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Ecosystm Insights - A new age Technology Research platform to help you access latest market insights,expert opinions and research data
Ground-Realities-Leadership-Insights-on-AI-ROI
Ground Realities: Leadership Insights on AI ROI

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Over the past year of moderating AI roundtables, I’ve had a front-row seat to how the conversation has evolved. Early discussions often centred on identifying promising use cases and grappling with the foundational work, particularly around data readiness. More recently, attention has shifted to emerging capabilities like Agentic AI and what they mean for enterprise workflows. The pace of change has been rapid, but one theme has remained consistent throughout: ROI.

What’s changed is the depth and nuance of that conversation. As AI moves from pilot projects to core business functions, the question is no longer just if it delivers value, but how to measure it in a way that captures its true impact. Traditional ROI frameworks, focused on immediate, measurable returns, are proving inadequate when applied to AI initiatives that reshape processes, unlock new capabilities, and require long-term investment.

To navigate this complexity, organisations need a more grounded, forward-looking approach that considers not only direct gains but also enablement, scalability, and strategic relevance. Getting this right is key to both validating today’s investments and setting the stage for meaningful, sustained transformation.

Here is a summary of the key thoughts around AI ROI from multiple conversations across the Asia Pacific region.

1. Redefining ROI Beyond Short-Term Wins

A common mistake when adopting AI is using traditional ROI models that expect quick, obvious wins like cutting costs or boosting revenue right away. But AI works differently. Its real value often shows up slowly, through better decision-making, greater agility, and preparing the organisation to compete long-term.

AI projects need big upfront investments in things like improving data quality, upgrading infrastructure, and managing change. These costs are clear from the start, while the bigger benefits, like smarter predictions, faster processes, and a stronger competitive edge, usually take years to really pay off and aren’t easy to measure the usual way.

Ecosystm research finds that 60% of organisations in Asia Pacific expect to see AI ROI over two to five years, not immediately.

The most successful AI adopters get this and have started changing how they measure ROI. They look beyond just money and track things like explainability (which builds trust and helps with regulations), compliance improvements, how AI helps employees work better, and how it sparks new products or business models. These less obvious benefits are actually key to building strong, AI-ready organisations that can keep innovating and growing over time.

Head of Digital Innovation

2. Linking AI to High-Impact KPIs: Problem First, Not Tech First

Successful AI initiatives always start with a clearly defined business problem or opportunity; not the technology itself. When a precise pain point is identified upfront, AI shifts from a vague concept to a powerful solution.

An industrial firm in Asia Pacific reduced production lead time by 40% by applying AI to optimise inspection and scheduling. This result was concrete, measurable, and directly tied to business goals.

This problem-first approach ensures every AI use case links to high-impact KPIs – whether reducing downtime, improving product quality, or boosting customer satisfaction. While this short-to-medium-term focus on results might seem at odds with the long-term ROI perspective, the two are complementary. Early wins secure executive buy-in and funding, giving AI initiatives the runway needed to mature and scale for sustained strategic impact.

Together, these perspectives build a foundation for scalable AI value that balances immediate relevance with future resilience.

CIO

3. Tracking ROI Across the Lifecycle

A costly misconception is treating pilot projects as the final success marker. While pilots validate concepts, true ROI only begins once AI is integrated into operations, scaled organisation-wide, and sustained over time.

Ecosystm research reveals that only about 32% of organisations rigorously track AI outcomes with defined success metrics; most rely on ad-hoc or incomplete measures.

To capture real value, ROI must be measured across the full AI lifecycle. This includes infrastructure upgrades needed for scaling, ongoing model maintenance (retraining and tuning), strict data governance to ensure quality and compliance, and operational support to monitor and optimise deployed AI systems.

A lifecycle perspective acknowledges the real value – and hidden costs – emerge beyond pilots, ensuring organisations understand the total cost of ownership and sustained benefits.

Director of Data & AI Strategy

4. Strengthening the Foundations: Talent, Data, and Strategy

AI success hinges on strong foundations, not just models. Many projects fail due to gaps in skills, data quality, or strategic focus – directly blocking positive ROI and wasting resources.

Top organisations invest early in three pillars:

  • Data Infrastructure. Reliable, scalable data pipelines and quality controls are vital. Poor data leads to delays, errors, higher costs, and compliance risks, hurting ROI.
  • Skilled Talent. Cross-functional teams combining technical and domain expertise speed deployment, improve quality, reduce errors, and drive ongoing innovation – boosting ROI.
  • Strategic Roadmap. Clear alignment with business goals ensures resources focus on high-impact projects, secures executive support, fosters collaboration, and enables measurable outcomes through KPIs.

Strengthening these fundamentals turns AI investments into consistent growth and competitive advantage.

CTO

5. Navigating Tool Complexity: Toward Integrated AI Lifecycle Management

One of the biggest challenges in measuring AI ROI is tool fragmentation. The AI lifecycle spans multiple stages – data preparation, model development, deployment, monitoring, and impact tracking – and organisations often rely on different tools for each. MLOps platforms track model performance, BI tools measure KPIs, and governance tools ensure compliance, but these systems rarely connect seamlessly.

This disconnect creates blind spots. Metrics sit in silos, handoffs across teams become inefficient, and linking model performance to business outcomes over time becomes manual and error prone. As AI becomes more embedded in core operations, the need for integration is becoming clear.

To close this gap, organisations are adopting unified AI lifecycle management platforms. These solutions provide a centralised view of model health, usage, and business impact, enriched with governance and collaboration features. By aligning technical and business metrics, they enable faster iteration, responsible scaling, and clearer ROI across the lifecycle.

AI Strategy Lead

Final Thoughts: The Cost of Inaction

Measuring AI ROI isn’t just about proving cost savings; it’s a shift in how organisations think about value. AI delivers long-term gains through better decision-making, improved compliance, more empowered employees, and the capacity to innovate continuously.

Yet too often, the cost of doing nothing is overlooked. Failing to invest in AI leads to slower adaptation, inefficient processes, and lost competitive ground. Traditional ROI models, built for short-term, linear investments, don’t account for the strategic upside of early adoption or the risks of falling behind.

That’s why leading organisations are reframing the ROI conversation. They’re looking beyond isolated productivity metrics to focus on lasting outcomes: scalable governance, adaptable talent, and future-ready business models. In a fast-evolving environment, inaction carries its own cost – one that may not appear in today’s spreadsheet but will shape tomorrow’s performance.

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Forecasting-Falls-Short-Use-Backcasting-to-Win-Budget-for-Big-Moves
Forecasting Falls Short: Use Backcasting to Win Budget for Big Moves

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Typically, business leaders rely on forecasts to secure budgets for achieving their goals and objectives. Forecasts take historical trends and project them forward, with added assumptions about what may or may not change in the market or operating environment.  

But in today’s volatile economic and political climate, traditional forecasting is increasingly unreliable. 

The threat of tariffs, actual tariffs, ongoing and emerging conflicts, political transitions and rising authoritarianism, along with the uncertain impact of AI on employment and productivity, are all undermining not just business and consumer confidence, but also supply chains and manufacturing capacity. 

Look at the PC market in Asia Pacific. Shipments have traditionally been relatively straightforward to forecast; but in 2025, projections have swung from a 10% decline to 12% growth, and everything in between! These forecasts continue to shift month by month as market conditions evolve. The same applies to tech and non-tech products and services across many industries. Forecasts are no longer reliable or trustworthy. 

So, if we cannot trust forecasts, what can we do to secure budget for our short-, medium- and longer-term initiatives? For many leaders, the answer is “Backcasting”.  

When Forecasts Break Down, Backcasting Steps Up 

Put simply, backcasting is creating a future vision, and building a plan to make that vision a reality.  

For example, imagine you are the Asia Pacific Managing Director of a US-based software company aiming to move from the fifth to the second-largest provider in the region by 2030. To reach this goal, you’ll need to build specific capabilities such as adding distributors; expanding implementation and systems integration partners across ASEAN and India (which means strengthening your partner management team); increasing sales and account managers in tier 2 cities; and developing localised product versions and language support. You might also need to choose a different cloud provider to access certain markets like China and adapt your software to meet local regulations.  

Backcasting helps you plan all these steps by starting with your 2030 goal and working backwards to create a clear roadmap to get there. 

The benefit of backcasting over forecasting is that it gives your organisation defendable goals, targets and initiatives. It moves the thinking beyond the traditional quarterly targets to a longer-term vision. When global leaders ask you to cut budgets, it provides them with clear insight into how those cuts will affect the organisation’s success in Asia Pacific over the medium to long term. It also helps to understand which resources will help you achieve the longer-term goals and which will not.  

Ultimately, backcasting is a better way of helping you defend your budgets from the tactical cuts and short-sighted strategies and sharpens your capability to deliver results in the longer term. 

Want to Know More? 

You can access a detailed report on backcasting: what it is, how it differs from traditional forecasting, and how it can be applied within your organisation. The report includes examples of companies using backcasting to shape strategic initiatives and support innovation, as well as a scenario outlining how an Asia Pacific tech vendor might use the approach to meet growing regional demands. 

We have also helped clients start their backcasting journeys through targeted workshops, internal presentations, training programs and helping them set the backcasting strategy and processes in place. These services can support organisations at a strategic level, by aligning long-term plans with overarching goals; or at a team level, by helping functions like sales and marketing meet specific performance expectations. 

We welcome your feedback – feel free to contact me or Alea Fairchild. If backcasting could support your organisation’s growth or budget planning, we’d be happy to connect via call or in person to discuss specific needs.

Here’s how we can help:

  • Workshops. In-person or virtual workshops designed to build backcasting capabilities, such as setting long-term goals, creating roadmaps, and shifting focus from short-term tactics to strategic outcomes.
  • Training (Internal Presentations & Webinars). Sessions to introduce teams to backcasting, explaining what it is, how it can be used, and why it supports more effective mid- to long-term planning.
  • Client-Facing Presentations. Presentations tailored for clients and customers to show how backcasting can support their planning and investment decisions, potentially strengthening alignment with available solutions.
  • Podcasts & Videos. Co-created audio or video content with leadership to explore how backcasting fits into current workflows, where the value lies, and how teams can tailor their efforts to organisational priorities.
Forecasting is Dead – Use Backcasting to Win Budget for Big Moves
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Ground Realities: Thailand’s Tech Pulse 

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Thailand’s digital transformation has shifted from an ambitious policy agenda to a national necessity. As the country accelerates its Thailand 4.0 strategy, digital platforms are becoming central to boosting competitiveness, enhancing public services, and building economic resilience. From logistics and healthcare to finance and manufacturing, digital tools now underpin how Thailand moves, heals, pays, and grows. 

Recent reforms, including the National AI Strategy, Smart City Masterplan, and National Digital ID framework, have been paired with efforts to strengthen digital infrastructure nationwide. Yet challenges remain: integrating platforms across government, closing the generational digital divide, and safeguarding vulnerable users in a rapidly evolving fintech and gig economy. 

Through multiple roundtables and stakeholder dialogues, Ecosystm has uncovered five core themes that highlight both the momentum and the friction points in Thailand’s digital journey. 

Theme 1: Bridging the Regional Divide 

Thailand’s digital transformation is accelerating in urban centres like Bangkok, Chonburi, and Rayong, but rural and low-income regions, especially in the North and Deep South, continue to lag. Gaps in connectivity, digital skills, and modern technical education are limiting access to online learning, mobile banking, and digital public services, while also holding back the growth of tech-driven industries. 

Initiatives like Net Pracharat have brought broadband to over 75,000 villages, and new investments in regional data centres and telecom infrastructure show promise. Still, last-mile gaps and fragile networks persist, particularly in conflict-affected or underserved areas. Even where fibre is available, unstable connections often block meaningful digital adoption. 

At the same time, Thailand’s push into future-focused industries such as EVs, semiconductors, AI, and smart logistics, is straining its talent pipeline. The Eastern Economic Corridor (EEC) is attracting major investment, but the demand for skilled workers in data science, cybersecurity, and industrial AI far exceeds supply. Many regional technical education systems have not kept pace, widening the skills gap. 

To ensure inclusive growth, Thailand needs to pair infrastructure investment with targeted reskilling and education reform. Programs like the Digital Skill Development Academy and revamped TVET initiatives are important first steps; but broader progress will require stronger industry-academia partnerships, faster certification pathways, and universal access to digital learning. 

Theme 2: Unifying Government Services for a Seamless Citizen Journey 

From PromptPay-linked welfare payments and Mor Prom for health services, to the rollout of the NDID (National Digital ID), Thailand has made considerable progress in digitalising public services. Citizens can now access more services online than ever before. 

However, many of these systems still operate in silos, with duplicated citizen data, separate logins, and limited backend integration between agencies. Ministries and local governments often lack the interoperability standards and cloud infrastructure needed to provide seamless, real-time services. 

The next phase of government digitalisation must focus on platform-level integration, supported by secure data sharing frameworks, API-first design, and privacy-by-default policies. The goal is to move from digitising transactions to building a citizen-centric, connected state, where services are proactive, mobile-friendly, and unified across domains. 

Theme 3: Strengthening Public Trust Through Proactive Cybersecurity 

With the rise of digital government, cloud adoption, and cashless ecosystems, Thailand’s attack surface is rapidly expanding. High-profile breaches in healthcare, telecom, and finance have triggered growing public concern around data misuse, fraud, and infrastructure vulnerabilities. 

The government has enacted the Cybersecurity Act (2019) and PDPA (2022), and agencies like the National Cybersecurity Agency (NCSA) are stepping up threat monitoring. But cybersecurity maturity across sectors remains uneven. Many SMEs, regional hospitals, and even provincial government systems operate with limited threat intelligence and minimal incident response protocols. 

Cybersecurity must now move from compliance to strategic resilience. This includes building sector-specific response plans, launching cyber drills in critical infrastructure, and scaling cyber talent development across the country. Trust in digital services will depend not just on what’s offered, but on how securely it’s delivered. 

Theme 4: Scaling Trust Through Local Language, Visibility, and Human Oversight 

AI systems in Thailand are increasingly interfacing with the public, from chatbots and digital assistants to automated approvals and diagnostics. However, public trust in these systems remains fragile, particularly when users cannot understand how decisions are made or get help when things go wrong.. Language barriers and unclear design only add to the uncertainty. 

Many AI tools are built in English-first environments, with limited Thai-language optimisation or cultural context. In rural areas or among older populations, this can create friction and resistance, even when the underlying system works well. Without transparency, user control, or recourse, AI tools risk being seen as alienating rather than empowering. 

To build public confidence, AI deployments must prioritise explainability, Thai-language usability, and built-in pathways for human support. This includes interface localisation, clear model intent statements, and fallback mechanisms. Trust will not be built through performance alone, it must be earned through transparency, accessibility, and responsiveness. 

Theme 5: Embedding Governance to Sustain Smart Urban Growth 

Thailand has made significant headway in its smart city development agenda, with over 30 provinces participating in the national Smart City program. Flagship initiatives in Phuket, Chiang Mai, Khon Kaen, and parts of the EEC have introduced smart traffic systems, e-governance tools, environmental monitoring, and digital tourism platforms. 

However, many smart city projects are still pilots, driven by local champions, reliant on short-term grants, and lacking long-term governance structures. Fragmented data, unclear stakeholder roles, and limited collaboration between cities continue to slow scale and national replication. 

The Smart City Office under DEPA is working to address these challenges by developing standard frameworks, urban data platforms, and public-private investment models. To maintain momentum, Thailand will need to embed smart city governance in multi-year digital urban strategies, establish shared infrastructure foundations, and invest in capacity-building for local leaders. 

For smart cities to succeed, they must move beyond tech demonstrations and deliver real, lasting improvements in liveability, safety, and economic opportunity.  

Sustaining Momentum in a Connected Nation 

Thailand’s digital future won’t be defined by policy or technology alone; but by how effectively the country aligns infrastructure, skills, services, and trust at scale. The foundations are already being built in classrooms, city halls, data centres, and boardrooms. The real opportunity lies in weaving these efforts into a cohesive, resilient digital fabric. Lasting impact will come not just from momentum, but from turning vision into everyday value for people, communities, and businesses alike. 

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End-User-Computing-Strategy-Checklist
End-User Computing Strategy Checklist

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In a previous blog, I explored why organisations need to rethink their end-user computing strategies in light of shifting business demands, evolving user expectations, and operational challenges.

Building on that, this post offers a strategy template: a living framework to guide sustainable, responsible tech procurement. Use it to define clear requirements that reflect your business goals, regional context, and workforce needs. Then tailor it further to suit your industry standards and organisational realities, revisiting it regularly as your environment evolves.

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Click here to download “End-User Computing Strategy Checklist” as a PDF.

1. Business Alignment and Objectives

  • Primary business goals such as productivity, collaboration, security, and innovation.
  • Strategic initiatives, including digital transformation, hybrid working, and compliance.
  • Alignment between EUC objectives, overall business strategy, and industry-specific drivers.

2. Industry-Specific Considerations

  • Regulatory requirements (Data privacy, compliance frameworks, cybersecurity).
  • Industry-specific applications (e.g., finance platforms, healthcare EMR, retail POS).
  • Business-critical workflows and processes supported by EUC.

3. Geographic & Regional Factors

  • Infrastructure considerations (network availability, connectivity quality, 4G/5G, Wi-Fi).
  • Regional compliance (local privacy laws, cybersecurity regulations, data residency requirements).
  • Support and logistics (local vendor availability, language support, supply chain).

4. Persona-Based Device Strategy

  • Employee personas including:
  1. Frontline/Mobile workers
  2. Knowledge workers
  3. Power users/Technical teams
  4. Executives
  5. Hybrid/Remote workers
  • Device types, operating systems, and form factors suited to each persona.

5. Technology and Platform Choices

  • Operating system selection (Windows, macOS, Chrome OS, Android, iOS).
  • VDI/DaaS selection (Citrix, VMware Horizon, AWS WorkSpaces, Azure Virtual Desktop).
  • Cloud-based productivity suite selection (Microsoft 365, Google Workspace).
  • Unified Endpoint Management (UEM) platform selection.

6. Security and Compliance Strategy

  • Endpoint security model (Zero Trust, EDR, MFA, biometrics).
  • Data encryption and privacy management strategy.
  • Identity and Access Management (IAM) policies.
  • Incident response and threat detection framework.

7. User Experience and Employee Engagement

  • Employee experience objectives (ease-of-use, personalisation, productivity).
  • Self-service portals and automation for IT support.
  • End-user training, change management, and continuous feedback loops.
  • Plans for local AI capabilities – Agents, Information and data management, etc.

8. Operational Excellence and Lifecycle Management

  • Device procurement, deployment, and lifecycle policies.
  • Automation and AI-driven analytics for device management.
  • Sustainability and environmental impact (device recycling, energy efficiency).
  • Other GRC requirements (anti-slavery etc).

9. Cost Optimisation and Budgeting

  • Total Cost of Ownership (TCO) calculation framework.
  • CAPEX vs OPEX considerations (purchase, lease, consumption-based).
  • Vendor financing and budgeting strategies.

10. Vendor and Partner Management

  • Vendor evaluation criteria (support, innovation, geographic coverage, pricing).
  • Partnership strategy (managed services, system integrators, technology alliances).
  • Vendor risk management and vendor performance monitoring framework.

11. Metrics and Measurement

  • Outcome-focused success metrics (e.g., productivity, satisfaction, security).
  • Monitoring and reporting structure.
  • Continuous improvement plan based on metric analysis.

12. ESG

  • Eco-labels, ISO 14067 or PAS 2050 carbon disclosures, and climate-condition testing to avoid energy waste.
  • Vendor take-back in all regions, minimums for firmware support and repairability to slow refresh cycles.
  • Supply-chain ethics evidence, including up-to-date RBA VAP scores or modern slavery reports.
  • Tracking of tightening regulations to stay ahead of compliance risks.
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Ground Realities: Banking AI Pulse 

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Consider the sheer volume of information flowing through today’s financial systems: every QR payment, e-KYC onboarding, credit card swipe, and cross-border transfer captures a data point. With digital banking and Open Banking, financial institutions are sitting on a goldmine of insights. But this isn’t just about data collection; it’s about converting that data into strategic advantage in a fast-moving, customer-driven landscape. 

With digital banks gaining traction and regulators around the world pushing bold reforms, the industry is entering a new phase of financial innovation powered by data and accelerated by AI.  

Ecosystm gathered insights and identified key challenges from senior banking leaders during a series of roundtables we moderated across Asia Pacific. The conversations revealed a clear picture of where momentum is building – and where obstacles continue to slow progress. From these discussions, several key themes emerged that highlight both opportunities and ongoing barriers in the Banking sector.  

1. AI is Leading to End-to-End Transformation 

Banks are moving beyond generic digital offerings to deliver hyper-personalised, data-driven experiences that build loyalty and drive engagement. AI is driving this shift by helping institutions anticipate customer needs through real-time analysis of behavioural, transactional, and demographic data. From pre-approved credit offers and contextual investment nudges to app interfaces that adapt to individual financial habits, personalisation is becoming a core strategy, not just a feature. This is a huge departure from reactive service models, positioning data as a long-term strategic asset. 

But the impact of AI isn’t limited to customer-facing experiences. It’s also driving innovation deep within the banking stack, from fraud detection and SME loan processing to intelligent chatbots that scale customer support. On the infrastructure side, banks are investing in agile, AI-ready platforms to support automation, model training, and advanced analytics at scale. These shifts are redefining how banks operate, make decisions, and deliver value. Institutions that integrate AI across both front-end journeys and back-end processes are setting a new benchmark for agility, efficiency, and competitiveness in a fast-changing financial landscape. 

2. Regulatory Shifts are Redrawing the Competitive Landscape 

Regulators are moving quickly in Asia Pacific by introducing frameworks for Open Banking, real-time payments, and even AI-specific standards like Singapore’s AI Verify. But the challenge for banks isn’t just keeping up with evolving external mandates. Internally, many are navigating a complicated mix of overlapping policies, built up over years of compliance with local, regional, and global rules. This often slows down innovation and makes it harder to implement AI and automation consistently across the organisation. 

As banks double down on AI, it is clear that governance can’t be an afterthought. Many are still dealing with fragmented ownership of AI systems, inconsistent oversight, and unclear rules around things like model fairness and explainability. The more progressive ones are starting to fix this by setting up centralised governance frameworks, investing in risk-based controls, and putting processes in place to monitor things like bias and model drift from day one. They are not just trying to stay compliant; they are preparing for what’s coming next. In this landscape, the ability to manage regulatory complexity with speed and clarity, both internally and externally, is quickly becoming a competitive edge. 

3. Success Depends on Strategy, Not Just Tech 

While enthusiasm for AI is high, sustainable success hinges on a clear, aligned strategy that connects technology to business outcomes. Many banks struggle with fragmented initiatives because they lack a unified roadmap that prioritises high-impact use cases. Without clear goals, AI projects often fail to deliver meaningful value, becoming isolated pilots with limited scalability. 

To avoid this, banks need to develop robust return-on-investment (ROI) models tailored to their context — measuring benefits like faster credit decisioning, reduced fraud losses, or increased cross-selling effectiveness. These models must consider not only the upfront costs of infrastructure and talent, but also ongoing expenses such as model retraining, governance, and integration with existing systems. 

Ethical AI governance is another essential pillar. With growing regulatory scrutiny and public concern about opaque “black box” models, banks must embed transparency, fairness, and accountability into their AI frameworks from the outset. This goes beyond compliance; strong governance builds trust and is key to responsible, long-term use of AI in sensitive, high-stakes financial environments. 

4. Legacy Challenges Still Hold Banks Back 

Despite strong momentum, many banks face foundational barriers that hinder effective AI deployment. Chief among these is data fragmentation. Core customer, transaction, compliance, and risk data are often scattered across legacy systems and third-party platforms, making it difficult to access the integrated, high-quality data that AI models require. 

This limits the development of comprehensive solutions and makes AI implementations slower, costlier, and less effective. Instead of waiting for full system replacements, banks need to invest in integration layers and modern data platforms that unify data sources and make them AI-ready. These platforms can connect siloed systems – such as CRM, payments, and core banking – to deliver a consolidated view, which is crucial for accurate credit scoring, personalised offers, and effective risk management. 

Banks must also address talent gaps. The shortage of in-house AI expertise means many institutions rely on external consultants, which increases costs and reduces knowledge transfer. Without building internal capabilities and adjusting existing processes to accommodate AI, even sophisticated models may end up underused or misapplied. 

5. Collaboration and Capability Building are Key Enablers 

AI transformation isn’t just a technology project – it’s an organisation-wide shift that requires new capabilities, ways of working, and strategic partnerships. Success depends on more than just hiring data scientists. Relationship managers, credit officers, compliance teams, and frontline staff all need to be trained to understand and act on AI-driven insights. Processes such as loan approvals, fraud escalations, and customer engagement must be redesigned to integrate AI outputs seamlessly. 

To drive continuous innovation, banks should establish internal Centres of Excellence for AI. These hubs can lead experimentation with high-value use cases like predictive credit scoring or real-time fraud detection, while ensuring that learnings are shared across business units. They also help avoid duplication and promote strategic alignment. 

Partnerships with fintechs, technology providers, and academic institutions play a vital role as well. These collaborations offer access to cutting-edge tools, niche expertise, and locally relevant AI models that reflect the regulatory, cultural, and linguistic contexts banks operate in. In a fast-moving and increasingly competitive space, this combination of internal capability building and external collaboration gives banks the agility and foresight to lead. 

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Ground Realities: The Philippines’ Tech Pulse 

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Digital transformation in the Philippines has moved from being a goal to an essential part of how organisations operate, compete, and serve their communities. This shift is evident across sectors – from  financial services and government to education, healthcare, and commerce – as digital platforms become integral to everyday life. 

In recent years, the country has been recognised as a leading improver in the UN E-Government Development Index, reflecting steady advances in digital public service delivery. Yet, progress across all sectots has been uneven, influenced by a mix of geography, regulation, and existing infrastructure. Organisations continue to adapt, responding to fast-paced technological change, rising user expectations, and an increasingly interconnected global digital economy. 

Through a series of roundtables with national leaders, Ecosystm examined the realities of digital transformation on the ground. What emerged were valuable insights into what’s working and where challenges and shifts are reshaping the definition of success in this evolving stage of digital maturity.   

Theme 1: Strengthening the Foundations for Nationwide Digital Equity 

The Philippines is advancing steadily in digitalisation, especially in Metro Manila and major urban centres, though the full benefits have yet to reach all regions evenly. Rural provinces and smaller islands face ongoing challenges with broadband access, latency, and mobile coverage, reflecting the country’s unique geography and historic underinvestment in digital infrastructure. 

National programs like the National Broadband Plan and Free Wi-Fi for All have established important foundations. Fibre rollouts by private telecom providers are extending coverage, but last-mile connectivity in geographically isolated and disadvantaged areas (GIDAs) still needs attention. Bridging this gap is key not only for broader inclusion but also to enable widespread adoption of technologies such as cloud computing, AI, and edge solutions. 

Achieving nationwide digital transformation requires a focused effort on regional infrastructure as a driver of inclusive growth. This involves co-investment, innovative public-private partnerships, and policies supporting shared towers, data centres, and satellite-backed connectivity. This benefits enterprises and critical citizen services like e-learning, e-health, and digital banking. 

Theme 2: From Outsourcing Hub to Innovation Engine – The Next Chapter for Talent 

The Philippines has established a strong global presence as a trusted centre for BPO and IT-enabled services, contributing nearly 9% to the national GDP and employing over 1.5 million professionals. In recent years, this foundation has rapidly evolved, with talent increasingly taking on complex roles in knowledge process outsourcing (KPO), AI annotation, fintech support, and cybersecurity operations. 

This shift reflects a broader transformation – from a labour-cost-driven outsourcing model to a high-skill, innovation-focused services economy. However, this transition is placing growing demands on the talent pipeline. Skilled cloud engineers, AI developers, and cybersecurity experts remain in short supply, with demand surpassing the current capacity of training and reskilling programs. 

To fully unlock its potential, the country needs to future-proof its talent ecosystem. This includes expanding technical education, strengthening collaboration between academia and industry, scaling national upskilling initiatives, and creating incentives that encourage tech professionals to build their careers locally. With targeted investment, the digital workforce can become a powerful competitive advantage on the global stage.  

Theme 3: Government Digitalisation Is Accelerating But Interoperability Remains a Challenge 

The Philippines has made major progress in digitising government services – from online business registrations via Business Name Registration System (BNRS) to digital ID rollout through PhilSys (Philippine Identification System), and integrated platforms like eGov PH Super App. The pandemic accelerated adoption of e-payment systems, telemedicine, and virtual public services, driving faster digital transformation across agencies. 

Despite this progress, interoperability challenges remain a key hurdle. Many government agencies still rely on siloed legacy systems that limit seamless data exchange. This fragmentation affects real-time decision-making, slows service delivery, and creates a fragmented experience for citizens and enterprises navigating multiple platforms. 

Going forward, the priority is system-wide integration. Building a truly citizen-centric digital government requires interoperable data architectures, strong privacy-by-design frameworks for cross-agency collaboration, and scalable API-driven platforms that enable secure, real-time connections between national and local government systems. A connected digital state not only boosts efficiency but also strengthens public trust and paves the way for more adaptive, responsive services. 

Theme 4: Cyber Resilience Is No Longer Optional – It’s Strategic 

As digital transformation accelerates, the Philippines has become one of Southeast Asia’s most targeted countries for cyberattacks – particularly in sectors like financial services, critical infrastructure, and government. High-profile breaches at agencies such as PhilHealth, the Philippine Statistics Authority, and COMELEC have brought cybersecurity to the forefront of national priorities. 

Regulatory steps such as the Cybercrime Prevention Act and the establishment of the Department of Information and Communications Technology (DICT) Cybersecurity Bureau have laid important groundwork. Yet, enterprise readiness remains uneven. Many organisations still rely on outdated defences, limited threat visibility, and ad hoc response plans that are outpaced by today’s threats. More importantly, many still look at cyber purely from a compliance angle.  

As AI, IoT, and cloud-based platforms scale, so too does the attack surface. Cyber resilience now demands more than compliance – it requires dynamic risk management, skills development, intelligence sharing, and coordinated action across sectors. The shift from reactive to adaptive security is becoming a defining capability for both public and private institutions.  

Theme 5: Financial Access at the Grassroots: The Digital Shift 

One of the Philippines’ most notable digital transformation successes has been in fintech and digital financial services. Platforms like GCash, Maya, and the government’s Paleng-QR PH program have significantly expanded access to cashless payments, savings, and credit – especially among unbanked and underbanked communities. 

By 2024, nearly 80% of Filipinos were using mobile financial apps – a striking milestone that reflects not only growing digital adoption but also evolving cultural and economic behaviours. From sari-sari stores to market vendors, digital wallets are reshaping everyday commerce and opening new avenues for financial empowerment at the grassroots level. 

Still, digital inclusion is not automatic. Maintaining this momentum will require continued investment in digital literacy – particularly for older adults, rural communities, and lower-income groups – as well as stronger measures for cybersecurity, consumer protection, and interoperable ID and payment systems. Done right, digital finance can serve as the foundation for a more inclusive and resilient economy. 

A Moment to Rethink What Progress Looks Like 

As digital systems take root across the Philippines’ economy and institutions, the focus is shifting from speed to staying power. The next phase will depend on the country’s ability to translate broad adoption into long-term value – through strategies that are inclusive, resilient, and built to scale. 

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Whitepaper – Use Backcasting, Not Forecasting in Uncertain Times

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As global tensions rise and regional priorities diverge, traditional forecasting is losing relevance. Inflation, trade barriers, and supply chain disruptions are unsettling once-stable markets, and the path forward is anything but certain. In this climate, backcasting offers a fresh alternative. By shifting the focus from predicting the future to actively shaping it, backcasting helps technology providers chart a more strategic, long-term course, particularly across Asia Pacific and Europe.

Ecosystm analysts Alea Fairchild and Tim Sheedy explore how backcasting can turn regional ambition into an investable strategy. Blending structured planning with narrative clarity, it connects long-term vision to immediate action. For global leaders, it transforms regional investment from a leap of faith into a confident, calculated move toward resilient, adaptive growth. 

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VoC Market Shakeup: PG Forsta Acquires InMoment

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The Voice of Customer (VoC) market continues to evolve, often driven by technological advancements as well as M&As. Medallia, Qualtrics, and InMoment are the three major VoC players in the enterprise segment globally and locally across ANZ.

Until recently, InMoment was the smaller contender among the three, but that changed with their acquisition by PG Forsta in May 2025. The move marks a significant shift that will alter the competitive dynamics globally and in the region.

By combining PG Forsta’s strengths in market research, structured feedback, and regulated industries with InMoment’s expertise in AI, unstructured data analysis, and its strong presence in ANZ, the newly formed entity is poised to challenge the dominance of larger rivals.

The Key Players

Medallia

Medallia is a mature player in the VoC market, with a focus on larger, more complex and ideally global programs. With ANZ, and particularly New Zealand dominated by SMB’s, the vendor is not quite as prominent locally as they are at a global level.

Medallia underwent a major executive shakeup earlier this year, bringing in a wave of leadership talent from Qualtrics, and former Clarabridge. This leadership reset brings not only strategic focus but also a significant transfer of domain expertise and IP, positioning Medallia to compete more aggressively, especially against Qualtrics.

The changes include Mark Bishof as Chairman and CEO (formerly Chief Business Officer at Qualtrics and CEO of Clarabridge), Sid Banerjee as Chief Strategy Officer (Founder of Clarabridge), and several other senior leaders.

While the vendor has been relatively quiet in the ANZ market in recent years, with renewed leadership and an internal reset, Medallia re-focuses its efforts on local customer engagement across ANZ and aims to be more active and visible in the market. For ANZ enterprises, this could bring more choice, and a potentially stronger Medallia presence in upcoming VoC initiatives.

Qualtrics

Qualtrics, another major player in the VoC market, is known for its product strength, platform developments and AI capabilities. They are the most active in terms of platform development and shared several major AI announcements earlier this year, including agentic AI capabilities. 

Qualtrics also formally introduced the term Experience Management (XM) as a discipline and new software category in 2017 with the launch of the Qualtrics XM Platform and continues to dominate the conversation on XM.

Qualtrics and InMoment have dominated the local ANZ market, in the SMB to enterprise sector. Qualtrics enjoyed winning customer deals that included market research and panel requirements, since InMoment lacked that capability in-house. And that’s where PG Forsta comes in to change the dynamic.

InMoment

InMoment is a VoC technology provider known for their Experience Improvement (XI) competencies. Their strengths include conversational intelligence, reputation management, and predictive analytics. InMoment has grown by acquisition, most notably the acquisition of MaritzCX, Lexalytics, and ReviewTracker, adding online reviews and deep analytics for unstructured data to their platform.

While smaller in size than their main competitors, InMoment has a strong local presence in ANZ and thrives on their strong customer relationships.  

PG Forsta Acquires InMoment: A Strategic Move

The VoC landscape, especially in ANZ, is bound to shift significantly following PG Forsta’s acquisition of InMoment. While mergers and acquisitions are common in tech, this move signals a deliberate attempt by PG Forsta and InMoment to expand their market footprint and compete more aggressively with established VoC rivals.

While PG Forsta and InMoment were both established players in the VoC market, their merger is notable not just for its scale, but for its strategic intent: to combine complementary strengths in research, analytics, and AI innovation to provide a more robust, cross-industry VoC platform.

PG Forsta, formed through Press Ganey’s 2022 acquisition of Forsta (itself a merger of Confirmit and FocusVision), offers a Human Experience (HX) platform that integrates customer, employee, and market feedback, with a strong foundation in healthcare. PG Forsta brings deep expertise in structured feedback, large-scale analytics, and regulated industries such as healthcare. InMoment, meanwhile, offers advanced capabilities in AI, machine learning, and unstructured data analysis. By combining these distinct strengths, the merged entity creates a more versatile and comprehensive solution. PG Forsta enhances their AI and omnichannel offering, while InMoment gains access to a broader, compliance-focused client base and robust market research capabilities.

The new entity will serve clients globally with a team of more than 3,000 employees. Unlike its main competitors, InMoment maintains a dedicated presence in New Zealand, bringing deep local market expertise and strong relationships. InMoment’s established footprint in ANZ further enhances PG Forsta’s local presence, providing valuable on-the-ground support that is increasingly important to organizations.

Both companies cite cultural alignment as a key factor in building a stronger, united organization, a critical foundation for any successful acquisition.

AI: The Battlefront for the Future of CX

A crucial aspect of this acquisition is its emphasis on AI. VoC platforms are evolving beyond traditional feedback collection, with growing pressure to gather data from both solicited and unsolicited sources and deliver actionable insights and recommendations. As AI capabilities become more embedded in operations, platforms are increasingly judged by their ability to go beyond static dashboards, to unify data, analyse unstructured data, and generate richer insights and proactive recommendations.

InMoment, along with some competitors, has invested in leveraging contact centre data to extract insights from unsolicited and unstructured sources through conversation intelligence. While initially used for customer insights, this technology is now expanding to serve contact centre teams and broader, organisation-wide intelligence use cases, breaking out of departmental silos.

As the market continues to prioritise outcome-driven CX, AI will be a central differentiator among leading platforms, and InMoment brings those capabilities into the PG Forsta deal.

Looking Ahead

While it’s too early to call the long-term outcome, this acquisition marks a significant shift in the VoC landscape, particularly in ANZ.

With a bold goal “to be THE VoC company in the market”, the bar is set high to deliver. The success of this acquisition will depend on execution. Seamless integration across systems, cultures, and product lines won’t happen overnight. But if they get it right, this merger could reshape the competitive landscape, raising the stakes for Medallia, Qualtrics, and others.

For CX leaders across ANZ, this brings more choice, more innovation, and better capabilities to drive deeper customer insights and business impact.

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End-User Computing: Why a Strategy Review is Critical

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We’re entering a new cycle of PC device growth, driven by the end-of-life of Windows 10 and natural enterprise upgrade cycles, brought into alignment by the COVID-era device boom. In Asia Pacific, PC shipments are expected to grow by 4-8% in 2025. The wide range reflects uncertainty linked to the US tariff regime, which could impact device pricing and availability in the region as manufacturers adjust to shifting demand globally.

To AI or Not to AI?

“AI PCs” (or Copilot PCs) are set to become a growing segment, but real AI benefits from these devices are still some way off. Microsoft’s announcement to embed Agentic AI capabilities into the OS marks the first step toward moving AI processing from the cloud to the desktop. However, for most organisations, these capabilities remain 12-24 months away.

This creates a strategic question: should organisations invest now in NPU-enabled devices that may not deliver immediate returns? Given typical refresh cycles of 3-5 years, it’s worth considering whether local AI processing could become relevant during that time. The safer bet is to invest in Copilot or AI PCs now, as the AI market is evolving rapidly; and the chances of NPUs becoming useful sooner rather than later are high.

Is the Desktop Being Left Behind?

PC market growth is concentrated in the laptop segment, drawing most manufacturers and chip providers to focus their innovation there. AI and Copilot PCs have yet to meaningfully enter the desktop space, where manufacturers remain largely focused on gaming.

This creates a gap for enterprises and SMEs. AI capabilities available on laptops may not be mirrored on desktops. Recent conversations with infrastructure and End-User Computing (EUC) managers suggest a shift in Asia Pacific toward laptops or cloud/ virtual desktop infrastructure (VDI) devices, including thin clients and desktops. If this trend continues, organisations will need to re-evaluate employee experience and ensure applications are designed to match the capabilities of each device type and user persona.

Fundamental EUC Drivers are Changing

As EUC and infrastructure teams revisit their strategies, several foundational drivers are undergoing significant change:

  • Remote work is no longer a default. Once considered the norm for information workers, remote work is now being reconsidered. With some organisations mandating full-time office returns, device strategies must adapt to a more hybrid and unpredictable working model.
  • Employee Experience is losing budget priority. During the pandemic, keeping employees productive and engaged was critical. But with rising cost pressures, growing automation through GenAI and Agentic AI, and changing labour dynamics, EX is no longer a top enterprise priority and budgets reflect that shift.
  • Cloud-based EUC solutions are now enterprise-ready. Since 2022, cloud adoption in EUC has accelerated. Solutions like Microsoft 365, Google Workspace, AWS WorkSpaces, and VMware Horizon Cloud now offer mature capabilities. Unified Endpoint Management (UEM) is increasingly cloud-managed, enabling more scalable and agile IT operations.
  • Zero-trust is moving security closer to the user. EUC security is evolving from perimeter-based models to identity-centric, continuous verification approaches. Investments in EDR, AI-driven threat analytics, MFA, biometric authentication, and proactive threat hunting are now standard, driven by the shift to zero trust.
  • Device diversity is increasing. Standardised device fleets are giving way to more diverse options – touchscreen laptops, foldables, and a broader mix of PC brands. Enterprise offerings are expanding beyond traditional tiers to meet varied needs across user personas.
  • Metrics are shifting from technical to outcome-based. Traditional KPIs like uptime and cost are giving way to metrics tied to business value – employee productivity, experience, collaboration, cyber resilience, and adaptability. EUC success is now measured in terms of outcomes, not just infrastructure performance.

Build a Modern and Future-Ready EUC Strategy

Organisations must reassess their plans to align with changing business needs, user expectations, and operational realities. Modern EUC strategies must account for a broad set of considerations.  

Key factors to consider:

Strategic Business Alignment

  • Business Outcomes. EUC strategies must align with core business goals such as boosting productivity, enhancing employee experience, improving customer outcomes, and driving competitive advantage. Consider how device choices enable new work models, such as remote/hybrid setups, gig workforce enablement, and cross-border collaboration.
  • Digital Transformation Fit. Ensure EUC refresh cycles are integrated with broader digital transformation efforts – cloud migration, AI adoption, automation, and innovation. Devices should be future-ready, capable of supporting the AI and automation needs of 2026 and beyond. While some workloads may shift to the cloud, others like GenAI-powered video and image creation, may demand stronger local processing across the broader workforce, not just specialist teams.

Technology Considerations

User Experience

  • Employee Productivity and Engagement. Even as EX slips down the priority list – and the budget – EUC leaders must still champion intuitive, user-friendly devices to boost productivity and reduce training and support demands. Seamless collaboration is critical across physical, remote, and hybrid teams. In-office collaboration is back in focus, but its value depends on digitising outcomes: laptops, smartphones, and tablets must enable AI-driven transcription, task assignment, and follow-up tracking from physical or hybrid meetings.
  • Personalisation and Mobility. Where practical, offer device personalisation through flexible BYOD or CYOD models. Even in industries or geographies where this isn’t feasible, small touches like device colour or accessories, can improve engagement. UEM tools are essential to enforce security while enabling flexibility.
  • Performance and Reliability. Choose devices that deliver the right performance for the task, especially for users handling video, design, or AI workloads. Prioritise long battery life and reliable connectivity, including Wi-Fi 6/7 and 5G where available. While 5G laptops are still rare across many Asia Pacific markets, that’s likely to change as networks expand and manufacturers respond to demand.
  • Localised Strategy. Given the distributed nature of many organisations in the region, support and warranty strategies should reflect local realities. Tiered service agreements may provide better value than one-size-fits-all premium coverage that’s difficult to deliver consistently.

Security and Compliance

  • Cybersecurity Posture. EUC teams typically work hand-in-hand with their cyber teams in the development of a secure EUC strategy and the deployment of the preferred devices. Cybersecurity teams will likely provide specific guidance and require compliance with local and regional regulations and laws. They will likely require that EUC teams prioritise integrated security capabilities (such as zero-trust architectures, endpoint detection and response – EDR solutions, biometrics, hardware-based security features like TPM). Consider deploying AI-driven endpoint threat detection and response tools for proactive threat mitigation.
  • Data Privacy and Regulatory Compliance. Assess devices and management systems to ensure adherence to local regulatory frameworks (such as Australia’s Privacy Act, Singapore’s PDPA, or the Philippines’ Data Privacy Act). Deploy robust policies and platforms for data encryption, remote wiping, and identity and access management (IAM).

Management, Sustainability and Operational Efficiency

  • Unified Endpoint Management (UEM). Centralise device management through UEM platforms to streamline provisioning, policy enforcement, patching, updates, and troubleshooting. Boost efficiency further with automation and self-service tools to lower IT overhead and support costs.
  • Asset Lifecycle Management (ALM). While many organisations have made progress in optimising ALM – from procurement to retirement – gaps remain, especially in geographies outside core operations. Use device analytics to monitor health, utilisation, and performance, enabling smarter refresh cycles and reduced downtime.
  • Sustainable IT and CSR Alignment. Choose vendors with strong sustainability credentials such as energy-efficient devices, ethical manufacturing, and robust recycling programs. Apply circular economy principles to extend device lifespan, reduce e-waste, and lower your carbon footprint. Align EUC strategies with broader CSR and ESG goals, using device refresh cycles as opportunities to advance sustainability targets and reinforce your organisation’s values.

Cost and Investment Planning

  • Total Cost of Ownership (TCO). Evaluate TCO holistically, factoring in purchase price, operations, software licensing, security, support, warranties, and end-of-life costs. TCO frameworks are widely available, but if you need help tailoring one to your business, feel free to reach out. Balance CapEx and OpEx across different deployment models – owned vs leased, cloud-managed vs on-premises.
  • Budgeting & Financial Modelling. Clearly define ROI and benefit realisation timelines to support internal approvals. Explore vendor financing or consumption-based models to enhance flexibility. These often align with sustainability goals, with many vendors offering equipment recycling and resale programs that reduce overall costs and support circular IT practices.

Vendor and Partner Selection

  • Vendor Support & Regional Coverage. Select vendors with strong regional support across Asia Pacific to ensure consistent service delivery across diverse markets. Many organisations rely on distributors and resellers for their extended reach into remote geographies. Others prefer working directly with manufacturers. While this can reduce procurement costs, it may increase servicing complexity and response times. Assess vendors not just on cost, but on local presence, partner network strength, and critically, their supply chain resilience.
  • Innovation & Ecosystem Alignment. Partner with vendors whose roadmaps align with future technology priorities – AI, IoT, edge computing – and who continue to invest in advancing EUC capabilities. Long-term innovation alignment is just as important as short-term performance.

Building a modern, future-ready EUC strategy isn’t just about devices – it’s about aligning people, technology, security, sustainability, and business outcomes in a way that’s cost-effective and forward-looking. But we know investment planning can be tricky. At Ecosystm, we’ve helped organisations build ROI models that make a strong case for EUC investments. If you’d like guidance, feel free to reach out – we’re here to help you get it right.

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