Consider the sheer volume of information flowing through today’s financial systems: every QR payment, e-KYC onboarding, credit card swipe, and cross-border transfer captures a data point. With digital banking and Open Banking, financial institutions are sitting on a goldmine of insights. But this isn’t just about data collection; it’s about converting that data into strategic advantage in a fast-moving, customer-driven landscape.
With digital banks gaining traction and regulators around the world pushing bold reforms, the industry is entering a new phase of financial innovation powered by data and accelerated by AI.
Ecosystm gathered insights and identified key challenges from senior banking leaders during a series of roundtables we moderated across Asia Pacific. The conversations revealed a clear picture of where momentum is building – and where obstacles continue to slow progress. From these discussions, several key themes emerged that highlight both opportunities and ongoing barriers in the Banking sector.
1. AI is Leading to End-to-End Transformation
Banks are moving beyond generic digital offerings to deliver hyper-personalised, data-driven experiences that build loyalty and drive engagement. AI is driving this shift by helping institutions anticipate customer needs through real-time analysis of behavioural, transactional, and demographic data. From pre-approved credit offers and contextual investment nudges to app interfaces that adapt to individual financial habits, personalisation is becoming a core strategy, not just a feature. This is a huge departure from reactive service models, positioning data as a long-term strategic asset.
But the impact of AI isn’t limited to customer-facing experiences. It’s also driving innovation deep within the banking stack, from fraud detection and SME loan processing to intelligent chatbots that scale customer support. On the infrastructure side, banks are investing in agile, AI-ready platforms to support automation, model training, and advanced analytics at scale. These shifts are redefining how banks operate, make decisions, and deliver value. Institutions that integrate AI across both front-end journeys and back-end processes are setting a new benchmark for agility, efficiency, and competitiveness in a fast-changing financial landscape.
2. Regulatory Shifts are Redrawing the Competitive Landscape
Regulators are moving quickly in Asia Pacific by introducing frameworks for Open Banking, real-time payments, and even AI-specific standards like Singapore’s AI Verify. But the challenge for banks isn’t just keeping up with evolving external mandates. Internally, many are navigating a complicated mix of overlapping policies, built up over years of compliance with local, regional, and global rules. This often slows down innovation and makes it harder to implement AI and automation consistently across the organisation.
As banks double down on AI, it is clear that governance can’t be an afterthought. Many are still dealing with fragmented ownership of AI systems, inconsistent oversight, and unclear rules around things like model fairness and explainability. The more progressive ones are starting to fix this by setting up centralised governance frameworks, investing in risk-based controls, and putting processes in place to monitor things like bias and model drift from day one. They are not just trying to stay compliant; they are preparing for what’s coming next. In this landscape, the ability to manage regulatory complexity with speed and clarity, both internally and externally, is quickly becoming a competitive edge.
3. Success Depends on Strategy, Not Just Tech
While enthusiasm for AI is high, sustainable success hinges on a clear, aligned strategy that connects technology to business outcomes. Many banks struggle with fragmented initiatives because they lack a unified roadmap that prioritises high-impact use cases. Without clear goals, AI projects often fail to deliver meaningful value, becoming isolated pilots with limited scalability.
To avoid this, banks need to develop robust return-on-investment (ROI) models tailored to their context — measuring benefits like faster credit decisioning, reduced fraud losses, or increased cross-selling effectiveness. These models must consider not only the upfront costs of infrastructure and talent, but also ongoing expenses such as model retraining, governance, and integration with existing systems.
Ethical AI governance is another essential pillar. With growing regulatory scrutiny and public concern about opaque “black box” models, banks must embed transparency, fairness, and accountability into their AI frameworks from the outset. This goes beyond compliance; strong governance builds trust and is key to responsible, long-term use of AI in sensitive, high-stakes financial environments.
4. Legacy Challenges Still Hold Banks Back
Despite strong momentum, many banks face foundational barriers that hinder effective AI deployment. Chief among these is data fragmentation. Core customer, transaction, compliance, and risk data are often scattered across legacy systems and third-party platforms, making it difficult to access the integrated, high-quality data that AI models require.
This limits the development of comprehensive solutions and makes AI implementations slower, costlier, and less effective. Instead of waiting for full system replacements, banks need to invest in integration layers and modern data platforms that unify data sources and make them AI-ready. These platforms can connect siloed systems – such as CRM, payments, and core banking – to deliver a consolidated view, which is crucial for accurate credit scoring, personalised offers, and effective risk management.
Banks must also address talent gaps. The shortage of in-house AI expertise means many institutions rely on external consultants, which increases costs and reduces knowledge transfer. Without building internal capabilities and adjusting existing processes to accommodate AI, even sophisticated models may end up underused or misapplied.
5. Collaboration and Capability Building are Key Enablers
AI transformation isn’t just a technology project – it’s an organisation-wide shift that requires new capabilities, ways of working, and strategic partnerships. Success depends on more than just hiring data scientists. Relationship managers, credit officers, compliance teams, and frontline staff all need to be trained to understand and act on AI-driven insights. Processes such as loan approvals, fraud escalations, and customer engagement must be redesigned to integrate AI outputs seamlessly.
To drive continuous innovation, banks should establish internal Centres of Excellence for AI. These hubs can lead experimentation with high-value use cases like predictive credit scoring or real-time fraud detection, while ensuring that learnings are shared across business units. They also help avoid duplication and promote strategic alignment.
Partnerships with fintechs, technology providers, and academic institutions play a vital role as well. These collaborations offer access to cutting-edge tools, niche expertise, and locally relevant AI models that reflect the regulatory, cultural, and linguistic contexts banks operate in. In a fast-moving and increasingly competitive space, this combination of internal capability building and external collaboration gives banks the agility and foresight to lead.
Indonesia’s vast, diverse population and scattered islands create a unique landscape for AI adoption. Across sectors – from healthcare to logistics and banking to public services – leaders view AI not just as a tool for efficiency but as a means to expand reach, build resilience, and elevate citizen experience. With AI expected to add up to 12% of Indonesia’s GDP by 2030, it’s poised to be a core engine of growth.
Yet, ambition isn’t enough. While AI interest is high, execution is patchy. Many organisations remain stuck in isolated pilots or siloed experiments. Those scaling quickly face familiar hurdles: fragmented infrastructure, talent gaps, integration issues, and a lack of unified strategy and governance.
Ecosystm gathered insights and identified key challenges from senior tech leaders during a series of roundtables we moderated in Jakarta. The conversations revealed a clear picture of where momentum is building – and where obstacles continue to slow progress. From these discussions, several key themes emerged that highlight both opportunities and ongoing barriers in the country’s digital journey.
Theme 1. Digital Natives are Accelerating Innovation; But Need Scalable Guardrails
Indonesia’s digital-first companies – especially in fintech, logistics tech, and media streaming – are rapidly building on AI and cloud-native foundations. Players like GoTo, Dana, Jenius, and Vidio are raising the bar not only in customer experience but also in scaling technology across a mobile-first nation. Their use of AI for customer support, real-time fraud detection, biometric eKYC, and smart content delivery highlights the agility of digital-native models. This innovation is particularly concentrated in Jakarta and Bandung, where vibrant startup ecosystems and rich talent pools drive fast iteration.
Yet this momentum brings new risks. Deepfake attacks during onboarding, unsecured APIs, and content piracy pose real threats. Without the layered controls and regulatory frameworks typical of banks or telecom providers, many startups are navigating high-stakes digital terrain without a safety net.
As these companies become pillars of Indonesia’s digital economy, a new kind of guardrail is essential; flexible enough to support rapid growth, yet robust enough to mitigate systemic risk.
A sector-wide governance playbook, grounded in local realities and aligned with global standards, could provide the balance needed to scale both quickly and securely.
Theme 2. Scaling AI in Indonesia: Why Infrastructure Investment Matters
Indonesia’s ambition for AI is high, and while digital infrastructure still faces challenges, significant opportunities lie ahead. Although telecom investment has slowed and state funding tightened, growing momentum from global cloud players is beginning to reshape the landscape. AWS’s commitment to building cloud zones and edge locations beyond Java is a major step forward.
For AI to scale effectively across Indonesia’s diverse archipelago, the next wave of progress will depend on stronger investment incentives for data centres, cloud interconnects, and edge computing.
A proactive government role – through updated telecom regulations, streamlined permitting, and public-private partnerships – can unlock this potential.
Infrastructure isn’t just the backbone of digital growth; it’s a powerful lever for inclusion, enabling remote health services, quality education, and SME empowerment across even the most distant regions.
Theme 3. Cyber Resilience Gains Momentum; But Needs to Be More Holistic
Indonesian organisations are facing an evolving wave of cyber threats – from sophisticated ransomware to DDoS attacks targeting critical services. This expanding threat landscape has elevated cyber resilience from a technical concern to a strategic imperative embraced by CISOs, boards, and risk committees alike. While many organisations invest heavily in security tools, the challenge remains in moving beyond fragmented solutions toward a truly resilient operating model that emphasises integration, simulation, and rapid response.
The shift from simply being “secure” to becoming genuinely “resilient” is gaining momentum. Resilience – captured by the Bahasa Indonesia term “ulet” – is now recognised as the ability not just to defend, but to endure disruption and bounce back stronger. Regulatory steps like OJK’s cyber stress testing and continuity planning requirements are encouraging organisations to go beyond mere compliance.
Organisations will now need to operationalise resilience by embedding it into culture through cross-functional drills, transparent crisis playbooks, and agile response practices – so when attacks strike, business impact is minimised and trust remains intact.
For many firms, especially in finance and logistics, this mindset and operational shift will be crucial to sustaining growth and confidence in a rapidly evolving digital landscape.
Theme 4. Organisations Need a Roadmap for Legacy System Transformation
Legacy systems continue to slow modernisation efforts in traditional sectors such as banking, insurance, and logistics by creating both technical and organisational hurdles that limit innovation and scalability. These outdated IT environments are deeply woven into daily operations, making integration complex, increasing downtime risks, and frustrating cross-functional teams striving to deliver digital value swiftly. The challenge goes beyond technology – there’s often a disconnect between new digital initiatives and existing workflows, which leads to bottlenecks and slows progress.
Recognising these challenges, many organisations are now investing in middleware solutions, automation, and phased modernisation plans that focus on upgrading key components gradually. This approach helps bridge the gap between legacy infrastructure and new digital capabilities, reducing the risk of enterprise-wide disruption while enabling continuous innovation.
The crucial next step is to develop and commit to a clear, incremental roadmap that balances risk with progress – ensuring legacy systems evolve in step with digital ambitions and unlock the full potential of transformation.
Theme 5. AI Journey Must Be Rooted in Local Talent and Use Cases
Ecosystm research reveals that only 13% of Indonesian organisations have experimented with AI, with most yet to integrate it into their core strategies.
While Indonesia’s AI maturity remains uneven, there is a broad recognition of AI’s potential as a powerful equaliser – enhancing public service delivery across 17,000 islands, democratising diagnostics in rural healthcare, and improving disaster prediction for flood-prone Jakarta.
The government’s 2045 vision emphasises inclusive growth and differentiated human capital, but achieving these goals requires more than just infrastructure investment. Building local talent pipelines is critical. Initiatives like IBM’s AI Academy in Batam, which has trained over 2,000 AI practitioners, are promising early steps. However, scaling this impact means embedding AI education into national curricula, funding interdisciplinary research, and supporting SMEs with practical adoption toolkits.
The opportunity is clear: GenAI can act as an multiplier, empowering even resource-constrained sectors to enhance reach, personalisation, and citizen engagement.
To truly unlock AI’s potential, Indonesia must move beyond imported templates and focus on developing grounded, context-aware AI solutions tailored to its unique landscape.
From Innovation to Impact
Indonesia’s tech journey is at a pivotal inflection point – where ambition must transform into alignment, and isolated pilots must scale into robust platforms. Success will depend not only on technology itself but on purpose-driven strategy, resilient infrastructure, cultural readiness, and shared accountability across industries. The future won’t be shaped by standalone innovations, but by coordinated efforts that convert experimentation into lasting, systemic impact.
Retail transformation is a continuous, dynamic journey of reinvention – driven by agility, experimentation, and the need to keep pace with ever-evolving consumer behaviour. It’s not a fixed destination but an ongoing process of innovation.
At its heart, retail transformation is about putting the customer squarely in control. It’s the strategic overhaul that allows retailers to truly understand individual desires, offering hyper-personalised journeys that blur the lines between online browsing and in-store discovery.
Click here to download “Future Forward: Reimagining Retail” as a PDF.
Enabling Growth with Smarter Sales and Distribution
India’s Tata Consumer Products, aiming to grow their FMCG market share, set out to digitise sales across the vast ‘kirana’-driven retail network.
The company replaced outdated tools with a system that streamlines distributor onboarding, order management, and retail execution – cutting setup times from days to minutes.
A mobile app gives field reps real-time inventory, auto-applied promos, and personalised KPIs, while dashboards give managers live territory insights. Built in seven months, the platform now handles 6M+ transactions monthly, supports 8,000 reps, 12,000 distributors, and 1.6M outlets. Centralised service and rapid feature rollouts keep Tata Consumer fast, responsive, and customer-focused.
Addressing Legacy Limitations
One of New Zealand’s leading grocery retailer, Foodstuffs South Island, faced growing limitations from aging ERP systems and hardware nearing end-of-life.
Instead of reinvesting in outdated tech, FSSI launched Project Petra – a leap to a unified, cloud-based ERP platform.
The shift enabled intelligent replenishment, robotic automation, and a vastly improved user experience. In 18 months, FSSI streamlined roles, rebuilt core apps, and completed a smooth go-live in just three days. The payoff: forecasting and replenishment times cut by up to 50%, faster transactions, seamless price updates, and real-time insights. What began as a tech upgrade became a full transformation – boosting agility, empowering teams, and fuelling future-ready growth.
Streamlining Workflows, Empowering Employees
UCC Group, the Japanese coffee pioneer, is brewing a transformation internally. With 88 locations across 21 countries, UCC faced mounting inefficiencies from outdated legacy systems – slow, complex workflows and clunky portals that frustrated employees and slowed approvals.
UCC replaced their legacy systems with a cloud-first, mobile-first platform.
VPNs were eliminated. Approvals that once took multiple logins now take one tap. A clean, co-designed portal replaced the old interface, putting ease of use first. E-signatures and digitised requests cut paper use by 90% – over 1.5 million forms saved. A new life-event portal launched in just one month, proving speed and simplicity can coexist. Now expanding globally, UCC is unifying ERP, data, and apps into a single, employee-first hub – built for scale, speed, and the future.
Scaling Customer Experience at Speed
Aditya Birla Fashion Retail Limited (ABFRL) faced the challenge of scaling their multi-brand presence without compromising customer experience. As growth surged across stores, online platforms, and marketplaces, their order management system struggled to keep up – putting fulfillment speed, accuracy, and satisfaction at risk.
To solve this, ABFRL implemented a scalable, multi-instance order management solution that streamlined inventory tracking, fulfillment, and refunds.
The result: 99.5% faster inventory sync, zero refund failures, smarter order decisions, and accurate delivery estimates across all channels. This strategic overhaul helped ABFRL maintain service excellence while fuelling sustainable growth – proving that operational agility is key to scaling customer experience at speed.
Solving Reliability & Scalability Challenges
Chicks Lifestyle is a trusted home-grown brand in Hong Kong known for quality innerwear and thermal wear. As they expanded online and geared up for sustainable growth, outdated on-prem systems began to strain under peak-season pressure – causing crashes, long checkout lines, and customer frustration.
To fix this, they migrated their core ERP and POS systems to the cloud in just six weeks with zero data loss.
The result: 99.99% uptime, 30% jump in efficiency, 15% faster checkouts, and 40% lower IT costs. Loyalty data access dropped from minutes to seconds, enabling personalised service at scale. With a stable, scalable tech backbone in place, Chicks Lifestyle is now exploring AI to power their next phase of innovation.
