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CXOCIETY (read "society") is the platform for senior business, technology, finance and operations executives to discuss, share and discover the latest in technology, process and people innovation."CXOInsights" by CXOCIETY is the repository of shared insights and experiences by the best, brightest and most experienced professionals globally. Subscribe to "CXOInsights" by CXOCIETY to keep abreast in the latest in all things innovation.

  1. vor 3 Tagen

    PodChats for FutureCFO: AI in finance as a compliance imperative

    A 2026 Wolters Kluwer report reveals that a striking 83% of APAC CFOs see AI adoption as a key force reshaping finance, while 72% believe its impact will be significant within three years. As understanding of what AI do for finance teams, we are starting to see the adoption narrative move from a discretionary "innovation project" to a necessary part of the governance and controls framework—a language CFOs and compliance officers understand intimately.  To be clear, anxieties about moving fast (in the adoption journey) remain persistent as is maintaining trust, a theme echoed in the Deloitte survey which found CFOs reinforcing fundamentals and cost discipline even as they invest in AI. In this PodChats for FutureCFO, Nikhil Parambath, Regional Vice President for Asia at BlackLine, offers some insight into how CFOs and the finance leadership can finetune their adoption strategies as AI moves from a nice to have to a compliance imperative. Nikhil, welcome back to PodChats for FutureCFO. 1.       Across Asia, CFOs are being asked to close faster and support real-time decisions, yet many close processes remain stitched together with spreadsheets and manual workarounds. Where are finance teams in the region still most vulnerable to this "spreadsheet dependence," and what specific risks does this create for a CFO's ability to 'trust the numbers' in a volatile environment?  2.       BlackLine uses the term "self-driving close." In business terms, what does this operating model look like in practice, and what are the biggest misconceptions finance leaders in Southeast and Northeast Asia have about it?  3.       As agentic AI evolves from copilots to autonomous actors, which specific close activities—such as reconciliations, journal entries, intercompany matching, and variance analysis—are the safest and most impactful to automate first, giving finance teams the fastest return on confidence and efficiency?  4.       Agentic AI is only as good as the data it operates on. Before a CFO can confidently let parts of the close run on "autopilot," what critical data, process, and control foundations need to be in place to ensure governance, security, and an auditable chain of trust? Foundational readiness 5.       Controllable autonomy As the system starts handling the "heavy lifting" of routine tasks, the finance professional's role is shifting from processor to validator and strategist. How do you see the role and skillset of finance teams evolving over the next 2-3 years, and how should CFOs prepare their people for this transition to an advisory role?  6.       In a region marked by rapid digitalization yet persistent skills gaps, what are the key implementation challenges for CFOs in places like Singapore, Hong Kong, and Japan who are trying to scale AI-led finance?  7.       As AI agents become more autonomous, questions of accountability arise. How can CFOs adapt their internal controls and compliance frameworks to effectively "govern" AI, ensuring the autonomous close meets regulatory standards?  8.       Finally, how does achieving a "self-driving close" free the CFO's office to focus on what matters most—such as strategic analysis, partnering with the business, and steering the organization through volatility?

    PodChats for FutureCFO: AI in finance as a compliance imperative
  2. vor 3 Tagen

    PodChats for FutureCIO: The digital traffic jam of 2026

    For Asia’s CIOs, 2026 signals the dawn of the Agentic Era—where AI shifts from chatbots to autonomous co-workers. Yet consumer ease with LLMs hides enterprise realities: compute demand straining grids, legacy networks choking progress, and “vibe hacking” agents undermining trust.  By 2027, reasoning models like Claude Mythos will force CIOs to govern agentic swarms, rewriting IAM and latency for a new digital order. In this PodChats for FutureCIO, Jeetu Patel, president and chief product officer, Cisco, answers critical technology questions CIOs and Heads of Technology must grapple as quickly as they can. Risk and security 1.       With AI agents “vibe hacking” executive styles, how do we defend enterprises when traditional security fails—and who’s accountable when autonomous agents act without human oversight?  2.       Southeast Asia prioritizes data sovereignty. How can CIOs keep AI fast and efficient without illegally moving sensitive data across borders? Infrastructure reality 3.       AI agents generate 100x more network traffic than humans. With hybrid AI adoption surging, how do we prevent a digital congestion collapse in 2026? 4.       Power grids are strained, yet data centres must act as one. Should CIOs embrace complex distributed clusters or invest in smaller, localized GPU pools? Readiness for 2027 5.       Agent-to-agent commerce is coming. As consumers and partners start using AI agents to interact with businesses, how can enterprises ensure their backends are "machine-readable" and they don't become invisible in this new agent-driven economy? 6.       With AI shifting from automation to orchestration, how should ROI be measured—cost savings, or agility and revenue creation? 7.       Scaling agentic systems makes old monitoring tools obsolete. Should CIOs rebuild telemetry and observability stacks from scratch to manage high-speed interactions? The challenge of industrializing AI is about moving from isolated pilots to "AI factories". With plans to scale agentic systems, old monitoring tools are obsolete. Should CIOs in the region be planning to rebuild their telemetry and observability stacks from scratch this year to manage these complex, high-speed interactions? 8.       Our topic is The digital traffic jam of 2026. What is your suggestion/suggestions for CIOs and even board as they look to embed AI in the way of work?

    PodChats for FutureCIO: The digital traffic jam of 2026
  3. 6. Aug.

    PodChats for FutureCIO: Architecting storage to power AI agility

    APAC enterprises face data sovereignty fragmentation, IT talent shortages, and sustainability mandates. Enterprise storage is now pivotal to AI success—reshaped by engines like IBM's 5th Generation FlashCore Module (FCM5) that autonomously handle deduplication, encryption, and compression. Yet CIOs must secure data end‑to‑end, from ransomware recovery to quantum‑safe archival, procuring storage that adapts, protects, and optimizes relentlessly for the AI era. In this PodChats for FutureCIO, Barry Whyte, Principal Storage Specialist and Master Inventor at IBM, to talk about the forgotten technology that is core to the continuing development and use of AI in the enterprise. 1.       What are the three most critical pain points facing APAC enterprises as AI transforms storage from passive repository to active computational engine?  2.       How do you see data sovereignty regulations, skills shortages, and sustainability mandates compound these challenges across the data lifecycle? 3.       How is AI fundamentally reshaping storage technology development—from computational offload (deduplication, compression, encryption) to autonomous performance tuning? 4.       Where do autonomous AI agents deliver maximum value in the storage lifecycle—real-time ransomware recovery, predictive capacity planning, or dynamic workload optimization?  5.       What does this mean for CIOs architecting infrastructure that must adapt to unpredictable generative and agentic AI workloads? 6.       How can APAC CIOs prioritize use cases that address region-specific constraints like space-limited datacentres and carbon neutrality deadlines? 7.       As post-quantum cryptography transitions from "decades away" to "plan now," how should APAC’s financial and government sectors rethink storage security architecture to protect AI training data and models across their entire lifecycle—from ingestion to archival—against "harvest now, decrypt later" threats? 8.       Given that AI is compressing hardware refresh cycles while demanding greater capital efficiency, how should APAC CIOs and storage architects balance cloud-adjacent consumption models with on-prem computational storage investments to optimize TCO across the AI data lifecycle? 9.       What is your recommendation for CIOs architecting storage to power AI agility?

    PodChats for FutureCIO: Architecting storage to power AI agility
  4. 22. Juli

    PodChats for FutureCISO: Defending against the invisible

    Before Stuxnet, there was fast16: a state-grade sabotage framework that didn’t steal data or crash systems. It silently altered engineering simulations and calculations—poisoning digital twins while everything appeared normal. Now imagine AI giving attackers the power to find such weaknesses in hours. As Singapore expands protections beyond core CII, fast16 is a warning: tomorrow’s breach won’t hold your data hostage. It will corrupt the simulations and AI models you trust to run your plant, bridge, or refinery. And you won’t know until something breaks. In this PodChats for FutureCISO, Vitaly Kumluk, cybersecurity researcher at SentinelOne Lab, SentinelOne, sheds light on what cybersecurity teams need to know and be prepared against this new breed of cyberthreats. 1.       What is the role of a researcher in the cybersecurity space? 2.       In a nutshell, what is fast16 and what makes it different from other categories of cyber threats? 3.       How do we identify which of our engineering simulations, digital twins, and AI training pipelines are most vulnerable to silent output manipulation—and do we have any validation layer that checks results against physical or independent models? 4.       How do we detect an attack that changes calculations but leaves systems running normally? 5.       What stops an AI-powered attacker from finding a hidden weakness in our simulation software? 6.       How do we assess and continuously monitor the integrity of simulation outputs from external partners, cloud-hosted digital twins, or legacy OT environments we cannot directly instrument? 7.       Our incident plan covers ransomware. Do they cover a scenario where a state-grade actor has been quietly corrupting our engineering decisions for six months? How do we roll back trust in our own data? 8.       If an attacker manipulates a supporting system’s simulation to cause a real-world failure, will current cyber insurance or legal framework treat that as a “breach” or as a “design error”? 9.       How do we differentiate between adversarial attacks on the AI’s availability (denial) vs. subtle corruption of its reasoning or output distribution—and which defensive architectures apply? 10.   Given what we now understand about fast16, what is your recommendation for moving forward?

    PodChats for FutureCISO: Defending against the invisible
  5. 22. Juli

    PodChats for FutureCIO: Trends shaping the CIO agenda for 2026–2027

    A recent Gartner survey found that only 28% of AI use cases fully meet ROI expectations, with a further 20% failing outright. For Asia-Pacific CIOs, the bottleneck is clear: it is not the model, but the governance and orchestration layer beneath it.  In 2026, the challenge has shifted from experimentation to industrialisation, demanding a focus on taming "agent sprawl" and mitigating "shadow AI" risks.  As Celine Siow, VP of Sales, GM for APAC at Workato argues, the control plane must be platform-agnostic to avoid recreating fragmentation. The path to 'production-ready AI' lies in a robust, vendor-neutral governance layer that ensures trust, interoperability, and measurable business value. She joins us on this edition of PodChats for FutureCIO to elaborate further on her arguments for a platform-agnostic control plane as CIOs orchestrate the industrialisation of AI. 1.       With only 28% of AI projects meeting ROI targets, how can we build a formal "value playbook" to ensure our AI investments deliver tangible, measurable business outcomes? 2.       As "agent sprawl" becomes the new technical debt, how can we architect a neutral control plane to govern, orchestrate, and observe our growing fleet of autonomous agents? 3.       Given that 80% of workers now use unapproved AI tools, how can we move from simply blocking "shadow AI" to enabling governed, safe adoption across the entire workforce? 4.       What does an effective governance framework look like when AI moves beyond content generation to action management, requiring real-time control over permissions, escalation, and audit trails? 5.       With AI infrastructure costs set to run up to 30% higher than planned, how should our FinOps practices evolve to manage this new cost volatility, including token-based consumption?

    PodChats for FutureCIO: Trends shaping the CIO agenda for 2026–2027
  6. 20. Juli

    PodChats for FutureCIO: Innovation-focused IT budget strategies

    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?

    PodChats for FutureCIO: Innovation-focused IT budget strategies
  7. 20. Juli

    PodChats for FutureCIO: Tips for safeguarding AI integrity

    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.

    PodChats for FutureCIO: Tips for safeguarding AI integrity
  8. 13. Juli

    PodChats for FutureCIO: Turning APAC’s AI Pilots into Profits in 2026

    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. What is RAG?Given that most regional AI pilots never scale, what specific architectural weaknesses does agentic RAG fix that traditional RAG or fine-tuning cannot?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?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?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? 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?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?(original 3) How should CIOs in Singapore and across Southeast Asia measure the ROI of retrieval intelligence compared to simply upgrading large language models?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?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?

    PodChats for FutureCIO: Turning APAC’s AI Pilots into Profits in 2026

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CXOCIETY (read "society") is the platform for senior business, technology, finance and operations executives to discuss, share and discover the latest in technology, process and people innovation."CXOInsights" by CXOCIETY is the repository of shared insights and experiences by the best, brightest and most experienced professionals globally. Subscribe to "CXOInsights" by CXOCIETY to keep abreast in the latest in all things innovation.