The Manufacturing sector, traditionally defined by stable processes and infrastructure, is now facing a pivotal shift. Rapid technological advancements and shifting global market dynamics have rendered incremental improvements inadequate for long-term competitiveness and growth. To thrive, manufacturers must fundamentally reimagine their entire value chain.
By embracing intelligent systems, enhancing agility, and proactively shaping future-ready operations, organisations can navigate today’s industrial complexities and position themselves for sustained success.
Here are recent examples of Manufacturing transformation in the Asia Pacific.
Click here to download “Future Forward: Reimagining Manufacturing” as a PDF.
Intelligent Automation & Efficiency
Komatsu Australia, a global industrial equipment manufacturer, tackled growing inefficiencies in its small parts department, where teams manually processed hundreds of PDF invoices daily from more than 250 suppliers.
To streamline this, the company deployed intelligent automation – AI now extracts and validates data from invoices against purchase orders and inputs it directly into the legacy mainframe.
The impact has been sharp: over 300 hours saved annually for one supplier, 1,100 invoices processed in three weeks, and a dramatic drop in manual errors. Employees have shifted to higher-value tasks, and a citizen developer program is enabling staff to build custom automation tools. With a scalable framework in place, Komatsu has not only transformed invoice processing but also set the stage for broader automation across the enterprise.
Data-Driven Insights & Agility
Berger Paints India Ltd., a leader in paints and coatings, needed to scale fast amid rising database loads and complex on-prem systems.
In response, Berger Paints migrated its mission-critical databases and core business applications – covering finance, manufacturing, sales, and asset management – to a high-performance cloud platform.
This shift boosted operational efficiency by 25%, doubled reporting and system response times, and enhanced scalability and disaster recovery with geographically distributed cloud regions. The move simplified access to data, driving faster, insight-driven decision-making. With streamlined infrastructure management and optimised costs, Berger Paints is now poised to leverage advanced technologies like AI/ML, setting the stage for continued innovation and growth.
Connected Operations & Customer Centricity
JSW Steel, one of India’s leading steel producers, set out to shift from a plant-centric model to a customer-first approach. The challenge: integrating complex systems like ERP, CRM, and manufacturing to streamline operations and improve order fulfillment.
With a robust integration platform, JSW Steel connected over 32 systems using 120+ APIs – automating processes and enabling real-time data flow across orders, inventory, pricing, and production.
The results speak for themselves: faster order fulfillment, reduced cost-to-serve, and real-time visibility that optimises scheduling. Scalable, composable APIs now support growth, while a 99.7% success rate across 7.2 million API calls ensures reliability. JSW Steel has transformed how it operates – running faster, serving smarter, and delivering better customer experiences across the entire order-to-cash journey.
Modernising Core Systems & Foundational Transformation
Fujitsu General, a global leader in air conditioning systems, was constrained by a 30-year-old COBOL-based mainframe and fragmented processes. The legacy system posed a Y2K-like risk and limited operational agility.
The company implemented a modern, unified ERP platform to eliminate risk, streamline operations, and boost agility.
By integrating functions across sales, production, procurement, accounting, and HR and addressing unique business needs with low-code development, the company created a clean, adaptable core system. Robust integration connected disparate data sources, while a central repository eliminated silos. The transformation delivered seamless end-to-end operations, standardised workflows, improved agility, and real-time insights – setting Fujitsu General up for continued innovation and long-term resilience.
Powering Growth with a Modern Network
As a critical supplier to India’s infrastructure boom, Hindalco needed to modernise its network across 55 sites – improving app performance, enabling real-time insights, and building a future-ready, sustainable foundation.
Hindalco replaced its ageing hub-and-spoke model with a modern mesh architecture using SD-WAN.
The new architecture prioritised key app traffic, simplified cloud access, and enabled segmentation. Centralised orchestration and SSE integration brought automation and robust security. The impact: 30% lower costs, 50% faster apps, real-time visibility, rapid deployment, and smarter bandwidth. Hindalco now runs on a lean, secure digital backbone – built for agility, performance, and scale.
AI has become a battleground for geopolitical competition, national resilience, and societal transformation. The stakes are no longer theoretical, and the window for action is closing fast.
In March, the U.S. escalated its efforts to shape the global technology landscape by expanding export controls on advanced AI and semiconductor technologies. Over 80 entities – more than 50 in China – were added to the export blacklist, aiming to regulate access to critical technologies. The move seeks to limit the development of high-performance computing, quantum technologies, and AI in certain regions, citing national security concerns.
As these export controls tighten, reports have surfaced of restricted chips entering China through unofficial channels, including e-commerce platforms. U.S. authorities are working to close these gaps by sanctioning new entities attempting to circumvent the restrictions. The Department of Commerce’s Bureau of Industry and Security (BIS) is also pushing for stricter Know Your Customer (KYC) regulations for cloud service providers to limit unauthorised access to GPU resources across the Asia Pacific region.
Geopolitics & the Pursuit of AI Dominance
Bipartisan consensus has emerged in Washington around the idea that leading in artificial general intelligence (AGI) is a national security imperative. If AI is destined to shape the future balance of power, the U.S. government believes it cannot afford to fall behind. This mindset has accelerated an arms-race dynamic reminiscent of the Thucydides Trap, where the fear of being overtaken compels both sides to push ahead, even if alignment and safety mechanisms are not yet in place.
China has built extensive domestic surveillance infrastructure and has access to large volumes of data that would be difficult to collect under the regulatory frameworks of many other countries. Meanwhile, major U.S. social media platforms can refine their AI models using behavioural data from a broad global user base. AI is poised to enhance governments’ ability to monitor compliance and enforce laws that were written before the digital age – laws that previously assumed enforcement would be limited by practical constraints. This raises important questions about how civil liberties may evolve when technological limitations are no longer a barrier to enforcement.
The Digital Battlefield
Cybersecurity Threat. AI is both a shield and a sword in cybersecurity. We are entering an era of algorithm-versus-algorithm warfare, where AI’s speed and adaptability will dictate who stays secure and who gets compromised. Nations are prioritising AI for cyber defence to stay ahead of state actors using AI for attacks. For example, the DARPA AI Cyber Challenge is funding tools that use AI to identify and patch vulnerabilities in real-time – essential for defending against state-sponsored threats.
Yet, a key vulnerability exists within AI labs themselves. Many of these organisations, though responsible for cutting-edge models, operate more like startups than defence institutions. This results in informal knowledge sharing, inconsistent security standards, and minimal government oversight. Despite their strategic importance, these labs lack the same protections and regulations as traditional military research facilities.
High-Risk Domains and the Proliferation of Harm. AI’s impact on high-risk domains like biotechnology and autonomous systems is raising alarms. Advanced AI tools could lower the barriers for small groups or even individuals to misuse biological data. As Anthropic CEO Dario Amodei warns, “AI will vastly increase the number of people who can cause catastrophic harm.”
This urgency for oversight mirrors past technological revolutions. The rise of nuclear technology prompted global treaties and safety protocols, and the expansion of railroads drove innovations like block signalling and standardised gauges. With AI’s rapid progression, similar safety measures must be adopted quickly.
Meanwhile, AI-driven autonomous systems are growing in military applications. Drones equipped with AI for real-time navigation and target identification are increasingly deployed in conflict zones, especially where traditional systems like GPS are compromised. While these technologies promise faster, more precise operations, they also raise critical ethical questions about decision-making, accountability, and latency.
The 2024 National Security Memorandum on AI laid down initial guidelines for responsible AI use in defence. However, significant challenges remain around enforcement, transparency, and international cooperation.
AI for Intelligence and Satellite Analysis. AI also holds significant potential for national intelligence. Governments collect massive volumes of satellite imagery daily – far more than human analysts can process alone. AI models trained on geospatial data can greatly enhance the ability to detect movement, monitor infrastructure, and improve border security. Companies like ICEYE and Satellogic are advancing their computer vision capabilities to increase image processing efficiency and scale. As AI systems improve at identifying patterns and anomalies, each satellite image becomes increasingly valuable. This could drive a new era of digital intelligence, where AI capabilities become as critical as the satellites themselves.
Policy, Power, and AI Sovereignty
Around the world, governments are waking up to the importance of AI sovereignty – ensuring that critical capabilities, infrastructure, and expertise remain within national borders. In Europe, France has backed Mistral AI as a homegrown alternative to US tech giants, part of a wider ambition to reduce dependency and assert digital independence. In China, DeepSeek has gained attention for developing competitive LLMs using relatively modest compute resources, highlighting the country’s determination to lead without relying on foreign technologies.
These moves reflect a growing recognition that in the AI age, sovereignty doesn’t just mean political control – it also means control over compute, data, and talent.
In the US, the public sector is working to balance oversight with fostering innovation. Unlike the internet, the space program, or the Manhattan Project, the AI revolution was primarily initiated by the private sector, with limited state involvement. This has left the public sector in a reactive position, struggling to keep up. Government processes are inherently slow, with legislation, interagency reviews, and procurement cycles often lagging rapid technological developments. While major AI breakthroughs can happen within months, regulatory responses may take years.
To address this gap, efforts have been made to establish institutions like the AI Safety Institute and requiring labs to share their internal safety evaluations. However, since then, there has been a movement to reduce the regulatory burden on the AI sector, emphasising the importance of supporting innovation over excessive caution.
A key challenge is the need to build both policy frameworks and physical infrastructure in tandem. Advanced AI models require significant computational resources, and by extension, large amounts of energy. As countries like the US and China compete to be at the forefront of AI innovation, ensuring a reliable energy supply for AI infrastructure becomes crucial.
If data centres cannot scale quickly or if clean energy becomes too expensive, there is a risk that AI infrastructure could migrate to countries with fewer regulations and lower energy costs. Some nations are already offering incentives to attract these capabilities, raising concerns about the long-term security of critical systems. Governments will need to carefully balance sovereignty over AI infrastructure with the development of sufficient domestic electricity generation capacity, all while meeting sustainability goals. Without strong partnerships and more flexible policy mechanisms, countries may risk ceding both innovation and governance to private actors.
What Lies Ahead
AI is no longer an emerging trend – it is a cornerstone of national power. It will shape not only who leads in innovation but also who sets the rules of global engagement: in cyber conflict, intelligence gathering, economic dominance, and military deterrence. The challenge governments face is twofold. First, to maintain strategic advantage, they must ensure that AI development – across private labs, defence systems, and public infrastructure – remains both competitive and secure. Second, they must achieve this while safeguarding democratic values and civil liberties, which are often the first to erode under unchecked surveillance and automation.
This isn’t just about faster processors or smarter algorithms. It’s about determining who defines the future – how decisions are made, who has oversight, and what values are embedded in the systems that will govern our lives.
Ecosystm research shows that cybersecurity is the most discussed technology at the Board and Management level, driven by the increasing sophistication of cyber threats and the rapid adoption of AI. While AI enhances security, it also introduces new vulnerabilities. As organisations face an evolving threat landscape, they are adopting a more holistic approach to cybersecurity, covering prevention, detection, response, and recovery.
In 2025, cybersecurity leaders will continue to navigate a complex mix of technological advancements, regulatory pressures, and changing business needs. To stay ahead, organisations will prioritise robust security solutions, skilled professionals, and strategic partnerships.
Ecosystm analysts Darian Bird, Sash Mukherjee, and Simona Dimovski present the key cybersecurity trends for 2025.
Click here to download ‘Securing the AI Frontier: Top 5 Cyber Trends for 2025’ as a PDF
1. Cybersecurity Will Be a Critical Differentiator in Corporate Strategy
The convergence of geopolitical instability, cyber weaponisation, and an interconnected digital economy will make cybersecurity a cornerstone of corporate strategy. State-sponsored cyberattacks targeting critical infrastructure, supply chains, and sensitive data have turned cyber warfare into an operational reality, forcing businesses to prioritise security.
Regulatory pressures are driving this shift, mandating breach reporting, data sovereignty, and significant penalties, while international cybersecurity norms compel companies to align with evolving standards to remain competitive.
The stakes are high. Stakeholders now see cybersecurity as a proxy for trust and resilience, scrutinising both internal measures and ecosystem vulnerabilities.
2. Zero Trust Architectures Will Anchor AI-Driven Environments
The future of cybersecurity lies in never trusting, always verifying – especially where AI is involved.
In 2025, the rise of AI-driven systems will make Zero Trust architectures vital for cybersecurity. Unlike traditional networks with implicit trust, AI environments demand stricter scrutiny due to their reliance on sensitive data, autonomous decisions, and interconnected systems. The growing threat of adversarial attacks – data poisoning, model inversion, and algorithmic manipulation – highlights the urgency of continuous verification.
Global forces are driving this shift. Regulatory mandates like the EU’s DORA, the US Cybersecurity Executive Order, and the NIST Zero Trust framework call for robust safeguards for critical systems. These measures align with the growing reliance on AI in high-stakes sectors like Finance, Healthcare, and National Security.
3. Organisations Will Proactively Focus on AI Governance & Data Privacy
Organisations are caught between excitement and uncertainty regarding AI. While the benefits are immense, businesses struggle with the complexities of governing AI. The EU AI Act looms large, pushing global organisations to brace for stricter regulations, while a rise in shadow IT sees business units bypassing traditional IT to deploy AI independently.
In this environment of regulatory ambiguity and organisational flux, CISOs and CIOs will prioritise data privacy and governance, proactively securing organisations with strong data frameworks and advanced security solutions to stay ahead of emerging regulations.
Recognising that AI will be multi-modal, multi-vendor, and hybrid, organisations will invest in model orchestration and integration platforms to simplify management and ensure smoother compliance.
4. Network & Security Stacks Will Streamline Through Converged Platforms
This shift stems from the need for unified management, cost efficiency, and the recognition that standardisation enhances security posture.
Tech providers are racing to deliver comprehensive network and security platforms.
Recent M&A moves by HPE (Juniper), Palo Alto Networks (QRadar SaaS), Fortinet (Lacework), and LogRhythm (Exabeam) highlight this trend. Rising player Cato Networks is capitalising on mid-market demand for single-provider solutions, with many customers planning to consolidate vendors in their favour. Meanwhile, telecoms are expanding their SASE offerings to support organisations adapting to remote work and growing cloud adoption.
5. AI Will Be Widely Used to Combat AI-Powered Threats in Real-time
By 2025, the rise of AI-powered cyber threats will demand equally advanced AI-driven defences.
Threat actors are using AI to launch adaptive attacks like deepfake fraud, automated phishing, and adversarial machine learning, operating at a speed and scale beyond traditional defences.
Real-time AI solutions will be essential for detection and response.
Nation-state-backed advanced persistent threat (APT) groups and GenAI misuse are intensifying these challenges, exploiting vulnerabilities in critical infrastructure and supply chains. Mandatory reporting and threat intelligence sharing will strengthen AI defences, enabling real-time adaptation to emerging threats.
Cybersecurity is essential to every organisation’s resilience, yet it often fails to resonate with business leaders focused on growth, innovation, and customer satisfaction. The challenge lies in connecting cybersecurity with these strategic goals. To bridge this gap, it is important to shift from a purely technical view of cybersecurity to one that aligns directly with business objectives.
Here are 5 impactful strategies to make cybersecurity relevant and valuable at the executive level.
1. Elevate Cybersecurity as a Pillar of Business Continuity
Cybersecurity is not just a defensive strategy; it is a proactive investment in business continuity and success. Leaders who see cybersecurity as foundational to business continuity protect more than just digital assets – they safeguard brand reputation, customer trust, and operational resilience. By framing cybersecurity as essential to keeping the business running smoothly, leaders can shift the focus from reactive problem-solving to proactive resilience planning.
For example, rather than viewing cybersecurity incidents as isolated IT issues, organisations should see them as risks that could disrupt critical business functions, halt operations, and destroy customer loyalty. By integrating cybersecurity into continuity planning, executives can ensure that security aligns with growth and operational stability, reinforcing the organisation’s ability to adapt and thrive in a constantly evolving threat landscape.
2. Translate Cyber Risks into Business-Relevant Insights
To make cybersecurity resonate with business leaders, technical risks need to be expressed in terms that directly impact the organisation’s strategic goals. Executives are more likely to respond to cybersecurity concerns when they understand the financial, reputational, or operational impacts of cyber threats. Reframing cybersecurity risks into clear, business-oriented language that highlights potential disruptions, regulatory implications, and costs helps leadership see cybersecurity as part of broader risk management.
For instance, rather than discussing a “data breach vulnerability”, frame it as a “threat to customer trust and a potential multi-million-dollar regulatory liability”. This approach contextualises cyber risks in terms of real-world consequences, helping leadership to recognise that cybersecurity investments are risk mitigations that protect revenue, brand equity, and shareholder value.
3. Build Cybersecurity into the DNA of Innovation and Product Development
Cybersecurity must be a foundational element in the innovation process, not an afterthought. When security is integrated from the early stages of product development – known as “shifting left” – organisations can reduce vulnerabilities, build customer trust, and avoid costly fixes post-launch. This approach helps businesses to innovate with confidence, knowing that new products and services meet both customer expectations and regulatory requirements.
By embedding security in every phase of the development lifecycle, leaders demonstrate that cybersecurity is essential to sustainable innovation. This shift also empowers product teams to create solutions that are both user-friendly and secure, balancing customer experience with risk management. When security is seen as an enabler rather than an obstacle to innovation, it becomes a powerful differentiator that supports growth.
4. Foster a Culture of Shared Responsibility and Continuous Learning
The most robust cybersecurity strategies extend beyond the IT department, involving everyone in the organisation. Creating a culture where cybersecurity is everyone’s responsibility ensures that each employee – from the front lines to the boardroom – understands their role in protecting the organisation. This culture is built through continuous education, regular simulations, and immersive training that makes cybersecurity practical and engaging.
Awareness initiatives, such as cyber escape rooms and live demonstrations of common attacks, can be powerful tools to engage employees. Instead of passive training, these methods make cybersecurity tangible, showing employees how their actions impact the organisation’s security posture. By treating cybersecurity as an organisation-wide effort, leaders build a proactive culture that treats security not as an obligation but as an integral part of the business mission.
5. Leverage Industry Partnerships and Regulatory Compliance for a Competitive Edge
As regulations around cybersecurity tighten, especially for critical sectors like finance and infrastructure, compliance is becoming a competitive advantage. By proactively meeting and exceeding regulatory standards, organisations can position themselves as trusted, compliant partners for clients and customers. Additionally, building partnerships across the public and private sectors offers access to shared knowledge, best practices, and support systems that strengthen organisational security.
Leaders who engage with regulatory requirements and industry partnerships not only stay ahead of compliance but also benefit from a network of resources that can enhance their cybersecurity strategies. Proactive compliance, combined with strategic partnerships, strengthens organisational resilience and builds market trust. In doing so, cybersecurity becomes more than a safeguard; it’s an asset that supports brand credibility, customer loyalty, and competitive differentiation.
Conclusion
For cybersecurity to be truly effective, it must be woven into the fabric of an organisation’s mission and strategy. By reframing cybersecurity as a foundational aspect of business continuity, expressing cyber risks in business language, embedding security in innovation, building a culture of shared responsibility, and leveraging compliance as an advantage, leaders can transform cybersecurity from a technical concern to a strategic asset. In an age where digital threats are increasingly complex, aligning cybersecurity with business priorities is essential for sustainable growth, customer trust, and long-term resilience.
At the Nutanix .NEXT 2024 event in Barcelona, it became clear that the discourse around cloud computing has evolved significantly. The debate that once polarised organisations over whether on-prem/co-located data centres or public cloud was better has been decisively settled. Both cloud providers and on-prem equipment providers are thriving, as evident from their earnings reports.
Hybrid cloud has emerged as the clear victor, offering the flexibility and control that organisations demand. This shift is particularly relevant for tech buyers in the Asia Pacific region, where diverse market maturities and unique business challenges require a more adaptable approach to IT infrastructure.
The Hybrid Cloud Advantage
Hybrid cloud architecture combines the best of both worlds. It provides the scalability and agility of public cloud services while retaining the control and security of on-prem systems. For Asia Pacific organisations, that often operate across various regulatory environments and face unique data sovereignty issues, this dual capability is invaluable. The ability to seamlessly move workloads between on-prem, private cloud, and public cloud environments enables enterprises to optimise their IT strategies, balancing cost, performance, and compliance.
Market Maturity and Adoption in Asia Pacific
The region shows a wide spectrum of technological maturity among its markets. Countries like Australia, Japan, and Singapore lead with advanced cloud adoption and robust IT infrastructures, while emerging markets such as Vietnam, Indonesia, and the Philippines are still in the nascent stages of cloud integration.
However, regardless of their current maturity levels, organisations in Asia Pacific are recognising the benefits of a hybrid cloud approach. Mature markets are leveraging hybrid cloud to refine their IT strategies, focusing on enhancing business agility and driving innovation.
Ecosystm research shows that 75% of organisations in Australia have a hybrid, multi-cloud strategy. Over 30% of organisations have repatriated workloads from the public cloud, and only 22% employ a “cloud first” strategy when deploying new services.
Meanwhile, emerging markets see hybrid cloud as a pathway to accelerate their digital transformation journeys without the need for extensive upfront investments in on-prem infrastructure. Again, Ecosystm data shows that when it comes to training large AI models and applications, organisations across Southeast Asia use a mix of public, private, hybrid, and multi-cloud environments.
Strategic Flexibility Without Compromise
One of the most compelling messages from the Nutanix .NEXT 2024 event is that hybrid cloud eliminates the need for compromise when deciding where to place workloads – and that is what the data above represents. The location of the workload is no longer a limiting factor. Being “cloud first” locks organisations into a tech provider, whereas agility was once exclusively in favour of public cloud providers. Whether it’s for performance optimisation, cost efficiency, or regulatory compliance, tech leaders can now choose the best environment for every workload without being constrained by location.
For example, an organisation might keep sensitive customer data within a private cloud to comply with local data protection laws while leveraging public cloud resources for less sensitive applications to take advantage of its scalability and cost benefits. I recently spoke to an organisation in the gaming space that had 5 different regulatory bodies to appease – which required data to be stored in 5 different locations! This strategic flexibility ensures that IT investments are fully aligned with business objectives, enhancing overall operational efficiency.
Moving Forward: Actionable Insights for Asia Pacific Tech Leaders
To fully capitalise on the hybrid cloud revolution, APAC tech leaders should:
- Assess Workload Requirements. Evaluate the specific needs of each workload to determine the optimal environment, considering factors like latency, security, and compliance.
- Invest in Integration Tools. Ensure seamless interoperability between on-premises and cloud environments by investing in advanced integration and management tools.
- Focus on Skill Development. Equip IT teams with the necessary skills to manage hybrid cloud infrastructures, emphasising continuous learning and certification.
- Embrace a Multi-Cloud Strategy. Consider a multi-cloud approach within the hybrid model to avoid vendor lock-in and enhance resilience.
Conclusion
The hybrid cloud has definitively won the battle for enterprise IT infrastructure, particularly in the diverse Asia Pacific region. By enabling organisations to place their workloads wherever they make the most sense without compromising on performance, security, or compliance, hybrid cloud empowers tech leaders to drive their digital transformation agendas forward with confidence. Based on everything we know today*, the future of cloud is hybrid. Reform your sourcing practices to put business needs, not cloud service providers or data centres, at the centre of your data decisions.
*In this fast-changing world, it seems naïve to make sweeping statements about the future of technology!
In my previous blogs, I outlined strategies for public sector organisations to incorporate technology into citizen services and internal processes. Building on those perspectives, let’s talk about the critical role of data in powering digital transformation across the public sector.
Effectively leveraging data is integral to delivering enhanced digital services and streamlining operations. Organisations must adopt a forward-looking roadmap that accounts for different data maturity levels – from core data foundations and emerging catalysts to future-state capabilities.
1. Data Essentials: Establishing the Bedrock
Data model. At the core of developing government e-services portals, strategic data modelling establishes the initial groundwork for scalable data infrastructures that can support future analytics, AI, and reporting needs. Effective data models define how information will be structured and analysed as data volumes grow. Beginning with an Entity-Relationship model, these blueprints guide the implementation of database schemas within database management systems (DBMS). This foundational approach ensures that the data infrastructure can accommodate the vast amounts of data generated by public services, crucial for maintaining public trust in government systems.
Cloud Databases. Cloud databases provide flexible, scalable, and cost-effective storage solutions, allowing public sector organisations to handle vast amounts of data generated by public services. Data warehouses, on the other hand, are centralised repositories designed to store structured data, enabling advanced querying and reporting capabilities. This combination allows for robust data analytics and AI-driven insights, ensuring that the data infrastructure can support future growth and evolving analytical needs.
Document management. Incorporating a document or records management system (DMS/RMS) early in the data portfolio of a government e-services portal is crucial for efficient operations. This system organises extensive paperwork and records like applications, permits, and legal documents systematically. It ensures easy storage, retrieval, and management, preventing issues with misplaced documents.
Emerging Catalysts: Unleashing Data’s Potential
Digital Twins. A digital twin is a sophisticated virtual model of a physical object or system. It surpasses traditional reporting methods through advanced analytics, including predictive insights and data mining. By creating detailed virtual replicas of infrastructure, utilities, and public services, digital twins allow for real-time monitoring, efficient resource management, and proactive maintenance. This holistic approach contributes to more efficient, sustainable, and livable cities, aligning with broader goals of urban development and environmental sustainability.
Data Fabric. Data Fabric, including Data Lakes and Data Lakehouses, represents a significant leap in managing complex data environments. It ensures data is accessible for various analyses and processing needs across platforms. Data Lakes store raw data in its original format, crucial for initial data collection when future data uses are uncertain. In Cloud DB or Data Fabric setups, Data Lakes play a foundational role by storing unprocessed or semi-structured data. Data Lakehouses combine Data Lakes’ storage with data warehouses’ querying capabilities, offering flexibility, and efficiency for handling different types of data in sophisticated environments.
Data Exchange and MOUs. Even with advanced data management technologies like data fabrics, Data Lakes, and Data Lakehouses, achieving higher maturity in digital government ecosystems often depends on establishing data-sharing agreements. Memorandums of Understanding (MoUs) exemplify these agreements, crucial for maximising efficiency and collaboration. MoUs outline terms, conditions, and protocols for sharing data beyond regulatory requirements, defining its scope, permitted uses, governance standards, and responsibilities of each party. This alignment ensures data integrity, privacy, and security while facilitating collaboration that enhances innovation and service delivery. Such agreements also pave the way for potential commercialisation of shared data resources, opening new market opportunities.
Future-Forward Capabilities: Pioneering New Frontiers
Data Mesh. Data Mesh is a decentralised approach to data architecture and organisational design, ideal for complex stakeholder ecosystems like digital conveyancing solutions. Unlike centralised models, Data Mesh allows each domain to manage its data independently. This fosters collaboration while ensuring secure and governed data sharing, essential for efficient conveyancing processes. Data Mesh enhances data quality and relevance by holding stakeholders directly accountable for their data, promoting integrity and adaptability to market changes. Its focus on interoperability and self-service data access enhances user satisfaction and operational efficiency, catering flexibly to diverse user needs within the conveyancing ecosystem.
Data Embassies. A Data Embassy stores and processes data in a foreign country under the legal jurisdiction of its origin country, beneficial for digital conveyancing solutions serving international markets. This approach ensures data security and sovereignty, governed by the originating nation’s laws to uphold privacy and legal integrity in conveyancing transactions. Data Embassies enhance resilience against physical and cyber threats by distributing data across international locations, ensuring continuous operation despite disruptions. They also foster international collaboration and trust, potentially attracting more investment and participation in global real estate markets. Technologically, Data Embassies rely on advanced data centres, encryption, cybersecurity, cloud, and robust disaster recovery solutions to maintain uninterrupted conveyancing services and compliance with global standards.
Conclusion
By developing a cohesive roadmap that progressively integrates cutting-edge architectures, cross-stakeholder partnerships, and avant-garde juridical models, agencies can construct a solid data ecosystem. One where information doesn’t just endure disruption, but actively facilitates organisational resilience and accelerates mission impact. Investing in an evolutionary data strategy today lays the crucial groundwork for delivering intelligent, insight-driven public services for decades to come. The time to fortify data’s transformative potential is now.
We spoke about what public sector agencies should consider when building citizen-centric services. Integrating technology into organisational processes requires a similarly strategic approach that considers immediate needs, emerging enablers, and futuristic innovations.
Here is a comprehensive look at what public sector organisations should consider when integrating technology into processes.
1. Process Essentials: Laying the Groundwork
The immediate view focuses on deploying technologies that are widely adopted and essential for current digital service provision. These foundational technologies serve as the backbone for enhancing process efficiency.
- Code. At the most basic level, the foundation is built on code – the programming languages and frameworks used to create digital services. This includes technologies like HTML, CSS, JavaScript, Java, Python, etc. A typical approach is to have a front-end web layer for the user interface and a back-end application layer for processing.
- Monolithic ERP. These systems are also crucial, especially in the early stages. These integrated software suites help manage core functions like customer management and document handling. They provide comprehensive, pre-built solutions that can be customised to specific needs. ERPs enable organisations to effectively manage complex processes from the start.
2. Emerging Catalysts: Accelerating Processes
As organisations establish foundational technologies, they should look towards second-generation enablers. Although less mature, these technologies offer emerging digital opportunities, and can significantly enhance service differentiation, through improved processes.
- PaaS. As digital services mature, organisations can leverage platform-as-a-service (PaaS) solutions hosted in the cloud. PaaS provides greater scalability, flexibility, and reduced infrastructure management overhead compared to custom development approaches. Adopting a microservices architecture on PaaS allows for developing independent components that can be updated independently, promoting continuous improvement. This modern, modular approach is highly efficient.
- Low Code/ No Code. LC/NC platforms further simplify application development by providing intuitive, visual tools that don’t require extensive coding expertise. They build on PaaS capabilities while minimising the need for deep technical skills. These environments also facilitate collaboration by enabling partners and third-parties to easily create custom solutions that integrate with the organisation’s systems. This spurs innovation through an ecosystem of complementary apps and services.
3. Future-Forward Capabilities: Next-Gen Processes
The futuristic view focuses on forward-looking technologies that address long-term roadblocks and offer transformative potential. These technologies are currently speculative but hold the promise of significantly reshaping the market.
- Complex RPA and ML. Robotic process automation (RPA) and machine learning take technological maturity to the next level by automating routine tasks and optimising decision-making through intelligent algorithms. The integration of RPA with machine learning goes beyond simple automation to enable more complex, data-driven decision processes across the workflow. Analysts predict that by 2025, up to 50% of work could be automated this way, drastically improving efficiency.
- Enterprise-Wide Microservices Architecture. An enterprise-wide microservices architecture represents an advanced approach suitable for collaboration between agencies, technical service providers, and partners. Each microservice is designed to be independently deployable, testable, and focused on specific capabilities. This decentralised model allows services to be updated or replaced without disrupting the entire system, enhancing resilience. On a PaaS platform, it enables an agile, scalable approach aligned with modern e-government needs.
- Industry Cloud. The Industry Cloud is essentially a highly configurable PaaS solution, designed to meet the specific needs of not just one government agency or jurisdiction, but with adaptability for broader use.
Ecosystm Opinion
A comprehensive roadmap should outline how to build upon current process foundations with emerging catalysts like cloud platforms and low-code development, while actively preparing for future-forward capabilities around automation, microservices architectures, and industry cloud solutions.
By taking a long-term, systematic approach to integrating technology at every stage of the process lifecycle, agencies can cultivate an adaptable digital process ecosystem that continually evolves in lockstep with technological innovation. The goal is to foster processes that don’t just endure disruption, but fundamentally improve because of it – cementing organisational resilience and agility for decades to come.
2024 will be another crucial year for tech leaders – through the continuing economic uncertainties, they will have to embrace transformative technologies and keep an eye on market disruptors such as infrastructure providers and AI startups. Ecosystm analysts outline the key considerations for leaders shaping their organisations’ tech landscape in 2024.
Navigating Market Dynamics
Continuing Economic Uncertainties. Organisations will focus on ongoing projects and consider expanding initiatives in the latter part of the year.
Popularity of Generative AI. This will be the time to go beyond the novelty factor and assess practical business outcomes, allied costs, and change management.
Infrastructure Market Disruption. Keeping an eye out for advancements and disruptions in the market (likely to originate from the semiconductor sector) will define vendor conversations.
Need for New Tech Skills. Generative AI will influence multiple tech roles, including AIOps and IT Architecture. Retaining talent will depend on upskilling and reskilling.
Increased Focus on Governance. Tech vendors are guide tech leaders on how to implement safeguards for data usage, sharing, and cybersecurity.
5 Key Considerations for Tech Leaders
#1 Accelerate and Adapt: Streamline IT with a DevOps Culture
Over the next 12-18 months, advancements in AI, machine learning, automation, and cloud-native technologies will be vital in leveraging scalability and efficiency. Modernisation is imperative to boost responsiveness, efficiency, and competitiveness in today’s dynamic business landscape.
The continued pace of disruption demands that organisations modernise their applications portfolios with agility and purpose. Legacy systems constrained by technical debt drag down velocity, impairing the ability to deliver new innovative offerings and experiences customers have grown to expect.
Prioritising modernisation initiatives that align with key value drivers is critical. Technology leaders should empower development teams to move beyond outdated constraints and swiftly deploy enhanced applications, microservices, and platforms.
#2 Empowering Tomorrow: Spring Clean Your Tech Legacy for New Leaders
Modernising legacy systems is a strategic and inter-generational shift that goes beyond simple technical upgrades. It requires transformation through the process of decomposing and replatforming systems – developed by previous generations – into contemporary services and signifies a fundamental realignment of your business with the evolving digital landscape of the 21st century.
The essence of this modernisation effort is multifaceted. It not only facilitates the integration of advanced technologies but also significantly enhances business agility and drives innovation. It is an approach that prepares your organisation for impending skill gaps, particularly as the older workforce begins to retire over the next decade. Additionally, it provides a valuable opportunity to thoroughly document, reevaluate, and improve business processes. This ensures that operations are not only efficient but also aligned with current market demands, contemporary regulatory standards, and the changing expectations of customers.
#3 Employee Retention: Consider the Strategic Role of Skills Acquisition
The agile, resilient organisation needs to be able to respond at pace to any threat or opportunity it faces. Some of this ability to respond will be related to technology platforms and architectures, but it will be the skills of employees that will dictate the pace of reform. While employee attrition rates will continue to decline in 2024 – but it will be driven by skills acquisition, not location of work.
Organisations who offer ongoing staff training – recognising that their business needs new skills to become a 21st century organisation – are the ones who will see increasing rates of employee retention and happier employees. They will also be the ones who offer better customer experiences, driven by motivated employees who are committed to their personal success, knowing that the organisation values their performance and achievements.
#4 Next-Gen IT Operations: Explore Gen AI for Incident Avoidance and Predictive Analysis
The integration of Generative AI in IT Operations signifies a transformative shift from the automation of basic tasks, to advanced functions like incident avoidance and predictive analysis. Initially automating routine tasks, Generative AI has evolved to proactively avoiding incidents by analysing historical data and current metrics. This shift from proactive to reactive management will be crucial for maintaining uninterrupted business operations and enhancing application reliability.
Predictive analysis provides insight into system performance and user interaction patterns, empowering IT teams to optimise applications pre-emptively, enhancing efficiency and user experience. This also helps organisations meet sustainability goals through accurate capacity planning and resource allocation, also ensuring effective scaling of business applications to meet demands.
#5 Expanding Possibilities: Incorporate AI Startups into Your Portfolio
While many of the AI startups have been around for over five years, this will be the year they come into your consciousness and emerge as legitimate solutions providers to your organisation. And it comes at a difficult time for you!
Most tech leaders are looking to reduce technical debt – looking to consolidate their suppliers and simplify their tech architecture. Considering AI startups will mean a shift back to more rather than fewer tech suppliers; a different sourcing strategy; more focus on integration and ongoing management of the solutions; and a more complex tech architecture.
To meet business requirements will mean that business cases will need to be watertight – often the value will need to be delivered before a contract has been signed.
While the discussions have centred around AI, particularly Generative AI in 2023, the influence of AI innovations is extensive. Organisations will urgently need to re-examine their risk strategies, particularly in cyber and resilience practices. They will also reassess their infrastructure needs, optimise applications for AI, and re-evaluate their skills requirements.
This impacts the entire tech market, including tech skills, market opportunities, and innovations.
Ecosystm analysts Alea Fairchild, Darian Bird, Richard Wilkins, and Tim Sheedy present the top 5 trends in building an Agile & Resilient Organisation in 2024.
Click here to download ‘Ecosystm Predicts: Top 5 Resilience Trends in 2024’ as a PDF.
#1 Gen AI Will See Spike in Infrastructure Innovation
Enterprises considering the adoption of Generative AI are evaluating cloud-based solutions versus on-premises solutions. Cloud-based options present an advantage in terms of simplified integration, but raise concerns over the management of training data, potentially resulting in AI-generated hallucinations. On-premises alternatives offer enhanced control and data security but encounter obstacles due to the unexpectedly high demands of GPU computing needed for inferencing, impeding widespread implementation. To overcome this, there’s a need for hardware innovation to meet Generative AI demands, ensuring scalable on-premises deployments.
The collaboration between hardware development and AI innovation is crucial to unleash the full potential of Generative AI and drive enterprise adoption in the AI ecosystem.
Striking the right balance between cloud-based flexibility and on-premises control is pivotal, with considerations like data control, privacy, scalability, compliance, and operational requirements.
#2 Cloud Migrations Will Make Way for Cloud Transformations
The steady move to the public cloud has slowed down. Organisations – particularly those in mature economies – now prioritise cloud efficiencies, having largely completed most of their application migration. The “easy” workloads have moved to the cloud – either through lift-and-shift, SaaS, or simple replatforming.
New skills will be needed as organisations adopt public and hybrid cloud for their entire application and workload portfolio.
- Cloud-native development frameworks like Spring Boot and ASP.NET Core make it easier to develop cloud-native applications
- Cloud-native databases like MongoDB and Cassandra are designed for the cloud and offer scalability, performance, and reliability
- Cloud-native storage like Snowflake, Amazon S3 and Google Cloud Storage provides secure and scalable storage
- Cloud-native messaging like Amazon SNS and Google Cloud Pub/Sub provide reliable and scalable communication between different parts of the cloud-native application
#3 2024 Will be a Good Year for Technology Services Providers
Several changes are set to fuel the growth of tech services providers (systems integrators, consultants, and managed services providers).
There will be a return of “big apps” projects in 2024.
Companies are embarking on significant updates for their SAP, Oracle, and other large ERP, CRM, SCM, and HRM platforms. Whether moving to the cloud or staying on-premises, these upgrades will generate substantial activity for tech services providers.
The migration of complex apps to the cloud involves significant refactoring and rearchitecting, presenting substantial opportunities for managed services providers to transform and modernise these applications beyond traditional “lift-and-shift” activities.
The dynamic tech landscape, marked by AI growth, evolving security threats, and constant releases of new cloud services, has led to a shortage of modern tech skills. Despite a more relaxed job market, organisations will increasingly turn to their tech services partners, whether onshore or offshore, to fill crucial skill gaps.
#4 Gen AI and Maturing Deepfakes Will Democratise Phishing
As with any emerging technology, malicious actors will be among the fastest to exploit Generative AI for their own purposes. The most immediate application will be employing widely available LLMs to generate convincing text and images for their phishing schemes. For many potential victims, misspellings and strangely worded appeals are the only hints that an email from their bank, courier, or colleague is not what it seems. The ability to create professional-sounding prose in any language and a variety of tones will unfortunately democratise phishing.
The emergence of Generative AI combined with the maturing of deepfake technology will make it possible for malicious agents to create personalised voice and video attacks. Digital channels for communication and entertainment will be stretched to differentiate between real and fake.
Security training that underscores the threat of more polished and personalised phishing is a must.
#5 A Holistic Approach to Risk and Operational Resilience Will Drive Adoption of VMaaS
Vulnerability management is a continuous, proactive approach to managing system security. It not only involves vulnerability assessments but also includes developing and implementing strategies to address these vulnerabilities. This is where Vulnerability Management Platforms (VMPs) become table stakes for small and medium enterprises (SMEs) as they are often perceived as “easier targets” by cybercriminals due to potentially lesser investments in security measures.
Vulnerability Management as a Service (VMaaS) – a third-party service that manages and controls threats to automate vulnerability response to remediate faster – can improve the asset cybersecurity management and let SMEs focus on their core activities.
In-house security teams will particularly value the flexibility and customisation of dashboards and reports that give them enhanced visibility over all assets and vulnerabilities.
