AI is not just reshaping how businesses operate — it’s redefining the CFO’s role at the centre of value creation, risk management, and operational leadership.
As stewards of capital, CFOs must cut through the hype and ensure AI investments deliver measurable business returns. As guardians of risk and compliance, they must shield their organisations from new threats — from algorithmic bias to data privacy breaches with heavy financial and reputational costs. And as leaders of their function, CFOs now have a generational opportunity to modernise finance, champion AI adoption, and build teams ready for an AI-powered future.
LEAD WITH RIGOUR. SAFEGUARD WITH VIGILANCE. CHAMPION WITH VISION.
That’s the CFO playbook for AI success.
Click here to download “AI Stakeholders: The Finance Perspective” as a PDF.
1. Investor & ROI Gatekeeper: Ensuring AI Delivers Value
CFOs must scrutinise AI investments with the same discipline as any major capital allocation.
- Demand Clear Business Cases. Every AI initiative should articulate the problem solved, expected gains (cost, efficiency, accuracy), and specific KPIs.
- Prioritise Tangible ROI. Focus on AI projects that show measurable impact. Start with high-return, lower-risk use cases before scaling.
- Assess Total Cost of Ownership (TCO). Go beyond upfront costs – factor in integration, maintenance, training, and ongoing AI model management.
Only 37% of Asia Pacific organisations invest in FinOps to cut costs, boost efficiency, and strengthen financial governance over tech spend.
2. Risk & Compliance Steward: Navigating AI’s New Risk Landscape
AI brings significant regulatory, compliance, and reputational risks that CFOs must manage – in partnership with peers across the business.
- Champion Data Quality & Governance. Enforce rigorous data standards and collaborate with IT, risk, and business teams to ensure accuracy, integrity, and compliance across the enterprise.
- Ensure Data Accessibility. Break down silos with CIOs and CDOs and invest in shared infrastructure that AI initiatives depend on – from data lakes to robust APIs.
- Address Bias & Safeguard Privacy. Monitor AI models to detect bias, especially in sensitive processes, while ensuring compliance.
- Protect Security & Prevent Breaches. Strengthen defences around financial and personal data to avoid costly security incidents and regulatory penalties.
3. AI Champion & Business Leader: Driving Adoption in Finance
Beyond gatekeeping, CFOs must actively champion AI to transform finance operations and build future-ready teams.
- Identify High-Impact Use Cases. Work with teams to apply AI where it solves real pain points – from automating accounts payable to improving forecasting and fraud detection.
- Build AI Literacy. Help finance teams see AI as an augmentation tool, not a threat. Invest in upskilling while identifying gaps – from data management to AI model oversight.
- Set AI Governance Frameworks. Define accountability, roles, and control mechanisms to ensure responsible AI use across finance.
- Stay Ahead of the Curve. Monitor emerging tech that can streamline finance and bring in expert partners to fast-track AI adoption and results.
CFOs: From Gatekeepers to Growth Drivers
AI is not just a tech shift – it’s a CFO mandate. To lead, CFOs must embrace three roles: Investor, ensuring every AI bet delivers real ROI; Risk Guardian, protecting data integrity and compliance in a world of new risks; and AI Champion, embedding AI into finance teams to boost speed, accuracy, and insight.
This is how finance moves from record-keeping to value creation. With focused leadership and smart collaboration, CFOs can turn AI from buzzword to business 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.
What if your bank could predict your financial needs before you even realised them? Imagine a financial institution that understands your behaviours, anticipates your needs, and engages with you meaningfully in real time. That’s the power of modern marketing. We’re not talking about one-size-fits-all campaigns; we’re talking about creating personalised experiences that resonate on an individual level. Financial institutions are increasingly recognising that when marketing is done right, it becomes a powerful driver of customer loyalty and growth.
Take Netflix, for example – the frontrunner in personalisation. They don’t just serve content; they study audience preferences to deliver exactly what each viewer wants. Now, picture banks doing the same. Banks can apply the same principles by building a complete view of each customer based on transactions, preferences, and lifestyle signals. This allows them to deliver personalised content, products, and nudges that help customers make smarter financial decisions – and feel more understood in the process.
The Opportunity: Marketing Beyond the Surface
The real opportunity for banks today is to reimagine marketing – not as a support function, but as a strategic growth engine. This means pulling marketing out of the back office and placing it at the heart of business decision-making. When marketing is deeply embedded in strategy, aligned with business goals, and backed by executive support, it becomes a force multiplier. Cross-functional teams start working in sync, campaigns become smarter and more personalised, and outcomes become measurable and meaningful. The impact? Rapid customer growth, stronger retention, and sharper product uptake. This reimagination hinges on two foundational shifts:
- Culture Shift. Agile, cross-functional teams that focus on delivering specific customer outcomes rather than managing marketing channels in silos. These teams are empowered to act quickly, experiment, and refine based on feedback.
- Tech-Enabled Precision. A well-governed MarTech stack that enables real-time personalisation by effectively using data, decisioning models, and delivery mechanisms. This means moving from siloed systems to unified, intelligent platforms.
When these shifts align, marketing transforms from a function into a growth engine – fuelling innovation and building deeper customer relationships.
Embracing Modern Marketing Principles
Modern marketing starts with a few foundational shifts.
1. Embedding Marketing into Business Strategy. Marketing needs to be part of business strategy from the start – not bolted on at the end. When marketers have a seat at the table during strategy planning, they can shape priorities, align efforts, and measure impact more effectively.
This requires:
- Early involvement in strategic decision-making
- Marketing scorecards derived from business KPIs
- A unified voice across product, marketing, and operations
Also, Internal teams must be in sync with customer promises made externally. This means training, communication, and shared understanding across departments to ensure every touchpoint reinforces a consistent message. Whether it’s a branch interaction, a call centre response, or a chatbot exchange – each moment becomes a reflection of the brand’s commitment.
By embedding marketing within the business from the outset and aligning it with internal delivery mechanisms, organisations are better positioned to deliver on their promises and build lasting trust.
2. Turning Data into Action: Using MarTech for Smarter Decisions and Delivery. Modern marketing runs on data – but it only matters if it drives action. Banks need a systematic approach to turning raw data into relevant, timely customer experiences.
- Organise. Cleanse and consolidate data to form a single view of each customer.
- Decide. Apply AI/ML models to extract insights, make predictions, and personalise offerings.
- Deliver. Communicate through the most effective channels at the right moment.
But a smart stack needs structure. MarTech governance is essential to ensure tech investments are strategic – not duplicative. A cross-functional steering committee, with voices from marketing, IT, compliance, and business leadership, should guide decisions. This keeps tools aligned with business goals and ensures interoperability.
Equally important is fostering a culture of experimentation. A/B testing and continuous learning should be baked into campaign design – not as add-ons, but as core capabilities. This sharpens performance and fuels innovation by quickly scaling what works. Each test becomes a feedback loop, feeding a smarter, more agile marketing engine.
Embedding these practices into the data-decisioning-delivery loop helps banks move from scattered insights to coordinated, high-impact engagement.
3. Outcome-Focused Teams and Operating Models. Rather than being structured around traditional channels, high-performing marketing teams operate around customer journeys and outcomes. Agile squads can be created for:
- Seamless onboarding
- Product activation and adoption
- Retention and cross-sell strategies
These squads have to be multidisciplinary – combining marketing, data science, engineering, and product. They need to be empowered to experiment, move fast, and own KPIs tied to customer impact.
Outcome-driven teams focus on delivering measurable value – not just activity. For instance, a squad working on onboarding might track completion rates and activation time, while a cross-sell squad may target conversion on tailored offers. The shift to outcome-oriented delivery ensures that efforts are tied to clear business metrics, with faster feedback loops and accountability.
By storing, organising, and analysing customer data, banks equip these teams to predict needs more accurately. Insights fuel smarter decisions – enabling real-time, context-aware offers. Paired with agile delivery, this data-led approach makes every interaction timely, relevant, and impactful.
This approach ensures agility, accountability, and focus. By reducing reliance on rigid departmental structures, teams can iterate quickly and deliver greater value across the customer lifecycle.
The Modern Marketing Imperative
As customer needs and expectations evolve, marketing must adapt to modern standards, with a tighter alignment between business and marketing to deliver delightful customer experiences and impactful outcomes. These are the new imperatives for growth.
These principles are not just theoretical – they’re actionable steps that enable banks to anticipate needs, deliver hyper-personalised experiences, and build lasting relationships. By embracing this shift, banks can move from reactive to proactive, empowering customers to make smarter financial decisions while driving loyalty and growth. Ultimately, the future of banking lies in a personalised, integrated, and data-driven experience for every customer.
Customer Success leaders are keenly aware of AI’s burgeoning potential, and our latest research confirms it. AI is no longer a futuristic concept; it’s a present-day reality, already shaping content strategies for 55% of organisations and poised to expand its influence across a multitude of use cases.
Over the past two years, Ecosystm’s research – including surveys and deep dives with business and tech leaders – has consistently pointed to AI as the dominant theme.
Here are some insights for Customer Success Leaders from our research.
Click here to download “AI Stakeholders: The Customer Success Perspective” as a PDF.
AI in Action: Real-World Applications
The data speaks for itself. We’re seeing a significant uptake of AI in automating sales processes (69%), location-based marketing (63%), and delivering personalised product/service recommendations (61%). But beyond the numbers, what does this look like in practice?
In Marketing, AI tailors campaigns in real time based on customer behaviour, ensuring content and offers resonate. For e.g. in the Travel industry, AI analyses customer preferences to create customised itineraries, boosting satisfaction and repeat bookings. In Sales, AI-driven analysis of buying patterns helps teams stay ahead of trends, equipping them with the right products to meet demand. In Customer Experience, AI-powered feedback analysis identifies pain points before they escalate, leading to proactive problem-solving. We have already seen organisations using conversational AI to enable 24/7 customer engagement, instantly resolving issues while reducing team workload and enhancing CX.
Challenges and Opportunities: Navigating the AI Landscape
However, the path to AI adoption isn’t without its hurdles. Customer Success leaders face significant challenges, including the lack of an organisation-wide AI strategy, data complexity and access issues, and the cost of implementation.
Despite these challenges, the focus on AI to enhance Customer Success is evident, with nearly 40% of AI initiatives geared towards this goal. This requires a more active role for these leaders in shaping AI strategies and roadmaps.
Our research reveals that there lies a critical gap: Customer Success leaders have limited involvement in AI initiatives. Only 19% are involved in identifying and prioritising use cases, and a mere 10% have input into data ownership and governance. This lack of participation is a missed opportunity.
The 2025 Vision: AI-Driven Customer Success
Looking ahead, Customer Success leaders expect AI to deliver significant benefits, including improved customer experience (56%), increased productivity (50%), and enhanced innovation (44%). These expectations underscore AI’s pivotal role in shaping the future of customer success.
To fully harness AI’s potential and advancements like Agentic AI, leaders must take a more active role. This means driving a clear AI strategy, tackling data challenges, and working closely with IT and data science teams to ensure AI solutions address real customer pain points and business gaps.
The Asia Pacific region is rapidly emerging as a global economic powerhouse, with AI playing a key role in driving this growth. The AI market in the region is projected to reach USD 244B by 2025, and organisations must adapt and scale AI effectively to thrive. The question is no longer whether to adopt AI, but how to do so responsibly and effectively for long-term success.
The APAC AI Outlook 2025 highlights how Asia Pacific enterprises are moving beyond experimentation to maximise the impact of their AI investments.
Here are 5 key trends that will impact the AI landscape in 2025.
Click here to download “The Future of AI-Powered Business: 5 Trends to Watch” as a PDF.
1. Strategic AI Deployment
AI is no longer a buzzword, but Asia Pacific’s transformation engine. It’s reshaping industries and fuelling growth. Initially, high costs and complex ROI pushed leaders toward quick wins. Now, the game has changed. As AI adoption matures, the focus is shifting from short-term gains to long-term, innovation-driven strategies.
GenAI is is at the heart of this shift, moving beyond the periphery to power core business functions and deliver competitive advantage.
Organisations are rethinking AI investments, looking beyond pure financials to consider the impact on jobs, governance, and data readiness. The AI journey is about balancing ambition with practicality.
2. Optimising AI: Tailored Open-Source Models
Smaller, open-source, and specialised AI models will gain momentum as organisations seek efficiency, flexibility, and sustainability in their AI strategies.
Unlike LLMs, which require high computational power, smaller, task-specific models offer comparable performance while being more resource-efficient. This makes them ideal for organisations working with proprietary data or limited computational resources.
Beyond cost and performance, these models are more energy-efficient, addressing growing concerns about AI’s environmental impact.
3. Centralised Tools for Responsible Innovation
Navigating the increasingly complex AI landscape demands unified management and governance. Organisations will prioritise centralised frameworks to tame the chaos of diverse AI solutions, ensuring compliance (think EU AI Act) while boosting transparency and security.
Automated AI lifecycle management tools will streamline oversight, providing real-time tracking of model performance, usage, and issues like drift.
By using flexible developer toolkits and vendor-agnostic strategies, organisations can accelerate innovation while maintaining adaptability, as the technology evolves.
4. Supercharging Workflows With Agentic AI
Organisations will embrace Agentic AI to automate complex workflows and drive business value. Traditional automation tools struggle with real-world dynamism, but AI-powered agents offer a flexible solution. They empower autonomous task execution, intelligent decision-making, and adaptability to changing circumstances.
These agents, often using GenAI, understand complex instructions and learn from experience. They collaborate with humans, boosting efficiency, and adapt to disruptions, unlike rigid traditional automation.
Agentic workflows are key to redefining work, enabling agility and innovation.
5. From Productivity to People
The focus of AI conversations will shift from simply boosting productivity to using AI for human-centric innovation that transforms both employee roles and customer experiences.
For employees, AI will handle routine tasks, enabling them to focus on creativity and innovation. Education and training will be crucial for a smooth transition to AI-powered workflows.
For customers, AI is evolving to offer more empathetic, personalised interactions by understanding individual emotions, motivations, and preferences. Organisations are recognising the need for transparent, explainable AI to build trust, tailor solutions, and deepen engagement.
Hit or miss AI experiments have leaders demanding results. In this breakneck AI landscape, strategy and realism are your survival tools. A pragmatic approach? High-impact, achievable goals. Know your capabilities, prioritise manageable projects, and stay flexible. The AI winners will be those who champion human-AI collaboration, bake in ethics, and never stop researching.
In 2024, technology vendors have heavily invested in AI Agents, recognising their potential to drive significant value. These tools leverage well-governed, small datasets to integrate seamlessly with applications like Workday, Salesforce, ServiceNow, and Dayforce, enhancing processes and outcomes.
2025 is poised to be the year of AI Agent adoption. Designed to automate specific tasks within existing workflows, AI Agents will transform customer experiences, streamline operations, and boost efficiency. Unlike traditional AI deployments, they offer a gradual, non-disruptive approach, augmenting human capabilities without overhauling processes. As organisations adopt new software versions with embedded AI capabilities, 2025 will mark a pivotal shift in customer experience delivery.
Ecosystm analysts Audrey William, Melanie Disse, and Tim Sheedy present the top 5 trends shaping customer experience in 2025.
Click here to download ‘AI-Powered Customer Experience: Top 5 Trends for 2025’ as a PDF
1. AI Won’t Wow Many Customers in 2025
The data is in – the real focus of AI over the next few years will be on productivity and cost savings.
Senior management and boards of directors want to achieve more with less – so even when AI is being used to serve customers, it will be focused on reducing back-end and human costs.
There will be exceptions, such as the adoption of AI agents in contact centres. However, AI agents must match or exceed human performance to see broad adoption.
However, the primary focus in contact centres will be on reducing Average Handling Time (AHT), increasing call volume per agent, accelerating agent onboarding, and automating customer follow-ups.
2. Organisations Will Start Treating CX as a Team Sport
As CX programs mature, 2025 will highlight the need to break down not only data and technology siloes but also organisational and cultural barriers to achieve AI-powered CX and business success.
AI and GenAI have unlocked new sources of customer data, prompting leaders to reorganise and adopt a mindset shift about CX. This involves redefining CX as a collective effort, engaging the entire organisation in the journey.
Technologies and KPIs must be aligned to drive customer AND business needs, not purely driving success in siloed areas.
3. The First “AGI Agents” Will Emerge
AI Agents are set to explode in 2025, but even more disruptive developments in AI are on the horizon.
As conversational computing gains traction, fuelled by advances in GenAI and progress toward AGI, “Complex AI Agents” will emerge.
These “AGI Agents” will mimic certain human-like capabilities, though not fully replicating human cognition, earning their “Agent” designation.
The first use cases will likely be in software development, where these agents will act as intelligent platforms capable of transforming a described digital process or service into reality. They may include design, inbuilt testing, quality assurance, and the ability to learn from existing IP (e.g., “create an app with the same capabilities as X”).
4. Intelligent AI Bots Will Enhance Contact Centre Efficiency
The often-overlooked aspect of CX is the “operational side”, where Operations Managers face significant challenges in maintaining a real-time pulse on contact centre activities.
For most organisations, this remains a highly manual and reactive process. Intelligent workflow bots can revolutionise this by acting as gatekeepers, instantly identifying issues and triggering real-time corrective actions. These bots can even halt processes causing customer dissatisfaction, ensuring problems are addressed proactively.
Operational inefficiencies, such as back-office delays, unanswered emails, and slow issue containment, create constant headaches. Integrating bots into contact centre operations will significantly reduce time wasted on these inefficiencies, enhancing both employee and customer experiences.
5. Employee Experience Will Catch Up to CX Maturity
Employee experience (EX) has traditionally lagged behind CX in focus and technology investment. However, AI-powered technologies are now enabling organisations to apply CX use cases to EX efforts, using advanced data analysis, summaries, and recommendations.
AI and GenAI tools will enhance understanding of employee satisfaction and engagement while predicting churn and retention drivers.
HR teams and leaders will leverage these tools to optimise performance management and improve hiring and retention outcomes.
Additionally, organisations will begin to connect EX with financial performance, identifying key drivers of engagement and linking them to business success. This shift will position EX as a strategic priority, integral to achieving organisational goals.
Over the past year, Ecosystm has conducted extensive research, including surveys and in-depth conversations with industry leaders, to uncover the most pressing topics and trends. And unsurprisingly, AI emerged as the dominant theme. Here are some insights from our research on the Retail industry.
Click here to download ‘AI in Retail: Success Stories & Insights’ as a PDF
From personalised product recommendations to predictive analytics, AI is helping retailers deliver exceptional customer experiences and optimise their operations. However, many retailers are still grappling with the complexities of AI implementation. Those who can successfully navigate this challenge and harness the power of AI will emerge as industry leaders, driving innovation and shaping the future of retail.
Despite the challenges, Retail organisations are witnessing early AI success in these 3 areas:
- 1. Customer Experience & Engagement
- 2. Supply Chain Optimisation
- 3. Fraud & Risk Analysis
Customer Experience & Engagement
- Conversational AI. Providing real-time customer support and answering queries
- Personalisation. Offering tailored product suggestions based on customer preferences and behaviour
- Virtual Try-On. Allowing customers to visualise products in different settings using AR
“AI has helped us to refine our customer chatbots to allow for more self-service. We’ve experienced faster customer order processing and quicker resolution of issues, putting control directly in the hands of our customers.” – CX LEADER
Supply Chain Optimisation
- Inventory Management. Automating inventory management processes to ensure optimal stock levels
- Supply Chain Visibility. Monitoring and optimising supply chain operations, including logistics and distribution
- Demand Forecasting. Predicting sales and demand trends to optimise inventory and production planning
“We use AI to optimise the supply chain, saving operational costs. Digital supply chains and cloud-based tracking systems streamline operations and enhance efficiency.” – CFO
Fraud & Risk Analysis
- Fraud Detection. Identify and prevent fraudulent activities, such as online fraud and chargebacks
- Risk Assessment. Assessing risk factors associated with customer transactions and preventing losses
- Customer & Market Insights. Understanding customer behaviour, market trends, and growth opportunities
“With eCommerce as a key market force, understanding customer habits is crucial to ensuring we have the right products in stock and optimising our pricing strategy.” – COO
Southeast Asia’s banking sector is poised for significant digital transformation. With projected Net Interest Income reaching USD 148 billion by 2024, the market is ripe for continued growth. While traditional banks still hold a dominant position, digital players are making significant inroads. To thrive in this evolving landscape, financial institutions must adapt to rising customer expectations, stringent regulations, and the imperative for resilience. This will require a seamless collaboration between technology and business teams.
To uncover how banks in Southeast Asia are navigating this complex landscape and what it takes to succeed, Ecosystm engaged in in-depth conversations with senior banking executives and technology leaders as part of our research initiatives. Here are the highlights of the discussions with leaders across the region.
#1 Achieving Hyper-Personalisation Through AI
As banks strive to deliver highly personalised financial services, AI-driven models are becoming increasingly essential. These models analyse customer behaviour to anticipate needs, predict future behaviour, and offer relevant services at the right time. AI-powered tools like chatbots and virtual assistants further enhance real-time customer support.
Hyper-personalisation, while promising, comes with its challenges – particularly around data privacy and security. To deliver deeply tailored services, banks must collect extensive customer information, which raises the question: how can they ensure this sensitive data remains protected?
AI projects require a delicate balance between innovation and regulatory compliance. Regulations often serve as the right set of guardrails within which banks can innovate. However, banks – especially those with cross-border operations – must establish internal guidelines that consider the regulatory landscape of multiple jurisdictions.
#2 Beyond AI: Other Emerging Technologies
AI isn’t the only emerging technology reshaping Southeast Asian banking. Banks are increasingly adopting technologies like Robotic Process Automation (RPA) and blockchain to boost efficiency and engagement. RPA is automating repetitive tasks, such as data entry and compliance checks, freeing up staff for higher-value work. CIMB in Malaysia reports seeing a 35-50% productivity increase thanks to RPA. Blockchain is being explored for secure, transparent transactions, especially cross-border payments. The Asian Development Bank successfully trialled blockchain for faster, safer bond settlements. While AR and VR are still emerging in banking, they offer potential for enhanced customer engagement. Banks are experimenting with immersive experiences like virtual branch visits and interactive financial education tools.
The convergence of these emerging technologies will drive innovation and meet the rising demand for seamless, secure, and personalised banking services in the digital age. This is particularly true for banks that have the foresight to future-proof their tech foundation as part of their ongoing modernisation efforts. Emerging technologies offer exciting opportunities to enhance customer engagement, but they shouldn’t be used merely as marketing gimmicks. The focus must be on delivering tangible benefits that improve customer outcomes.
#3 Greater Banking-Fintech Collaboration
The digital payments landscape in Southeast Asia is experiencing rapid growth, with a projected 10% increase between 2024-2028. Digital wallets and contactless payments are becoming the norm, and platforms like GrabPay, GoPay, and ShopeePay are dominating the market. These platforms not only offer convenience but also enhance financial inclusion by reaching underbanked populations in remote areas.
The rise of digital payments has significantly impacted traditional banks. To remain relevant in this increasingly cashless society, banks are collaborating with fintech companies to integrate digital payment solutions into their services. For instance, Indonesia’s Bank Mandiri collaborated with digital credit services provider Kredivo to provide customers with access to affordable and convenient credit options.
Partnerships between traditional banks and fintechs are essential for staying competitive in the digital age, especially in areas like digital payments, data analytics, and customer experience.
While these collaborations offer opportunities, they also pose challenges. Banks must invest in advanced fraud detection, AI monitoring, and robust authentication to secure digital payments. Once banks adopt a mindset of collaboration with innovators, they can leverage numerous innovations in the cybersecurity space to address these challenges.
#4 Agile Infrastructure for an Agile Business
While the banking industry is considered a pioneer in implementing digital technologies, its approach to cloud has been more cautious. While interest remained high, balancing security and regulatory concerns with cloud agility impacted the pace. Hybrid multi-cloud environments has accelerated banking cloud adoption.
Leveraging public and private clouds optimises IT costs, offering flexibility and scalability for changing business needs. Hybrid cloud allows resource adjustments for peak demand or cost reductions off-peak. Access to cloud-native services accelerates innovation, enabling rapid application development and improved competitiveness. As the industry adopts GenAI, it requires infrastructure capable of handling vast data, massive computing power, advanced security, and rapid scalability – all strengths of hybrid cloud.
Replicating critical applications and data across multiple locations ensures disaster recovery and business continuity. A multi-cloud strategy also helps avoid vendor lock-in, diversifies cloud providers, and reduces exposure to outages.
Hybrid cloud adoption offers benefits but also presents challenges for banks. Managing the environment is complex, needing coordination across platforms and skilled personnel. Ensuring data security and compliance across on-prem and public cloud infrastructure is demanding, requiring robust measures. Network latency and performance issues can arise, making careful design and optimisation crucial. Integrating on-prem systems with public cloud services is time-consuming and needs investment in tools and expertise.
#5 Cyber Measures to Promote Customer & Stakeholder Trust
The banking sector is undergoing rapid AI-driven digital transformation, focusing on areas like digital customer experiences, fraud detection, and risk assessment. However, this shift also increases cybersecurity risks, with the majority of banking technology leaders anticipate inevitable data breaches and outages.
Key challenges include expanding technology use, such as cloud adoption and AI integration, and employee-related vulnerabilities like phishing. Banks in Southeast Asia are investing heavily in modernising infrastructure, software, and cybersecurity.
Banks must update cybersecurity strategies to detect threats early, minimise damage, and prevent lateral movement within networks.
Employee training, clear security policies, and a culture of security consciousness are critical in preventing breaches.
Regulatory compliance remains a significant concern, but banks are encouraged to move beyond compliance checklists and adopt risk-based, intelligence-led strategies. AI will play a key role in automating compliance and enhancing Security Operations Centres (SOCs), allowing for faster threat detection and response. Ultimately, the BFSI sector must prioritise cybersecurity continuously based on risk, rather than solely on regulatory demands.
Breaking Down Barriers: The Role of Collaboration in Banking Transformation
Successful banking transformation hinges on a seamless collaboration between technology and business teams. By aligning strategies, fostering open communication, and encouraging cross-functional cooperation, banks can effectively leverage emerging technologies to drive innovation, enhance customer experience, and improve efficiency.
A prime example of the power of collaboration is the success of AI initiatives in addressing specific business challenges.
This user-centric approach ensures that technology addresses real business needs.
By fostering a culture of collaboration, banks can promote continuous learning, idea sharing, and innovation, ultimately driving successful transformation and long-term growth in the competitive digital landscape.
India is undergoing a remarkable transformation across various industries, driven by rapid technological advancements, evolving consumer preferences, and a dynamic economic landscape. From the integration of new-age technologies like GenAI to the adoption of sustainable practices, industries in India are redefining their operations and strategies to stay competitive and relevant.
Here are some organisations that are leading the way.
Download ‘From Tradition to Innovation: Industry Transformation in India’ as a PDF
Redefining Customer Experience in the Financial Sector
Financial inclusion. India’s largest bank, the State Bank of India, is leading financial inclusion with its YONO app, to enhance accessibility. Initial offerings include five core banking services: cash withdrawals, cash deposits, fund transfers, balance inquiries, and mini statements, with plans to include account opening and social security scheme enrollments.
Customer Experience. ICICI Bank leverages RPA to streamline repetitive tasks, enhancing customer service with its virtual assistant, iPal, for handling queries and transactions. HDFC Bank customer preference insights to offer tailored financial solutions, while Axis Bank embraces a cloud-first strategy to digitise its platform and improve customer interfaces.
Indian banks are also collaborating with fintechs to harness new technologies for better customer experiences. YES Bank has partnered with Paisabazaar to simplify loan applications, and Canara HSBC Life Insurance has teamed up with Artivatic.AI to enhance its insurance processes via an AI-driven platform.
Improving Healthcare Access
Indian healthcare organisations are harnessing technology to enhance efficiency, improve patient experiences, and enable remote care.
Apollo Hospitals has launched an automated patient monitoring system that alerts experts to health deteriorations, enabling timely interventions through remote monitoring. Manipal Hospitals’ video consultation app reduces emergency department pressure by providing medical advice, lab report access, bill payments, appointment bookings, and home healthcare requests, as well as home medication delivery and Fitbit monitoring. Omni Hospitals has also implemented AI-based telemedicine for enhanced patient engagement and remote monitoring.
The government is also driving the improvement of healthcare access. eSanjeevani is the world’s largest government-owned telemedicine system, with the capacity to handle up to a million patients a day.
Driving Retail Agility & Consumer Engagement
India’s Retail sector, the fourth largest globally, contributes over 10% of the nation’s GDP. To stay competitive and meet evolving consumer demands, Indian retailers are rapidly adopting digital technologies, from eCommerce platforms to AI.
Omnichannel Strategies. Reliance Retail integrates physical stores with digital platforms like JioMart to boost sales and customer engagement. Tata CLiQ’s “phygital” approach merges online and offline shopping for greater convenience while Shoppers Stop uses RFID and data analytics for improved in-store experiences, online shopping, and targeted marketing.
Retail AI. Flipkart’s AI-powered shopping assistant, Flippi uses ML for conversational product discovery and intuitive guidance. BigBasket employs IoT-led AI to optimise supply chain and improve product quality.
Reshaping the Automotive Landscape
Tech innovation, from AI/ML to connected vehicle technologies, is revolutionising the Automotive sector. This shift towards software-defined vehicles and predictive supply chain management underscores the industry’s commitment to efficiency, transparency, safety, and environmental sustainability.
Maruti Suzuki’s multi-pronged approach includes collaborating with over 60 startups through its MAIL program and engaging Accenture to drive tech change. Maruti has digitised 24 out of 26 customer touchpoints, tracking every interaction to enhance customer service. In the Auto OEM space, they are shifting to software-defined vehicles and operating models.
Tata Motors is leveraging cloud, AI/ML, and IoT to enhancing efficiency, improving safety, and driving sustainability across its operations. Key initiatives include connected vehicles, automated driving, dealer management, cybersecurity, electric powertrains, sustainability, and supply chain optimisation.
Streamlining India’s Logistics Sector
India’s logistics industry is on the cusp of a digital revolution as it embraces cutting-edge technologies to streamline processes and reduce environmental impact.
Automation and Predictive Analytics. Automation is transforming warehousing operations in India, with DHL India automating sortation centres to handle 6,000 shipments per hour. Predictive analytics is reshaping logistics decision-making, with Delhivery optimising delivery routes to ensure timely service.
Sustainable Practices. The logistics sector contributes one-third of global carbon emissions. To combat this, Amazon India will convert its delivery fleet to 100% EVs by 2030 to reduce emissions and fuel costs. Blue Energy Motors is also producing 10,000 heavy-duty LNG trucks annually for zero-emission logistics.
