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.
In Australia and New Zealand, the Banking, Financial Services, and Insurance (BFSI) sector is embracing AI to redefine financial services. While the potential is vast, many organisations face roadblocks in turning AI pilots into scalable solutions. Success depends on aligning technology investments with business goals and navigating challenges such as regulatory pressures, data management, and workforce transformation.
This eBook explores how BFSI organisations in ANZ can bridge the gap between AI pilots and scalable implementations. Drawing on industry research and roundtable insights, it provides strategies to develop comprehensive AI frameworks, strengthen operational guardrails, and foster a culture of innovation.
Download eBook: Strategies for AI Excellence in ANZ BFSI Organisations
(Clicking on this link will take you to the Cognizant website where you can download the resource)
AI is revolutionising the Banking, Financial Services, and Insurance (BFSI) industries by enabling deeper customer insights, personalised recommendations, and more efficient operations. However, many organisations struggle to move beyond AI pilots. Developing a robust AI strategy, from use case identification to data governance, is essential for success. Staying ahead with emerging technologies like Generative AI presents challenges, but the rewards can be significant.
This eBook looks at the challenges and opportunities in AI adoption within ASEAN’s BFSI sectors, featuring insights from a recent executive roundtable with industry leaders.
Download eBook: Five Strategies for Achieving AI Excellence in ASEAN BFSI
(Clicking on this link will take you to the Cognizant website where you can download the resource)
Healthcare organisations manage vast amounts of data—from patient records to clinical notes. While this data has the potential to enhance care and optimise operations, fragmentation across systems limits its effectiveness.
Different providers have unique priorities: residential healthcare needs mobile access to data, while acute care hospitals focus on securing patient records. By automating repetitive tasks, staff can devote more time to improving patient outcomes.
To fully leverage healthcare data, robust management, governance, and security are essential. Modernising legacy systems and strategically adopting cloud technologies can streamline operations. Furthermore, managing the increasing number of healthcare devices requires careful planning.
Ultimately, building trust and synergy by breaking down silos, promoting data sharing, and ensuring quality and consistency is crucial for effective data use across organisations.
This eBook explores why Australian healthcare providers must prioritise their data capabilities and outlines the 5 key considerations for those seeking to build trust and data synergy.
Download ebook – Australia’s Path To Data-Informed Healthcare Excellence
(Clicking on this link will take you to the Nexon website where you can download the whitepaper)
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.
The rapid adoption of technology in India is driving a surge in demand for AI solutions across sectors like finance, education, healthcare, and agriculture. AI is revolutionising these industries by making services more efficient, personalised, and accessible. This growing dependence on AI has created a fertile ground for innovation, propelling India’s emergence as a global hub for AI startups. With over 6,200 AI startups operating in the country, India offers a dynamic and challenging landscape for entrepreneurs seeking to make a meaningful impact.
Fuelling AI Innovation: India’s Strategic Investment
Earlier this year, the government allocated USD 1.3 billion for the India AI Mission, solidifying its commitment to AI. This comprehensive program is designed to catalyse the AI innovation ecosystem within the country. At the heart of this ecosystem’s development lies the expansion of compute infrastructure, a critical resource for AI startups. By providing access to powerful computing resources, the India AI Mission is empowering startups to scale their solutions and compete on a global level.
Beyond infrastructure, the initiative focuses on fostering collaborations between academia, industry, and startups to drive R&D. By creating a supportive environment that promotes knowledge sharing and resource accessibility, the India AI Mission aims to position India as a leader in the AI landscape.
A Spotlight on Indian Startups
Driving Industry Innovation
Healthcare. India’s vibrant AI startup ecosystem is driving innovation in healthcare, with companies leveraging AI to address critical challenges and improve patient outcomes.
- Cancer-Focused AI Startups. Several startups are revolutionising cancer care with AI-driven innovations. Niramai, globally recognised for its innovation, uses AI and thermal imaging for early breast cancer detection, particularly effective in younger women and dense breast tissue. Onward Assist provides predictive analytics for oncology, helping oncologists manage patient data and improve the accuracy of cancer care decisions. Similarly, Atom360 focuses on oral cancer screening with an AI-powered app that offers quick, affordable access to critical information, enhancing oral healthcare in underserved areas.
- AI-Driven Diagnostic Solutions. AI is significantly advancing diagnostics, enhancing accuracy, and reducing misdiagnosis. SigTuple develops AI-driven diagnostic solutions for medical imaging and pathology, improving accuracy and efficiency in disease detection. Endimension Technology, incubated at IIT Bombay, develops algorithms for detecting abnormalities in medical scans, aiming to reduce misdiagnosis and radiologist workload. Tricog Health delivers AI solutions for rapid heart attack diagnosis, reducing diagnosis time and improving outcomes, especially in underserved regions.
Financial Services. Fintechs have been at the forefront of AI-led innovations, offering innovative solutions for insurance, lending, and microfinance. Artivatic uses AI to transform traditional insurance systems into digital, personalised offerings, making coverage more accessible and affordable for a broader range of consumers. ZestMoney leverages AI for digital lending, providing credit to individuals without a credit history through easy EMI plans, and enhancing financial access. Meanwhile, mPokket offers instant micro-loans to students and young professionals, addressing short-term financial needs with flexible loan options and minimal documentation.
Other Industries. Beyond healthcare and financial services, AI startups are driving innovation across various industries, tackling critical challenges. Entropik uses AI to analyse human emotions and behaviour, helping businesses gain deeper insights into consumer preferences for market research and optimising user experiences. In agriculture, Intello Labs applies AI and computer vision to assess the quality of fresh produce, reducing food waste and improving supply chain efficiency. Similarly, AgNext enhances food value chains by offering AI-driven, real-time quality assessments through its SaaS platform, promoting safety and transparency in agribusiness.
Transforming Businesses
Technology for Security & Fraud. AI startups are offering innovative solutions tailored to organisations’ needs. SpoofSense combats deepfakes and identity fraud with advanced facial liveness detection, ensuring secure user verification by distinguishing between real users and spoofed images. Eagle Eye Networks provides cloud-based video surveillance solutions, using AI to offer real-time monitoring and analytics. In the e-commerce space, ThirdWatch uses AI to detect and prevent fraud in real-time by analysing user behaviour and transaction patterns, reducing financial losses for online retailers.
Tech Development. AI startups are empowering organisations to accelerate innovation and enhance productivity. Haptik helps businesses build intelligent virtual assistants, powering chatbots and voice bots across industries to improve customer engagement. DhiWise automates the development process, enabling faster app creation by converting designs into code. Additionally, Fluid AI provides advanced AI solutions like predictive analytics and natural language processing for sectors like finance, retail, and healthcare. Mihup enhances contact centre performance with its conversation intelligence platform, while Yellow.ai enables enterprises to automate customer engagement through its GenAI-powered platform, creating seamless and scalable customer service experiences.
Empowering People
AI startups are empowering individuals by providing personalised services that enhance learning, creativity, and financial management. SuperKalam and ZuAI offer students tailored learning experiences, using AI to create interactive lessons and assessments that adapt to individual learning styles, improving student engagement and outcomes. For creative professionals, Mugafi combines AI with human mentoring to assist writers in generating ideas and developing scripts, enabling them to create intellectual property with greater efficiency. Wright Research empowers individuals to make informed financial decisions through AI-powered investment advice, while Vahan simplifies job searches for blue-collar workers by using AI to match candidates with suitable employment opportunities via WhatsApp.
Promoting ESG
AI startups are driving meaningful change by optimising processes and creating economic opportunities. Ossus Biorenewables enhances biofuel production through AI, reducing waste and increasing efficiency in renewable energy generation, while Ishitva Robotic Systems promotes sustainability by automating waste sorting and recycling, contributing to a more efficient and circular economy. Karya connects rural workers with digital tasks, offering fair wages and skills development by matching them to tasks suited to their abilities using machine learning. In agriculture, KissanAI helps farmers improve crop yields and manage resources effectively through personalised, data-driven recommendations. ElasticRun improves last-mile delivery logistics in rural areas, enabling businesses to reach underserved markets.
Conclusion
Nvidia CEO Jensen Huang noted India’s potential to become the “largest exporter of AI,” signalling vast global opportunities. India’s AI startups are at the forefront of innovation but face hurdles such as fierce competition for skilled talent, navigating complex regulations, and securing funding. With strategic focus on these challenges and the backing of initiatives like Digital India and Startup India, India’s AI ecosystem can seize emerging market opportunities, accelerate tech advancements, and make a substantial impact on the global AI landscape.
Ecosystm research reveals that organisations in India are preparing to adopt emerging technologies driven by the Digital India movement. However, enterprise tech teams are grappling with challenges in their data and AI strategies, resource optimisation, and security threats.
India’s digital journey has been nothing short of remarkable, driven by a robust Digital Public Infrastructure (DPI) framework known as the India Stack. Over the past decade, the government, in collaboration with public and private entities, has built this digital ecosystem to empower citizens, improve governance, and foster economic growth.
The India Stack is a set of open APIs and platforms that provide a foundation for large-scale public service delivery and innovation. It enables governments, businesses, startups, and developers to leverage technology to offer services to millions of Indians, especially those in underserved areas.
The India Stack is viewed as a layered infrastructure, addressing identity, payments, data, and services.
Click here to download The India Stack: A Foundation for Digital India as a PDF
Four Pillars of the Digital Stack
The four layers of India Stack include:
- Presenceless Layer. Aadhaar enables remote authentication, providing a digital ID that requires only a 12-digit number and a fingerprint or iris scan, eliminating the need for physical documents. It prevents duplicate and fake identities.
- Paperless Layer. Reliance on digital records, using Aadhaar eKYC, eSign, and Digital Locker. It enables secure digital storage and retrieval, creating a paperless system for verifying and accessing documents anytime, on any device.
- Cashless Layer. Led by NPCI, this aims to universalise digital payments. UPI enables instant, secure money transfers between bank accounts using a simple Virtual Payment Address (VPA), moving transactions into the digital age for transparency and ease of use.
- Consent Layer. Enables secure, user-controlled data sharing through electronic consent, allowing data to flow freely. The Account Aggregator ecosystem benefits most, with AA acting as a thin data aggregation layer between Financial Information Providers (FIPs) and Financial Information Users (FIUs).
The Impact of the India Stack
The India Stack has played a pivotal role in the country’s rapid digitalisation:
Financial Inclusion. Aadhaar-enabled payment systems (AePS) and UPI have significantly expanded financial access, increasing inclusion from 25% in 2008 to 80% in 2024, particularly benefiting rural and underserved communities.
Boost to Digital Payments. The India Stack has fuelled exponential growth in digital payments, with UPI processing 10 billion monthly transactions. This has driven the rise of digital wallets, fintech platforms, and digitisation of small businesses.
Better Government Services. Aadhaar authentication has improved the delivery of government schemes like Direct Benefit Transfers (DBTs), Public Distribution System (PDS), and pensions, ensuring transparency and reducing leakages.
The India Stack: A Catalyst for Startup Success
The India Stack is fuelling startup innovation by providing a robust digital infrastructure. It enables entrepreneurs to build services like digital payments, eCommerce, and financial solutions for underserved populations. Platforms such as Aadhaar and UPI have paved the way for businesses to offer secure, seamless transactions, allowing startups like Paytm and BharatPe to thrive. These innovations are driving financial inclusion, empowering rural entrepreneurs, and creating opportunities in sectors like lending and healthtech, supported by global and domestic investments.
From Local Success to Global Inspiration
The impact of the India Stack’s success is being felt worldwide. Global giants such as Google Pay, WhatsApp, and Amazon Pay are drawing inspiration from it to enhance their global payment systems. Alphabet CEO Sundar Pichai plans to apply lessons from Google Pay’s Indian experience to other markets.
While India Stack has achieved significant success, there is still room for improvement. Strengthening data privacy and security is crucial as personal data collection continues to expand. The Digital Personal Data Protection Act aims to address these issues, but balancing innovation with privacy protection remains a challenge.
Bridging the digital divide by expanding Internet access and improving digital literacy, especially for rural and older populations, is key to ensuring that everyone can benefit from the India Stack’s advantages.
At a recently held Ecosystm roundtable, in partnership with Qlik and 121Connects, Ecosystm Principal Advisor Manoj Chugh, moderated a conversation where Indian tech and data leaders discussed building trust in data strategies. They explored ways to automate data pipelines and improve governance to drive better decisions and business outcomes. Here are the key takeaways from the session.
Data isn’t just a byproduct anymore; it’s the lifeblood of modern businesses, fuelling informed decisions and strategic growth. But with vast amounts of data, the challenge isn’t just managing it; it’s building trust. AI, once a beacon of hope, is now at risk without a reliable data foundation. Ecosystm research reveals that a staggering 66% of Indian tech leaders doubt their organisation’s data quality, and the problem of data silos is exacerbating this trust crisis.
At the Leaders Roundtable in Mumbai, I had the opportunity to moderate a discussion among data and digital leaders on the critical components of building trust in data and leveraging it to drive business value. The consensus was that building trust requires a comprehensive strategy that addresses the complexities of data management and positions the organisation for future success. Here are the key strategies that are essential for achieving these goals.
1. Adopting a Unified Data Approach
Organisations are facing a growing wave of complex workloads and business initiatives. To manage this expansion, IT teams are turning to multi-cloud, SaaS, and hybrid environments. However, this diverse landscape introduces new challenges, such as data silos, security vulnerabilities, and difficulties in ensuring interoperability between systems.
A unified data strategy is crucial to overcome these challenges. By ensuring platform consistency, robust security, and seamless data integration, organisations can simplify data management, enhance security, and align with business goals – driving informed decisions, innovation, and long-term success.
Real-time data integration is essential for timely data availability, enabling organisations to make data-driven decisions quickly and effectively. By integrating data from various sources in real-time, businesses can gain valuable insights into their operations, identify trends, and respond to changing market conditions.
Organisations that are able to integrate their IT and operational technology (OT) systems find their data accuracy increasing. By combining IT’s digital data management expertise with OT’s real-time operational insights, organisations can ensure more accurate, timely, and actionable data. This integration enables continuous monitoring and analysis of operational data, leading to faster identification of errors, more precise decision-making, and optimised processes.
2. Enhancing Data Quality with Automation and Collaboration
As the volume and complexity of data continue to grow, ensuring high data quality is essential for organisations to make accurate decisions and to drive trust in data-driven solutions. Automated data quality tools are useful for cleansing and standardising data to eliminate errors and inconsistencies.
As mentioned earlier, integrating IT and OT systems can help organisations improve operational efficiency and resilience. By leveraging data-driven insights, businesses can identify bottlenecks, optimise workflows, and proactively address potential issues before they escalate. This can lead to cost savings, increased productivity, and improved customer satisfaction.
However, while automation technologies can help, organisations must also invest in training employees in data management, data visualisation, and data governance.
3. Modernising Data Infrastructure for Agility and Innovation
In today’s fast-paced business landscape, agility is paramount. Modernising data infrastructure is essential to remain competitive – the right digital infrastructure focuses on optimising costs, boosting capacity and agility, and maximising data leverage, all while safeguarding the organisation from cyber threats. This involves migrating data lakes and warehouses to cloud platforms and adopting advanced analytics tools. However, modernisation efforts must be aligned with specific business goals, such as enhancing customer experiences, optimising operations, or driving innovation. A well-modernised data environment not only improves agility but also lays the foundation for future innovations.
Technology leaders must assess whether their data architecture supports the organisation’s evolving data requirements, considering factors such as data flows, necessary management systems, processing operations, and AI applications. The ideal data architecture should be tailored to the organisation’s specific needs, considering current and future data demands, available skills, costs, and scalability.
4. Strengthening Data Governance with a Structured Approach
Data governance is crucial for establishing trust in data, and providing a framework to manage its quality, integrity, and security throughout its lifecycle. By setting clear policies and processes, organisations can build confidence in their data, support informed decision-making, and foster stakeholder trust.
A key component of data governance is data lineage – the ability to trace the history and transformation of data from its source to its final use. Understanding this journey helps organisations verify data accuracy and integrity, ensure compliance with regulatory requirements and internal policies, improve data quality by proactively addressing issues, and enhance decision-making through context and transparency.
A tiered data governance structure, with strategic oversight at the executive level and operational tasks managed by dedicated data governance councils, ensures that data governance aligns with broader organisational goals and is implemented effectively.
Are You Ready for the Future of AI?
The ultimate goal of your data management and discovery mechanisms is to ensure that you are advancing at pace with the industry. The analytics landscape is undergoing a profound transformation, promising to revolutionise how organisations interact with data. A key innovation, the data fabric, is enabling organisations to analyse unstructured data, where the true value often lies, resulting in cleaner and more reliable data models.
GenAI has emerged as another game-changer, empowering employees across the organisation to become citizen data scientists. This democratisation of data analytics allows for a broader range of insights and fosters a more data-driven culture. Organisations can leverage GenAI to automate tasks, generate new ideas, and uncover hidden patterns in their data.
The shift from traditional dashboards to real-time conversational tools is also reshaping how data insights are delivered and acted upon. These tools enable users to ask questions in natural language, receiving immediate and relevant answers based on the underlying data. This conversational approach makes data more accessible and actionable, empowering employees to make data-driven decisions at all levels of the organisation.
To fully capitalise on these advancements, organisations need to reassess their AI/ML strategies. By ensuring that their tech initiatives align with their broader business objectives and deliver tangible returns on investment, organisations can unlock the full potential of data-driven insights and gain a competitive edge. It is equally important to build trust in AI initiatives, through a strong data foundation. This involves ensuring data quality, accuracy, and consistency, as well as implementing robust data governance practices. A solid data foundation provides the necessary groundwork for AI and GenAI models to deliver reliable and valuable insights.
