CIOs across Southeast and Northeast Asia face a brutal budgetary paradox today: board-mandated surges in AI and cybersecurity investments clashing directly with flat overall IT expenditure. 

According to IDC and Forrester, while regional tech spending is rising, geopolitical risks and inflation are eroding real purchasing power. Consequently, technology leaders are forced into aggressive reallocation. 

They must defer legacy ERP upgrades, consolidate SaaS contracts, and renegotiate vendor support to fund digital priorities without expanding the top-line budget, turning run-rate IT optimisation into a critical strategic lever for margin protection. This shift is redefining the CIO role.

In this PodChats for FutureCIO, we explore why IT budget strategies need to shift from cutting waste to driving innovation. For more on this, we are joined by Seth Ravin, CEO of Rimini Street.

Setting the Macro Context

1.       With overall IT budgets remaining largely flat across Asia despite surging AI demands, how are CIOs fundamentally restructuring their 2026 budget cycles to accommodate these new priorities without asking for more money?

The Core Trade-off: AI vs. Legacy 

2.       In your conversations with customers, when boards ring-fence AI and cybersecurity spend, which specific legacy IT projects or 'run rate' operations bear the brunt of the cuts?

3.       You have highlighted the deferral of ERP upgrades; what are the operational and technical risks CIOs are willing to accept by pushing these critical modernisations down the line?

Executing the Cuts: ERP, SaaS, and Cloud 

4.       How are enterprises leveraging third-party enterprise software support models to immediately free up capital. Is this shifting from a tactical cost-saving measure to a strategic boardroom lever? 

5.       Beyond traditional on-premise legacy systems, are we now seeing CIOs aggressively consolidating SaaS contracts and even renegotiating hyperscaler cloud commitments to fund AI initiatives?

Regional and Sector Nuances 

6.       CIOs at different sectors: manufacturing, healthcare, logistics, and financial services, approach how they manage their IT budgets. Are there distinct budget-cutting patterns or unique pressures specific to these sectors in the Asian market?

The CIO and CFO Dynamic 

7.       How has the conversation between the CIO and CFO evolved in the region? Are finance leaders now driving IT vendor renegotiations, or is the CIO leading this charge to protect innovation budgets?

Strategic and Financial Implications 

8.       Looking beyond 2026, if AI and cyber costs continue to scale without a corresponding increase in overall IT budgets, is the current model of funding them purely through legacy cuts sustainable?

9.       Let’s round out what we’ve covered so far. Our topic is IT budget strategies for focusing on innovation and not cost-cutting. What are your top 3 recommendations for IT budget strategies for focusing on innovation and not cost-cutting?

In 2026, the competitive advantage in AI will no longer come from model speed or scale—it will come from trust. As Southeast Asia and Korea accelerate enterprise AI adoption amid fragmented regulatory landscapes (from Singapore’s FEAT to Korea’s AI Basic Act), the CIO’s mandate has shifted from deployment to defense. 

“AI integrity”—the convergence of data provenance, bias mitigation, explainability, and ethical resilience—is now a board-level risk. For heads of compliance and data science, the question is no longer “Can we scale AI?” but “Can we certify its integrity?” Without it, you face regulatory fines, model drift, and reputational collapse. 
 In this PodChats for FutureCIO, we are joined by Lee Anstiss, Regional Director, Southeast Asia and Korea at Infoblox, to hopefully get insights and tips on how to safeguard AI integrity.

1.       Do Asia’s CIOs and CISOs know exactly which AI models are running across all our business units—or is shadow AI already creating integrity risks we cannot see?

2.       Given the fragmented state of each model’s regulatory status, what options are there for CIOs as they navigate fragmented rules with fragmented data?

3.       In your view, are enterprises in Asia prioritizing raw accuracy over an “integrity scorecard” that includes bias, explainability, and robustness—and if so, are CIOs trusting models that are fast but not fair?

4.       Based on current technologies and practices, can CIOs trace every piece of training data, including synthetic data, back to its source? Do organisations have blind spots where hidden bias or poisoned inputs could enter?

5.       Can CIOs test their production AI for bias against local languages and cultural norms in each market? Can they produce an audit trail for any regulator who asks?

6.       If a regulator demands proof of real-time bias disclosure tomorrow, is there a way for enterprises to have automated logs mapped to specific legal articles?

7.       Should organisations maintain a human-in-the-loop for high-stakes decisions, with override logs that feed back into retraining? How risky is using the discipline of oversight as a checkbox?

8.       Our topic is “tips on how to safeguard AI integrity” Can you share some of the most common or practical tips for CIOs, heads of AI, for ensuring or safeguarding AI integrity.

Across Southeast Asia, generative AI pilots are stalling—not from a lack of model power, but from broken retrieval. Agentic RAG bridges this gap: autonomous agents that verify facts, enforce governance, and execute end-to-end workflows. For CIOs in 2026, this turns fragile experiments into auditable, scalable profit centres. 

With Gartner warning that 60% of AI projects will be abandoned due to poor data and weak controls, agentic RAG is no longer optional—it is the only practical path from pilot to production. In markets like Singapore, where data residency and compliance are non-negotiable, retrieval intelligence is now the bedrock of ROI.

In this PodChats for FutureCIO, Ed Keisling, Chief AI Officer, Progress Software, discusses how CIOs and heads of AI across Southeast Asia, can turn AI pilots and POCs into profit-generating initiatives for enterprises in 2026.

1. What is RAG?
2. Given that most regional AI pilots never scale, what specific architectural weaknesses does agentic RAG fix that traditional RAG or fine-tuning cannot?
3. In markets with fragmented data landscapes—legacy systems, multilingual content, and disparate cloud storage—how does agentic RAG ensure consistent, high-quality retrieval at enterprise scale?
4. What out-of-the-box governance and audit trails does agentic RAG provide to satisfy both local data residency laws (e.g., Singapore’s PDPA) and board-level risk controls?
5. For CIOs managing lean teams, how does agentic RAG reduce the operational burden of maintaining retrieval pipelines, monitoring hallucinations, and orchestrating multi-step agent workflows? 
6. How can agentic RAG help move beyond isolated use cases (e.g., customer support) toward fully autonomous, end-to-end processes spanning finance, supply chain, and compliance?
7. As agents become more autonomous by 2027, what retrieval strategies will prevent cascading errors or unauthorised actions, and what should CIOs implement today to stay safe?
8. (original 3) How should CIOs in Singapore and across Southeast Asia measure the ROI of retrieval intelligence compared to simply upgrading large language models?
9. For regional enterprises without custom AI stacks, what vendor or open-source scaffolding for agentic RAG offers the fastest path from pilot to profit while preserving data sovereignty?
10. What organisational, data, and leadership shifts must CIOs prioritise over the next 12–18 months to ensure agentic RAG transitions from a technical capability into a sustained source of competitive advantage?

APAC CISOs face an escalating battle as AI agents rapidly outpace traditional defences. Key issues include distinguishing legitimate actions from malicious automation, soaring fraud speeds, and customer attrition from either excessive friction or unreimbursed losses. 

The Biocatch report, the future of Digital Trust, concluded that with 86% viewing AI agents as the industry’s greatest vulnerability, leaders urgently need real-time behavioural insights and interbank collaboration to preserve trust.

To know more about this and to help CISOs at the region’s banks find solutions to this rising AI-driven fraud incidents, we are joined by Subhashish Bose, Director of Global Advisory, BioCatch.

1.       What are the key salient points of the future of digital trust report?

2.       How can we distinguish legitimate AI-assisted customer actions from agentic AI-driven fraud in real time?

3.       What behavioural and intent-based signals can replace static identity checks as AI agents mimic human behaviour?

4.       How do we prevent customer attrition caused by either excessive friction or unreimbursed scam losses? (intelligent friction?)

5.       What interbank intelligence-sharing frameworks can we deploy to stop authorised fraud at the receiving account stage?

6.       AI-powered scammers are on the rise. How do we accelerate fraud detection systems to match the rising speed of AI-generated attacks?

7.       What investments are needed to counter agentic AI attacks that 79% of our peers have already encountered?

8.       How should we restructure fraud and scam reimbursement policies to maintain trust without increasing vulnerability?

9.       What metrics will tell us whether our AI defences are reducing fraud losses or merely shifting criminal tactics?

10.   What is your advice for CISOs, CIOs and banking executives in the face of this rising AI-driven fraud?

11.   What is the biggest myth related to financial fraud with AI?

CFOs in Southeast Asia and Hong Kong face a new reality: talent is now a strategic risk. Between 2026–2027, cautious hiring contrasts with fierce competition for hybrid-skilled professionals who blend accounting expertise, digital literacy, commercial acumen, and regulatory fluency. Automation and AI threaten traditional career pipelines, while rapid AI adoption, family office growth, and capital market resurgence intensify demand, driving attrition and salary inflation. CFOs must act as talent architects, restructuring teams, embedding AI governance, and building resilient succession plans to safeguard leadership continuity against competitive pressures and workforce disruption.

In this PodChats for FutureCFO, Angus Tsang, CFO and Company Secretary, CN Logistics International Holdings Limited, shares his thoughts on how finance leaders transforming the finance function to align to business priorities and market dynamics.

1. How are CFOs redefining the finance operating model to balance cost efficiency with the strategic agility required to support business growth in 2026-2027?

2. Do CFOs have a clear inventory of the skills they need versus the skills they possess, particularly regarding AI, data analytics, and regulatory technology?

3. How are CFOs adapting their talent acquisition strategy to compete for "versatile" talent in a market where specialists command significant salary premiums?

4. What is the CFO’s strategy for managing the "automation paradox"—automating routine work without eroding the developmental pathways for early-career finance professionals?

5. In your view, are succession plans for critical roles (e.g., Controllers, FP&A Heads, Tax) robust enough to withstand unexpected departures in a volatile hiring market? Is this succession plan reactive (someone resigns) or proactive?

6. What should be the approach to managing the emerging risks associated with AI governance, specifically ensuring that the team has the talent to oversee algorithmic decision-making and regulatory compliance?

7. How are CFOs leveraging the fluidity of regional hubs (Singapore, Hong Kong, Malaysia) to access talent pools that were previously out of reach?

8. Given the rise of contract roles (fractional/project) driven by transformation projects, how are CFOs (and CHROs) balancing permanent headcount with flexible talent to maintain organisational resilience?

10. How do CFOs measure the ROI of their talent development programmes, specifically regarding their impact on retention and internal promotion rates for leadership roles?

This year’s Earth Day (22 April), the conversations pivot from carbon accounting to carbon action. While APAC CIOs have embedded sustainability dashboards, the rise of autonomous agents threatens to undo this progress. 

In 2026, an uncontrolled "agent sprawl" could exponentially increase compute, data storage, and energy use—directly conflicting with Net Zero pledges. True sustainability isn’t just about reporting emissions; it’s about embedding green governance into every autonomous decision. 

As agents become "digital coworkers," CIOs must treat energy efficiency and waste reduction as non-negotiable compliance metrics, ensuring AI acceleration doesn't come at the planet’s expense.

With us to understand what Earth Day means in the context of the exploding AI agent sprawl is Mr Liher Urbizu, present and MD of SAP Southeast Asia.

Questions covered:

1.       Give us the agentic sprawl in Southeast Asia in 2026.

2.       How do you embed "carbon-aware" policies directly into agent workflows? This should force autonomous agents to defer non-urgent batch processing to times of renewable energy availability. (treat carbon data like financial data)

3.       With Earth Day commitments tightening, what technical controls are required to mandate energy consumption caps per agent, treating efficiency as a governance rule rather than a post-execution report?

4.       To ensure agents don't inadvertently increase waste, how do you establish trusted data lineage for Scope 3 emissions, enabling an agent to verify a supplier's carbon intensity before autonomously placing an order?

5.       Given that poor data quality leads to redundant processing, what data governance rules are necessary to prevent agents from repeatedly querying or transforming the same inefficient datasets, wasting energy?

6.       How do you build a "sustainability audit trail" for every autonomous decision, allowing CIOs to trace a specific agent's action back to its energy cost and carbon footprint for regulatory reporting?

7.       As we manage agents like digital coworkers, what "retirement criteria" ensure that low-value, high-frequency agents are automatically decommissioned to prevent long-term energy leakage? (leanIX)

8.       To avoid "shadow agent" sprawl doubling your infrastructure emissions undetected, what discovery tools can catalog every autonomous agent and calculate its real-time energy consumption against your Net Zero milestones?

9.       With stakes higher than Shadow IT, how do you differentiate between essential agents that optimize sustainability (e.g., logistics routing) versus "rogue" agents that create unnecessary digital waste and technical carbon debt?

10.   Where is the starting point for my organisation to move towards a more sustainable IT operation?

In 2026, the risk engineer in Asia faces a fractured reality. Geopolitical decoupling has splintered supply chains across Southeast Asia, while simmering South China Sea tensions directly threaten subsea cables—the region’s digital arteries. 

Concurrently, climate-driven heatwaves stress power grids, collapsing OT systems in manufacturing hubs. The core dilemma is no longer single-peril analysis but the "poly-crisis": ransomware demands spiking as a grid fails, or a sovereign cyber operation triggering an insurance exclusion. 

For Asian risk engineers, resilience means stress-testing for layered shocks—where a trade war, a flood, and a data exfiltration all arrive on the same Tuesday.

Vivien Bilquez, global head of Cyber at Zurich Resilience Solutions, answers the following questions on resilience imperatives as the region faces its most challenging crises to date. 

1.       To set the context for our dialogue, please briefly provide a state of resilience for organisations in Asia today?

2.       With global trade splitting into US and China-centric blocs, which regulatory regime (export controls, data localization) costs/is costing/will cost businesses in Asia the most to operate under?

3.       Are existing power/electricity backups designed for simultaneous crises (e.g., heatwave blackout plus ransomware), and can we recover in milliseconds rather than minutes?

4.       How much do businesses rely on subsea cables through the South China Sea or Strait of Malacca, and what is the backup route if a cable is cut? 

5.       If a nation-state or hacktivist group shuts down existing OT systems (e.g., cooling or chemical delivery), what is the financial loss per hour of halted production?

6.       Do prevailing insurance policies exclude "sovereign cyber operations" (Stryker clauses), and have organisations moved from relying on insurance to building quantified self-resilience?

7.       When an AI-driven disinformation campaign targets an organisation’s brand or a climate event shuts plants/production facilities, do organisations have a playbook that unites engineering, the CISO, and the CFO within ten minutes? (If not, can you suggest such a playbook?)

8.       State the resilience posture of organisations in Asia

9.       What questions do I ask to put my organisation on the track to resilience?

10.   What do I need to do to put my organisation on the path towards resilience?

For ASEAN CIOs in 2026, the AI paradox is clear: budgets are rising, yet financial returns are not. With almost half the region scaling AI beyond pilots, we have hit a "data wall". The shift to agentic AI has made integration the new control plane. 

To move from ambition to monetisation, leaders must stop managing data in silos and start activating it in real-time across finance, supply chains, and customer systems. 

Without a unified data fabric that ensures governance and trust, autonomous agents cannot operate safely at scale. Data activation is no longer an IT project; it is the core strategy for turning AI spend into EBIT.

Joining us to clear the cobwebs of this data wall, is Mr David Irecki, chief technology officer for Asia Pacific & Japan at Boomi.

David, welcome back to PodChats for FutureCIO.

1.       Boomi cites an interesting statistic: 95% of organisations struggle with AI ROI, yet you argue the models are ready. Where are ASEAN CIOs getting stuck—and why are data quality and integration now the real villains, not the AI? (Singaproe report)

2.       Beyond lakes and dashboards, what does "data activation" mean in practice? How do we put live, trusted data into the flows AI agents rely on?

3.       As Agentic AI explodes in 2026, why should CIOs see APIs and integration as the new "control plane" for security, privacy, and sovereign AI?

4.       According to Boomi, with 90% of staff using AI informally, how do we enforce data governance without killing speed? Can the integration layer automate policy enforcement?

5.       Define data debt. How do we build a business case for killing "data debt" and moving from brittle scripts to reusable, AI-ready integrations?

6.       According to Salesforce, 96% of CIOs say success hinges on integrating AI into the flow of everyday work. Where do ASEAN CIOs see the fastest payback for data activation—finance, supply chain, or customer service?

7.       How does activating data for a swarm of autonomous agents differ from powering a simple chatbot? How do we make different vendors' agents talk to each other?

8.       If Asia has hit a data wall, what are the three non-negotiables for CIOs to turn AI spend into EBIT (Earnings Before Interest and Taxes) by 2026?

9.       Takeway for CIO to get their CIO initiatives from delivering disappointing results to powering the business innovations? 

From IT’s view, enabling the workplace means ending the chaos of disjointed apps as well as siloed technologies and work environments. This workplace complexity breeds fragmentation spikes where teams juggle chat, docs, and tickets while workflows stall. 

One of the CIO’s critical missions in 2026 should be to restore flow: a unified system where conversations trigger actions, not more tabs. We need platforms that reduce IT firefighting by embedding knowledge, automation, and follow-through into collaboration itself. 

When work moves seamlessly from talk to completion, only then can we finally stop maintaining tools and start enabling outcomes. 

This is the Resolution Economy – an economic model that focuses on guaranteed outcomes, reduced fragmentation and systemic resolution beyond experience. For the IT department, the resolution economy means fewer alerts, smoother integrations, and a digital workplace that works as one.

Joining us on PodChats for FutureCIO is Carlos Quaderi, head of Asia, Zoom. He will share his perspective on the technologies and workflows for enabling workplace and collaboration for distributed IT teams.

Questions

1.       How do we measure ROI when collaboration platforms evolve from communication hubs to operational “systems of action”?

2.       With AI agents joining workflows, how do we govern data privacy across ASEAN’s varying regulations?

3.       Can our current stack reduce fragmentation without forcing yet another new tool on employees?

4.       What metrics truly indicate workflow completion velocity, not just user activity?

5.       How should we rethink vendor lock-in when a single platform begins controlling both conversation and execution?

6.       Will hyperlocal infrastructure (e.g., Indonesia’s data sovereignty laws) limit seamless cross-border collaboration?

7.       How do we balance frontline worker needs with knowledge workers in one integrated platform?

8.       What new security boundaries are needed when AI “follow-through” pulls data across previously siloed systems?

Despite rapid digital acceleration across Southeast Asia, enterprises remain trapped in a costly cycle of reactive cybersecurity and third-party risk management. Fragmented vendor ecosystems, opaque AI integrations, and siloed threat data force CISOs into perpetual firefighting rather than strategic anticipation. 

As regulatory expectations tighten and attack surfaces expand through generative and agentic AI, waiting for incidents to strike is no longer viable. Regional leaders must pivot from compliance-driven checkboxes to intelligence-led oversight. 

By unifying external threat intelligence, continuous vendor monitoring, and AI-augmented analytics, ASEAN organisations can break the reactive loop and build resilient, forward-looking risk architectures.

In this PodChats for FutureCISO, Mark Harris, solutions sales director APAC, for Diligent offers some practice insights and recommendations for how organisations in Asia can move out of reactive cyber habits in 2026.

1.       How are ASEAN enterprises currently measuring the gap between reactive incident response and proactive threat intelligence, and which metrics best validate a shift toward predictive oversight?

2.       Where do traditional third-party risk frameworks fall short in anticipating systemic cyber exposures introduced by agentic AI and cross-border cloud vendors?

3.       How can CISOs operationalise external threat intelligence and regional peer benchmarking to pre-emptively adjust controls before attackers or regulators force a reaction?

4.       What balance should organisations strike between AI-driven automation for vendor assessments and human-led judgement for nuanced, jurisdiction-specific supply chain risks?

5.       Which intelligence-led reporting narratives are successfully converting technical cyber and third-party exposures into actionable board-level strategy across diverse ASEAN markets?

6.       How are divergent regional data and AI regulations (e.g., PDPA, MAS, BSSN, NPC) creating reactive compliance silos, and what unified frameworks can harmonise oversight?

7.       What underutilised data signals or external intelligence sources could transform your organisation from reactive firefighting to continuous, predictive risk management?

8.       As AI-augmented vendor ecosystems become more autonomous, what new governance models will CISOs need to maintain intelligence-led oversight without stifling regional innovation?