data challenges, 58% of Singapore organisations and 47% of Indonesia organisations are adopting zero copy data integration, an approach that enables simultaneous access to data across multiple databases without moving, copying, or reformatting anything. 

This approach is paying off, with those in Singapore using zero copy reporting they are 74% more likely to deliver superior customer experiences, and 182% more likely to succeed with AI initiatives than those without zero copy.

Beyond Singapore and Indonesia, Fulbright University Vietnam is one organisation that’s used zero copy to kickstart its AI success. The university has tapped into the power of zero copy through Data 360, which seamlessly integrates all structured and unstructured data. The solution consolidates student information and has structured and centralised the organisation’s knowledge base, enabling Agentforce to draw on clean, reliable data. 

With the advantage of a single source of truth for data, Fulbright was well-positioned to move quickly on Agentforce. 

“From start to launch, Agentforce implementation took just three weeks. It was simple because we already had high-quality data on the Salesforce platform managed through Data 360, and the ease of deployment proved that our long-term strategy – investing early in clean data and unified systems – was the right one. It gives us the agility to adopt new technologies quickly and confidently.”

• Quang Ha Nguyen, Director of Information Technology, Fulbright University

Safeguarding the future: Why AI advances demand stronger data governance

The State of Data & Analytics Report found data governance lagging in Southeast Asia, with only 43% of leaders in Indonesia and 40% in Singapore having established formal data governance frameworks and policies. The global outlook is not much more promising, with 80% of data and analytics leaders having varying data governance practices across environments, and 57% lacking ethical AI guidelines.

The rise of AI exposes long-standing shortcomings in data security, compliance, and governance measures — and demands a new approach. Security leaders are already feeling this shift. More than half (62%) of those surveyed for our State of IT: Security Report indicated that customers remain cautious about AI adoption, with data security and privacy top of mind. At the same time, they point to a powerful opportunity: people want to trust AI and the businesses that use it.

As data and analytics leaders secure the agentic enterprise, they must consider how to: 

• Make governance scalable across data types and users
• Provide granular access control across data types
• Ensure privacy, ethics, and compliance in a unified data environment

Democratising insights with agentic analytics

Businesses that overcome their data challenges will be poised to succeed in an agentic future that democratises data, AI, and analytics for everyone. AI agents hold particular appeal and potential for data analytics, making data consumption and interaction highly intuitive and conversational.

Currently, 72% of data and analytics leaders in Singapore and 60% in Indonesia say translating business questions into technical queries is prone to error, and 97% of business leaders in both countries say they’d perform better if they could ask data questions with natural language. AI can solve for these challenges, improving data literacy and access.

AVPN is a great example of how AI makes data more accessible. The largest network of social investors in Asia, AVPN comprises over 600 funders and resource providers across 33 markets. The organisation leveraged Salesforce to build a secure, AI-powered platform, ImpactCollab, that connects private bank clients with verified philanthropic opportunities and streamlines due diligence. It aims to mobilise up to US$100 million in philanthropic capital by 2030, enhancing Singapore’s role as a philanthropic hub.

To address the challenge of navigating a vast number of opportunities, AVPN integrated Agentforce as a powerful search tool and an AI-powered ‘philanthropy advisor’. The AI agent helps relationship managers quickly find relevant opportunities and gain insights by simplifying complex terminology and answering specific queries. 

Agentforce assists both external investors seeking information and internal employees with due diligence. This AI-powered advice is more detailed and efficient than what human advisors canproduce in the same timeframe — showcasing the power of leveraging a unified source of data to drive better insights.

It’s time to elevate data maturity in ASEAN

As organisations journey to become agentic enterprises, they demand more from their data than their current foundations enable. Businesses that address this tension will be best positioned to scale AI with accuracy and confidence.

However, as the urgency around AI increases, trust remains essential. Building an agentic future requires a foundation rooted in security, compliance, and quality data that teams can rely on.

Learn more:

• Discover how Data 360 can unlock the full value of your data across the enterprise 
• Learn how Tableau Next powers analytics for the agentic era
• Watch how the Data 360 Zero Copy Partner Network unlocks your data
• Watch the keynotes from Dreamforce for free on Salesforce+