AI Appreciation Day: What next after agentic AI?

Agentic AI conceptual artwork generated by Google Gemini | Imagen 4.

How we look at AI has changed in 12 months. On AI Appreciation Day, which was first celebrated on 16 July in 2021, industry observers suggested new dimensions to AI approaches. 

Wai Kit Cheah, Senior Director of Products and Solutions, Asia Pacific at Lumen Technologies, said that World AI Appreciation Day is more than a celebration of innovation. "It’s a moment to reflect on the duality of AI and its growing influence on our digital lives. In Asia Pacific, where digital transformation is accelerating across sectors, AI is both a catalyst for progress and a challenge to security," he said.

"There’s a clear shift in how businesses view AI. It’s no longer a futuristic add-on, but a core component of daily operations. This shift has been enabled by advances in generative AI and, more importantly, by a growing emphasis on usability," said Simon Ma, MD, Asia, Freshworks.

"AI that can self-learn, require minimal tuning, and work across systems is what ultimately delivers sustainable value." 

Christanto Suryadarma, VP for Southeast Asia (SEA), South Korea and Channel APJeC, Zebra Technologies, shared that AI already powers product recognition, machine vision, robotic navigation, and package dimensioning. 

"Zebra’s latest Warehouse Vision Study reveals 78% of decision-makers see AI as crucial for operational resilience, improving forecasting, stock management, and space use. We’re moving beyond automation to empower people and processes," he said. 

"By embedding AI into frontline systems, businesses can enhance operations, asset visibility, and connectivity."

Guna Chellappan, GM for Singapore, Red Hat, said that Red Hat believes in the power of open source to democratise AI. "I am bullish about the opportunities ahead for us in AI, especially with the Singapore government’s focus on AI," he said.

Gayathri Peria, GM for Southeast Asia, SUSE, said that Southeast Asia has an appetite for open systems. "Open ways of AI development enable local innovators to build on global code, rather than starting from scratch, lowering entry barriers and accelerating time-to-market. These advantages are especially relevant in Southeast Asia, a diverse market where a 'one size fits all' approach rarely works. Recent regional government discussions about AI – whether it's Singapore's landmark budget investment announcement, Malaysia’s newly launched AI Office, or Indonesia’s review of AI regulations – speak to the importance of AI adoption at a national policy level," she said.

"Ultimately, AI success is inseparable from architecture. Treat every layer – model, data and infrastructure – as interchangeable building blocks to avoid lock-in and stay agile as breakthroughs emerge. On AI Appreciation Day we celebrate not just what AI can do, but how we choose to build it. With open source, businesses can innovate securely, transparently and on their own terms," she added.

Agentic AI

Nick Magnuson, Head of AI, Qlik, said: "At Qlik, we believe the future of AI goes beyond automation, it’s about empowerment. The true strength of AI lies in elevating our collective intelligence to address unmet challenges and opportunities. But for AI to deliver real-world value, it needs more than algorithms. It requires context, quality data, strong governance and a clear sense of purpose.

"Today, agentic AI is compelling organisations to redefine how they operate. Agentic systems don’t just respond—they reason, collaborate and take actions to solve real business challenges. From fraud detection to customer experience, we're seeing early signs of a digital ecosystem where AI agents can operate with autonomy and deliver measurable outcomes." 

AI has graduated, said David Irecki, CTO for Asia Pacific & Japan at Boomi. “AI is no longer on the sidelines — it’s moving from pilots to core operations. Today, AI is not just a tool, but a strategic priority for enterprises across Asia Pacific. Driving this shift is agentic transformation, where AI agents work autonomously across functions to enhance decision-making, boost productivity, and accelerate outcomes," he said. 

"We’re witnessing a new phase — one that builds on the foundations of digital transformation, but goes further. Agentic transformation introduces a new operating layer, powered by systems capable of learning, reasoning, and acting independently."  

The human aspect

Daniel Hein, Field CTO, Informatica Asia Pacific and Japan noted that the businesses in the APAC region have surpassed global counterparts in implementing generative AI into business practices. "Particularly, agentic AI drives optimised decision-making in sectors like energy and finance, while generative AI democratises problem-solving by empowering non-technical users," he noted. 

"Continuous retraining, reskilling, and upskilling—with a focus on AI literacy—have become essential across all roles, from entry-level positions to senior leadership.”

BlackLine, which specialises in financial solutions, has indeed seen a better experience with the use of AI. Jeremy Ung, CTO, BlackLine said: "We've seen significant gains in efficiency, with customers saving countless hours on tasks like document summarisation and transaction matching, allowing them to redirect their expertise to critical analysis and decision-making.

"A core principle of our approach is user control and trust. In finance, accuracy is non-negotiable. That's why BlackLine's AI solutions are designed to allow users to accept or reject AI outputs and fosters a continuous learning loop."

"We’re seeing growing interest in how AI can optimise what’s already in place for better finance and supply chain management, improved visibility across the value chain, and hyperautomation in low code app development. But that starts with a strong foundation of market-leading and vendor-agnostic strategies. Innovation happens when businesses can modernise at their own pace, keeping what works while exploring what’s next," said Han-Tiong Law, Regional CTO ASEAN and Greater China, Rimini Street.

"The question is no longer 'how fast can we adopt AI?' but rather, 'how do we adopt and deploy AI in a way that actually serves the business?'”

Bernard Montel, EMEA Technical Director and Security Strategist, Tenable, mentioned the people aspect as well. "To truly harness the power of AI in our computing environments, organisations must champion AI as a tool for augmentation, not replacement. This means designing systems where AI handles repetitive tasks, freeing humans to focus on complex problem-solving, innovation, and ethical oversight. Prioritising human creativity and judgment is paramount as AI continues to advance. Alongside AI literacy, educational initiatives should emphasise critical thinking and adaptability," he said.

Security

"AI’s rapid evolution has empowered cyberattackers with tools that are faster, more evasive, and alarmingly convincing. Generative AI is now being weaponised to craft hyperpersonalised phishing campaigns, deepfake-driven social engineering, and adaptive malware that can bypass traditional defences," Cheah shared. 

"In fact, we’re seeing a surge in AI-enhanced threats targeting critical sectors like healthcare, finance, and government across the region. Yet, this same technology is also redefining how we defend. Security teams are increasingly deploying AI to detect anomalies, anticipate risks, and respond in real time. 

"From predictive analytics to autonomous threat hunting, AI is enabling a shift from reactive to proactive cybersecurity. We’ve observed how AI-driven threat intelligence—when combined with human expertise—can significantly reduce dwell time and improve incident response outcomes."

Andrew Kay, Director Systems Engineering, APJ - Illumio, also touched on security. "AI Appreciation Day is the perfect time to reflect on the impact of AI on the businesses we all rely on," he said. "When it comes to cybersecurity – there are big gains, but drawbacks too."

"On one hand, AI is increasingly being used by threat actors to ramp up their attacks. Today’s threats are not only becoming more sophisticated – they’re also becoming more accessible, allowing even novice cybercriminals to carry out highly effective attacks. AI threats aren’t just a talking point for cyber experts – they’re real and impact everyday workers. A finance worker at a multinational Hong Kong bank, for example, transferred US$25 million after attackers used a Zoom deepfake scam to pose as the company’s chief financial officer," he shared.

"On the flip side - AI is enhancing cybersecurity technologies in new and exciting ways too. AI cloud detection and response (CDR), for example, is a new tool that identifies lateral movement risks, detects attacks, and contains breaches instantly — all at cloud scale."

Kay said that AI is powering security graphs allowing organisations to visualise risk and get an unparalleled view of their hybrid cloud attack surface. "This kind of visualisation and observability is incredibly important for organisations to identify unusual patterns and behaviours of attackers that otherwise largely go undetected," he said.

"With AI-powered attackers constantly scanning for gaps and adapting their techniques to evade defences they discover, prevention isn’t enough. Organisations need to meet fire with fire. They need containment, with AI-driven context and visibility, to block lateral movement and limit the blast radius when something breaks through," Kay added.

Parvinder Walia, President of the Asia Pacific Region, ESET, also mentioned the deepfake incident in Hong Kong. "Cybercriminals, too, are using AI and doing so at speed. Their operations now resemble agile software teams. Deepfakes, impersonation scams, and voice clones have become common and convincingly real," he said.

"In 2024, a finance employee in Hong Kong was tricked into paying out US$25 million after a video call with a deepfaked CFO. A survey done in Singapore this July showed that three in four people could not detect deepfakes, despite 80% of them being confident of being able to do so.

"Staying safe in the AI era means evolving how we apply digital hygiene: verify sources, avoid oversharing, be alert to ‘learning’ features that harvest data, and question out-of-the-blue communications that trigger fear or urgency. Most critically, workers need AI-powered cybersecurity that anticipates - rather than reacts to threats, and scales with how we live and work today," Walia added.

AI has changed the face of cybersecurity, agreed Jasie Fon, Regional VP, Asia at Ping Identity. "From deepfakes to autonomous agents, AI has transformed the landscape of identity-based cyberthreats, making it increasingly difficult to verify who, or what, is behind a digital interaction. Without the right safeguards, these technologies risk eroding the trust that underpins everything from financial services to healthcare," she said.

"Yet AI is also a powerful tool for defence. When deployed responsibly, it can enhance real-time risk detection, behavioural analysis, and adaptive authentication, helping organisations prevent fraud while improving the user experience.

"As AI continues to evolve and agents become more autonomous, now is the time for organisations to rethink identity models, ensure secure delegation, and prepare systems to recognise and authenticate not just people, but the intelligent processes acting on their behalf.

"Building and maintaining trust in every digital interaction is more essential than ever, and organisations must ensure their identity strategies evolve in lockstep with the technology driving today’s transformation."

Teck Wee Lim, Area VP, ASEAN, CyberArk, also referred to the threats from agentic AI. "The rapid adoption of AI and the rise of cloud-native technologies have resulted in machine identities now far outstripping human identities. The CyberArk 2025 Identity Security Landscape report found that there are 82 machine identities for every human one in organisations today, and this ratio is expected to continue widening with the advent of agentic AI," he said.

"This is creating a massive problem as these AI agents are able to make decisions autonomously without human input and escalate their access privileges within organisations’ IT systems by themselves. They can also be exploited by malicious actors to gain access to these systems. The top priority for organisations is to address these vulnerabilities by deploying an AI-powered, scalable and unified identity security solution, starting with machine identity security."

"CyberArk also advocates that companies, governments and researchers come together to build proactive frameworks that can stay ahead of their AI-enabled adversaries," Lim said.

"Identities – both human and machine – are central to the functioning of modern systems and therefore much of the conveniences we take for granted today. AI Appreciation Day therefore serves as a timely reminder of the need to strengthen the governance and security of these identities as AI continues to remake our modern society."

Montel highlighted AI's role in presenting multifaceted cybersecurity threats as well. "We're seeing everything from sophisticated AI-generated deepfakes designed to trick employees into making fraudulent bank transfers, to simplistic AI-generated malware leveraging known flaws through phishing attacks. 

"The most effective approach to defending against and mitigating these threats mirrors current cyberdefence strategies: preemptive exposure management to address vulnerabilities before they're exploited, and robust employee education on suspicious requests, no matter how compelling they may seem," he said.

Chaim Mazal, Chief Security Officer, Gigamon, said the full value of AI will only be realised if we can govern and secure it with the complete visibility needed to truly understand how it operates across infrastructures.

"This is proving to be more difficult, as AI is adding new complexities to networks, expanding attack surfaces, and increasing security risks. In fact, research shows one in three organisations have already seen network traffic double from AI workloads alone. This explosion in data can overwhelm traditional security tools, obscuring visibility into how AI is behaving, and what information it's accessing," he said.

"With the ongoing adoption of hybrid cloud infrastructure and the increasing use of AI, the need for real-time visibility into all data in motion, including encrypted and lateral (east-west) traffic, has never been more urgent. Without it, companies are exposing themselves to unintended data leakage or even malicious misuse by AI agents."

"On AI Appreciation Day, we’re reminded that progress and protection must go hand in hand. Key to that will be the best security and IT talent to both innovate and govern AI use. The human element is a critical component to successful AI and must not be forgotten. 

"Building a secure AI future means ensuring our teams are empowered to pair innovation with accountability and use network telemetry, data loss prevention, and deep observability to ensure that as AI gets smarter, we stay in control," Mazal added.

"If we can see it, we can secure it, and that’s how we truly unlock AI’s full potential without opening ourselves up to devastating risk."

Gerry Sillars, VP Asia Pacific and Japan, Semperis said: "Overall, AI lowers the skill barrier for attackers, enabling them to create more targeted, scalable, and sophisticated attacks." 

Sillars highlighted that Active Directory is a popular target in enterprises, and added: "We believe the effectiveness of AI in cybersecurity depends on the integrity of the data that fuels it. Without quality, well-governed data, even the most advanced models can produce unreliable results, opening up new vulnerabilities. That’s why we emphasise a 'data- first' mindset. In the context of identity threat detection and response (ITDR), AI is only as powerful as the context it understands."

Lee Anstiss, Regional Director, Southeast Asia and Korea, Infoblox, suggested that agentic AI can potentially enable pre-emptive security. "Instead of waiting to react to threats, these agents can proactively detect anomalies in DNS traffic and correlate patterns with threat intelligence. From there, they can either autonomously take mitigation steps or alert human defenders. This capability is especially critical as threat actors increasingly leverage AI to launch faster, more targeted attacks at scale," he said.

"Today’s security landscape is asymmetric: defenders are overwhelmed, while adversaries are augmented by automation. Agentic AI helps reverse that imbalance – allowing organisations to move from passive monitoring to active, predictive defence.

"On AI Appreciation Day, we celebrate this leap forward. Securing the future won’t be about reacting faster — it will be about anticipating smarter."

Responsibility 

The conversation must go beyond cybersecurity, Cheah added. "As AI becomes more embedded in critical infrastructure, the stakes rise. We must be clear-eyed about the risks. The more we rely on AI, the more we need governance frameworks that prioritise transparency, fairness, and accountability. 

"This is especially vital in Asia Pacific, where regulatory landscapes are evolving and digital maturity varies widely across markets. Appreciating AI means recognising both its promise and its pitfalls. It means asking hard questions about bias, explainability, and control. It means ensuring that innovation doesn’t outpace our ability to manage its consequences. 

"As we look ahead, the challenge isn’t just building smarter systems—it’s ensuring they serve real human needs, solve real-world problems, and do so in ways that are secure, ethical, and inclusive. That’s the future we should be working toward—not just on World AI Appreciation Day, but every day."

Responsibility should be at the forefront of AI strategies today, agreed Dr Barry Norton, Milestone Systems Fellow. "On AI Appreciation Day, recognising the transformative power of AI goes hand in hand with reflecting on the responsibility that comes with it. As AI reshapes industries, public spaces and daily life, its development must be guided by ethics from the ground up, not added on as an afterthought," he said. 

"In high-impact areas like video analytics and public safety, organisations should lead with transparency, accountability, and a human-first mindset." 

"Trust is the foundation of successful AI adoption. That trust is earned through openness about how AI systems are built, how data is collected, and how decisions are made. Strong accountability ensures that humans remain in control and responsible for AI outcomes, especially where public safety is concerned," he elaborated. 

Responsibility extends to data stewardship, Dr Norton added. "AI Appreciation Day is also a moment to acknowledge the importance of responsible data stewardship. Ethical practices must go beyond compliance, especially with sensitive data. Privacy, fairness and inclusivity should be designed into systems from the start," he said. 

"By embedding ethics into every stage of AI development, we not only avoid harm; we unlock AI’s full potential to serve the public good. On this day of recognition, let us commit to shaping AI that is not just intelligent, but also principled and trustworthy." 

"As we witness the rise of agentic AI - the next generation of autonomous decision making systems, it becomes more apparent that innovation must be balanced with strong security and governance," observed Red Hat's Chellappan. 

Governance concerned Irecki as well. "Seventy percent of APAC organisations expect agentic AI to disrupt their business models within the next 18 months. To unlock its full potential, businesses must ensure AI is built on a foundation of trust — including quality data, secure infrastructure, and strong governance," Irecki cautioned. 

"We’ve seen what happens when those foundations are weak: AI delivering inaccurate outputs or drawing biased conclusions. Without oversight, innovation can lead to unintended consequences. 

"That’s why governance is essential. It must evolve with AI, ensuring systems are transparent, ethical, and aligned to business goals. Organisations that succeed won’t just adopt AI — they’ll lead with responsibility, resilience, and intent.” 

Sustainability

Said Jason Low, APAC Director, Iceotope: "Tech adoption is accelerating not just out of ambition, but necessity. 

"Yet AI demands more than compute power. It calls for stable energy, advanced cooling, land, water, and skilled talent - resources that many Southeast Asian markets are now actively scaling in step with digital growth. 

"According to Uptime Institute, 27% of AI training racks now exceed 50 kW, far beyond what traditional data centres were built to handle; especially in Southeast Asia’s hot, humid, and resource-stressed environments." 

"As we mark AI Appreciation Day, it is a timely reminder that the true potential of AI depends on whether our infrastructure can keep up and do so sustainably. For example, the Philippines is expanding capacity beyond Metro Manila, but hubs like Davao and Iloilo face water scarcity, power limitations, and growing pressure from local communities," Low added. 

"In Malaysia, new electricity and water tariffs could push energy costs up by 14%. Meanwhile, ESG scrutiny is rising. Countries like Indonesia are introducing stricter sustainability reporting, pushing operators to cut energy, water use, and emissions.

"At the same time, other APAC economies are beginning to confront a similar reality: the need to invest in sovereign AI infrastructure of their own. Over-reliance on Southeast Asia’s emerging data powerhouses may prove unsustainable in the long run, particularly as demand for localised compute, data governance, and energy-conscious infrastructure intensifies."

"To get ahead, nations must look beyond traditional infrastructure towards decentralised, hybrid, and resource-conscious systems. For instance, a typical 100 MW data centre can use over 4 million litres of water daily, but adopting hybrid liquid cooling can reduce energy use by up to 40% and water consumption by as much as 90%. If the region wants to lead in AI, the time to build it is now," Low concluded. 

Fundamentals

Alex Teo, VP & MD of Southeast Asia, Siemens Digital Industries Software, said AI's growing value "lies in being deeply embedded in our core operations, enabling seamless collaboration between humans and machines to address today’s evolving challenges and drive both innovation and sustainability". "To fully realise digital transformation, we must move beyond treating AI as a supplementary tool and instead integrate it across our processes," he said. 

Hein added that AI’s effectiveness will hinge on a robust data foundation that enables advanced analytics and reliable model performance. "Investing in strong data infrastructure and continuous upskilling is critical to fully harness AI’s capabilities and future-proof organisations," he said. 

Luca Spinelli, MD for Singapore, SAS Institute, said that value-driven decision-making stems from a foundation of data and analytics. "As organisations digitally transform, the ones that embrace analytics in their decision processes will gain a distinct advantage. With AI advancing faster than regulation and innovation surpasses understanding, trust and responsible innovation must take centrestage," he said.

"During this AI era, it is crucial to have the right software - powering trusted, scalable systems where reliability, compliance and results matter most. This is when, regardless of industry and the circumstances of vast amounts of data, decisions are the drivers of workforce and not the data in itself."

"Within the agents added to the workflows, businesses need to decide the optimal level of AI autonomy and human involvement based on the complexity of task, risk and business goals," Spinelli added.

Lim Hsin Yin, VP of Sales, ASEAN, Cohesity, noted that AI is an enabler for organisations to transform enterprise backup data into actionable business intelligence. "The democratisation of AI has eliminated the barriers that once made AI seem like an esoteric field, making it now accessible to a wide audience, and no longer restricted to specific sectors. That said, foundational processes and automation must be in place before organisations can leverage AI effectively," she said.

"At the heart of AI lies data – vast quantities of it. AI and machine learning algorithms need to analyse large amounts of data quickly. Knowing how to store data storage effectively and securely is critical to the success of AI endeavours. Without proper visibility into their data or its storage locations, businesses struggle to manage storage efficiently, let alone comply with regulations or fully leverage the power of AI."

Matthew Oostveen, CTO and VP, APJ, Pure Storage, said that AI has moved from curiosity to business priority. "Across Asia Pacific, the conversation is shifting. Business leaders are no longer asking, 'Can we do AI?' but rather, 'Is it delivering?' The novelty is fading, and the expectations are getting sharper. What’s the return? What value are we unlocking? What problems are we actually solving?" he asked.

"But there’s a blind spot in many of these conversations. While companies rush to adopt AI tools and add compute power, few are spending enough time fixing what truly matters - the data feeding those systems."

"Here’s the reality: messy data means messy AI. If your organisation has five versions of the same dataset floating around, sitting in different departments, and no one’s quite sure which is the most accurate or up to date, you don’t get intelligence - you get noise. And in sectors like finance, healthcare, or government, that noise can lead to dangerous decisions. Throwing more compute at the problem won’t help - it’ll just get you to the wrong answer faster," he explained.

"To get AI right, we need to do the hard, unglamorous work: cleaning up data, standardising it, making sure everyone’s working off the same version of the truth. That means breaking down silos, setting clear rules on how data is handled, and investing in the right systems to track and manage it.

"This isn’t a one-off task - it’s a mindset shift. Think of it like a flywheel: clean data leads to better models, better models help make smarter decisions, and those decisions generate even more useful data. But the flywheel only spins if the input is solid."

Oostveen added: "We also need to take data accountability seriously. That means knowing where your data came from, how it’s been changed, and who has access to it. Without that transparency, we can’t build systems we trust and neither can regulators, customers, or the public.

"On AI Appreciation Day, let’s shift the focus to the foundation. Because real progress doesn’t come from adopting the latest tool, but from building the right infrastructure, mindset, and culture to support it."

After the proof-of-concept

Jay Tuseth, VP & GM for Asia Pacific and Japan (APJ) at Nutanix emphasised that unlocking AI's real value in the enterprise means "shifting focus from flashy demos to the engine that powers real-world results: inference". 

"Inference is where AI proves its worth – turning data into decisions in real time. Every intelligent recommendation, automated analysis, and predictive insight represents inference working across increasingly complex infrastructure landscapes. This isn't confined to cloud environments – it's distributed across data centres, edge computing nodes, and private clouds, where performance, security, and cost considerations drive real business outcomes," he said.

"At Nutanix, we believe managing AI inference should be treated like any other core IT function. It needs the same level of visibility, control, and governance as any other enterprise workload. That means understanding where inference is happening, who’s using it, which models are in play, what data is being exposed, and how all of this is being secured, and scaled. 

"This visibility is critical, especially in a region like APJ where AI regulation is evolving fast and accountability is becoming non-negotiable. "On AI Appreciation Day, we celebrate not just the breakthroughs that AI has made possible, but also the opportunity for enterprises to take confident control of how it's deployed and scaled. Because the real power of AI is not just in what it can create, but in how well we can manage and trust it."

According to Joseph Yang, GM, HPC, AI & NonStop, at HPE APAC and India, the true power of AI is only unlocked with robust infrastructure and high-quality data. "As AI workloads grow more complex – from generative AI to real-time analytics – AI factories powered by supercomputing and high-performance computing (HPC) have emerged as the critical foundation for enterprise AI. They are now essential for processing data at scale and embedding intelligence across operations," he said.

"We’ve entered a new era – not just of exascale, but of integrated, intelligent infrastructure underpinned by HPC. Every breakthrough in AI stands on decades of innovation in parallel computing, interconnects, system design, and collaborative software development.

"AI factories represent a new era where intelligence is manufactured at scale. By automating data pipelines, model training, and inference, they enable businesses to complement human expertise and supercharge productivity and innovation."

Rob Newell, Group VP Solutions Consulting, Asia Pacific & Japan, New Relic, said that organisations will have to fundamentally rethink their technology architectures to integrate AI tools and realise their potential. 

"Regardless of the size, all companies are facing the same harsh reality: AI tools are expensive to use, and the costs of building new AI-backed technologies are unpredictable. Organisations that win in our inevitable AI-enabled future won’t necessarily be the ones with the best ideas; instead, the winners will be those that have figured out how to effectively balance cost, value, and performance," Newell said.

"Despite the rapid evolution of generative AI technology, the fundamental questions underpinning the cost of AI are simple: How often do companies query a large language model (LLM) and how much do those queries cost? By controlling these queries effectively and getting the most out of every call by adopting AI-supportive techniques such as retrieval augmented generation (RAG) and agent frameworks, companies can more reliably predict and lower their AI expenses," he said.

"Historically, observability has offered organisations the ability to detect and respond to anomalies in their systems and optimise performance. But with AI driving a revolution in processes and architectures, observability needs to evolve to keep pace and continue providing users with a window into their own systems and processes. New Relic research found that 38% of IT leaders in Southeast Asia regarded AI as a key driver for observability adoption.

"Organisations need intelligent observability to rise and meet the challenge brought by AI. This next phase of observability will be preventive, self-healing, and autonomous, so that it can surface the right insights to the right person at the right time. AI monitoring tools give companies end-to-end visibility into their AI-integrated workflows, but more importantly real-time insight to troubleshoot, compare, and optimise approaches to using LLMs to improve their features or offer brand new experiences. This allows companies to adjust when necessary to manage costs, improve performance, and reduce common issues that can cause costly hiccups."

Frank Bignone, FPT Software VP and Director of Digital Transformation Division, FPT, said that the APAC momentum for AI innovation and adoption can only be sustained if organisations get the next phase of scaling AI right. "Scaling AI effectively involves implementing AI broadly across the organisation and requires a structured process to expand use cases. Organisations embarking on the journey to scale AI will need to establish best practices and the right tools," he said.

"Developing a single generative AI model or agentic AI system is no simple task—it requires orchestrating multiple specialised components and frameworks, often integrated by AI practitioners leveraging a broad ecosystem of open-source and proprietary technologies. This is where MLOps has evolved into what we now recognise as AIOps: a comprehensive set of practices and platforms designed to build, maintain, monitor, and govern AI systems effectively.

"AIOps establishes industry best practices and robust tooling for the end-to-end lifecycle of AI models—from development and deployment to continuous adaptation—while ensuring speed, reliability, and compliance. More importantly, it enables organisations to scale AI solutions intelligently and ensures these systems remain flexible and responsive to changing market dynamics, evolving customer expectations, and shifting regulatory landscapes."

Bignone further suggested that organisations should embed sound software engineering principles such as modular design and reusable code components. "According to McKinsey, these reusable code packages significantly accelerate development cycles and reduce operational costs by eliminating redundancy and freeing AI teams to concentrate on higher-value, strategic innovation," he said.

"Adopting a modular approach makes generative AI and agentic AI projects leaner, more resource-efficient, and easier to update or expand. This adaptability is critical as businesses seek to repurpose AI capabilities rapidly in response to emerging opportunities or compliance requirements. The combination of advanced AI operations frameworks and disciplined engineering practices is essential for delivering scalable, agile, and sustainable generative and agentic AI solutions that drive long-term business value."

Dinesh Varadharajan, Chief Product Officer at Kissflow, said the conversation around AI "must move beyond what it can do—to who gets to build with it". 

"Traditionally, creating digital solutions like apps, workflows, and automations has been confined to developers. This has created silos between IT and business teams, leaving many organisations stuck in what IDC calls 'AI pilot purgatory'. In fact, by 2026, more than one-third of APAC enterprises are expected to remain in this phase, unable to scale AI use or realise ROI. 

"The real breakthrough will come when organisations embrace enterprise-wide AI adoption—empowering both IT and business users with the tools to build, test, and launch solutions," Varadharajan said.

"At Kissflow, we see AI and low-code/no-code platforms as the foundation of this shift. Low-code/no- code breaks down traditional programming barriers. AI enhances this by turning natural language into workflows, offering intelligent suggestions, and accelerating development."

"In the coming years, over half of APAC enterprises are expected to rely on gen AI-enabled platforms for rapid IT training and automation. The future isn’t about who can code—it’s about who is empowered to innovate. AI is no longer just a backend enabler—it’s the copilot of modern enterprise innovation," Varadharajan added. 

The final analysis

Micah Heaton, Executive Director, Microsoft Product and Innovation Strategy, BlueVoyant said: "AI Appreciation Day isn’t about machines. It’s about us. It’s about the choices we make at machine speed that still echo at human scale. AI tools and other agentic allies are not here to save us. They are here to reflect us. To amplify our courage, expose our blind spots, and force us to ask who we protect first and why. While these tools are reshaping daily life, what and how we build them demands responsibility at the gate, not as an afterthought. Responsibility isn’t a checkbox. It’s the only thing standing between progress and catastrophe," he said.

"Today is a reminder that AI is both saviour and servant. It accelerates our decisions, but it doesn’t tell us who we want to be. That choice is still ours. And it always will be. If we want AI to work in the right direction, we have to bring every voice to the table. We have to build with intention, wield it with moral clarity, and protect people with the same ferocity we protect their data. That’s the real work. That’s the real appreciation. Resilience isn't given, it's built."

"While AI Appreciation Day may be peculiar to some, we'd advocate AI is here to amplify us—not replace us. With the right information, at the right moment, AI can help us work smarter, faster and more impactfully,” said Magnuson.

"AI has reached a point where it’s no longer just a technology discussion—it"’s a business one. The real opportunity isn’t in simply deploying AI, but in knowing when and where it creates tangible value," said Law.

"As we acknowledge AI Appreciation Day, let us appreciate the invisible engines of accountability; the systems that support high-stakes decisions across borders, and the teams who design AI not just to move fast, but to stand up under scrutiny," said Spinelli.

MLOps stands for machine language operations.

Hashtag: #AIAppreciationDay

APAC stands for the Asia-Pacific region. 

Hashtag: #AIAppreciationDay