Unblocking Enterprise Data

How APAC Businesses Are Turning AI Strategy Into Results

Executive Summary

As APAC businesses look ahead to 2026, the ambition is clear: grow faster, operate smarter, and adapt quicker but ambition alone isn’t enough. According to the APAC 2025 Business Trends Report, while growth and process simplification top the strategic agenda, many organizations are still struggling with the realities of execution: fragmented systems, unreliable data, and slow AI adoption. APAC leaders’ top internal blockers are data-centric: inconsistent data quality, fragmented systems, and legacy platforms. Integrated platforms are critical to connect data, systems, and processes, enabling AI to deliver tangible business outcomes, however nearly half of APAC businesses report lack of confidence in enterprise data.

To accelerate progress, 40–48% APAC leaders are investing heavily into AI, analytics and integration in the next 12 months. This investment into data infrastructure, embedded AI workflows and cross-functional collaboration will ensure these APAC leaders will better adapt to a rapidly evolving digital environment.

Nearly half of APAC businesses lack confidence in their data. Yet, 40–48% are investing in AI, analytics, and integration. The winners will be those who fix their data foundation first

LEOCH International Technology Ltd Achieved 10% Faster Implementation and 30% Less Manual Work

Order reconciliation dropped to 1 minute, transaction verification became 6x faster, and exchange-rate maintenance fell from 48 hours to 10 minutes. LEOCH is now exploring AI- driven automation use cases for further transformation.

Data-Centric Roadblocks

Despite clear goals for growth and process efficiency, several internal challenges slow progress. Barriers range from structural issues like departmental silos and outdated systems to capability gaps in talent and AI integration. Notably, data-related limitations also emerge as a top internal blocker, reinforcing the need for stronger infrastructure and governance.

Quality of Data / Decision Tools

System Integration Gaps

Legacy Systems

Enterprise Data access and quality trusted for AI 51% feel strongly that ED is sufficiently strong

Top 3 challenge for 33% (11% rank it as #1)

Top 3 challenge for 26.6% (9.7% #1)

Top 3 27.5% (10.2% #1)

Digging deeper into the data challenge, nearly half of leaders report limited confidence in the accessibility, quality, and reliability of the data they use.

47.4% have little to moderate trust that their data is complete and up to date .

46.1% do not fully trust the quality of data used for decisions.

45.9% lack sufficient access to the data needed for decision-making.

These gaps not only slow down strategic planning but also hinder the ability to scale AI, automate processes, and respond proactively to market changes. To move forward, organizations must confront these internal inefficiencies head-on while remaining agile in the face of external volatility. Strengthening data infrastructure, modernizing legacy systems, and fostering a culture of cross-functional collaboration are essential. As APAC leaders prioritize innovation and resilience, the ability to make confident, data-driven decisions will define who thrives in a rapidly evolving landscape.

Struggling with slow reporting, manual reconciliations, or

unreliable dashboards? 47% of APAC leaders say they can’t fully trust their data for decisions. This is an IT problem, and an opportunity.

Hitachi Cut Upgrade Cycles From 18 Months to 1 Month Reduced ERP customizations from 9,000 to 22 and cut upgrade cycles from 18 months to 1 month. Using SAP BTP for integration, automation, and low-code development, it built 98 extensions for workflows, reports, and subsystem integration. This approach enabled faster upgrade cycles and improved global connectivity.

Data for AI: Where Value & Risk Meet

While strategic growth ambitions set the direction, success hinges on operational execution. This is where AI becomes a pivotal enabler, bridging the gap between vision and reality.

The benefits of Business AI expand across all business operations; from automation of repetitive tasks, driving personalized customer experiences to empowering data-driven decision-making, AI drives efficiency, cost reduction, and scalability.

For APAC Businesses where AI has been deployed, these benefits are tangible:

• 61.5% of organizations say job satisfaction has improved, thanks to the reduction in repetitive tasks.

• 53.1% say AI has improved collaboration and communication across teams.

• 50% report improvement in work-life balance among employees, enabled by smarter workflows and reduced manual effort.

Perceived AI Risks

AI’s promise - automation, better decisions, happier teams - depends on IT’s ability to unify, govern, and activate enterprise data. The right platform turns IT from a cost center into a growth engine.

Insufficient data size / quality 34 .8%

Acting on Incorrect data 33 %

Lack of transparency 32 .3%

Data privacy controls 29 %

By investing in a unified data foundation like SAP Business Data Cloud (BDC), APAC organizations can overcome these barriers, ensuring that AI and analytics initiatives are built on reliable, accessible, and governed data, turning strategy into measurable results.

ABB Saved Over One Million FTE Days While Improving Quotation Accuracy Automated RFQ processing at scale with SAP Document AI and generative AI on SAP BTP, reducing response times by 1 day for large tenders and 4 days for smaller projects. This translates to potential annual savings of over one million FTE days and millions of dollars, while improving quotation accuracy and customer experience.

Increasing Investment into Enterprise Data and AI

Investment trends in APAC reflect growing interest in AI, with many APAC businesses citing their top technology investments into AI:

• 17.7% of leaders cite generative AI and AI agents

• 13.1% to use AI to automate processes and improve decision-making.

Strong awareness of the need for strong data foundations and governance is also evident. Overall, APAC’s Top Technology Investment priorities follow closely the ‘activate data’ stack, to build this data foundation towards confident AI implementation – as shown below.

Investments in Data & Foundation Solutions to Support AI Implementation

Gen AI – signaling strong intent to embed AI-driven automation and content generation Analytics Tool – reinforcing the need for actionable insights Integration of Systems - showing foundational moves to unify and modernize enterprise data

47.5%

38.3%

30.4%

28.5%

Cloud Migration

JK Cement Ltd. Reduced Process Time by 50% Embedded SAP Business AI within SAP BTP to simplify purchase requisitions using natural language input via the generative AI hub and ChatGPT-4o model. This reduced process time by 50%, freeing employees from repetitive tasks and enabling faster scaling. JK Cement plans to extend this AI-driven simplicity to invoices, sales orders, and goods receipts.

SAP Business Technology Platform: Turning Potential into Performance

To scale AI from pilot to production, organizations require a foundation that connects data, systems, and processes effectively.

Enterprise platforms such as SAP Business Technology Platform (BTP) provide capabilities for integration, automation, and AI deployment across business functions. These platforms address common challenges like fragmented systems and limited data accessibility by enabling real-time insights, supporting application development, and maintaining compliance in multi-cloud environments.

Specifically, SAP Business Data Cloud addresses the following APAC ‘pain points’ identified:

• Unified data access & virtualization across SAP/Non-SAP , tackling “lack of access,” “silos,” “integration between systems.” • Business-ready data products with governance - with catalog, lineage and quality rules, BDC addresses data quality/trust and AI risk. • Semantic alignment with SAP applications - data models for finance, supply chain, HR to accelerate analytics & AI outcomes • Multi-cloud elasticity and security - supports cloud migration and data privacy concerns. By leveraging a unified platform like BTP and BDC, businesses are not only streamlining processes but also positioning themselves for future growth through predictive insights and human-like digital experiences.

What the Analysts Say about SAP BTP

SAP Business Data Cloud (BDC)

Gartner

A governed, multi-cloud data foundation for SAP and non-SAP data that: • Unifies access via virtualization and connectors, • Standardizes semantics using business context from SAP apps, • Governs with catalog, lineage, quality, and policy, • Publishes reusable data products for analytics & AI, • Secures data with privacy/PII controls and auditable policies.

“SAP is a Leader in this Magic Quadrant. It offers SAP Integration Suite, which is part of the SAP BTP. It provides application, data, process, AI and business integration capabilities, both within and outside the SAP application ecosystem.” Read More

IDC

“SAP BTP is a cloud-native platform that brings together data and analytics, AI, application development, automation, and integration in one unified environment.” Read More

A Path Forward in 2026

As APAC businesses accelerate digital transformation, the insights from this report highlight a clear path forward: AI and data platforms are fundamental for bridging the gap between strategy and execution. Consider the following pathway for how your business can turn ambition into measurable outcomes by leveraging SAP Business Technology Platform (SAP BTP), Business Data Cloud (BDC) and AI-driven innovation.

Key Actions

Focus Area

KPI & Outcomes

• Baseline current data access, quality, and AI- data trust metrics.

Move to a ‘medium’ confidence in:

Data Visibility & Trust

•

Launch BDC catalog & lineage

• • •

Data access Data quality

• Identify critical data elements for 2–3 priority domains (e.g., vendor, material, workforce)

AI-data reliability

• Connect SAP and non-SAP sources into BDC

•

# of integrated systems

•

Publish first data products for a Top-3 business priority (e.g., process automation in Procure-to-Pay)

Integration to Outcomes

•

# of published data products

•

Enable cross-functional access

•

Move to a ‘strong’ confidence on AI-data reliability

• Layer analytics and predictive models on governed data

• Pilot AI agents using BDC-served features in a high-impact function (IT, SCM, HR) • Track outcome metrics (decision speed, cost reduction)

Decisioning & AI

•

Decision cycle time

•

Cost savings from automation

• Expand data quality policies, privacy, and access controls

• •

# of domains covered

# of policies implemented

Scale & Guardrails

• Extend BDC to additional domains and partners

•

Move to a ‘strong’ confidence in data quality/privacy

• Monitor and mitigate AI risks (data quality, privacy, transparency)

Book a Demo

Yulin Wang SAP BTP & DC Specialist, SAP China

Amjed Khan SAP BTP & BDC Specialist, SAP India

Kazuki Ogasawara SAP BTP & BDC Specialist, SAP Japan

Ranjith K SAP BTP & BDC Specialist, SAP SEA

amjed.khan@sap.com

kazuki.ogasawara@sap.com

ranjith.k01@sap.com

yulin.wang01@sap.com

Report Method: 2025 SAP Business Priorities

This report is grounded in the 2025 SAP Business Priorities survey, which gathered responses from 2,152 senior business leaders across Asia-Pacific markets, excluding China, and 9,293 global respondents for comparison as ‘Rest of World’ (RoW). The APAC sample spans a diverse mix of industries and company sizes, and the majority of respondents hold director- level or above roles, with over 60% reporting strategic decision-making responsibilities. This demographic breadth ensures a robust and representative view of the structural challenges and strategic priorities shaping Asia-Pacific’s business landscape.

To read full report, click here.

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