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AI Appreciation Day 2026: Technology Leaders React
Ai Appreciation Day 2025 Reactions

AI Appreciation Day 2026: Technology Leaders React

July 19, 2026 Reactions

Surprisingly Useful AI Article Enhancements

It’s AI Appreciation Day, the annual observance carries fresh urgency for enterprise technology leaders. First established in 2021, the day recognises the contributions of artificial intelligence to everyday life while encouraging serious conversation about how the technology should be developed, governed, and used responsibly. For B2B organisations, 2026 marks a turning point: companies have moved from experimentation to production rollout, and questions of data trust, sovereign AI governance, and secure API infrastructure now sit at the centre of enterprise strategy. The celebration is no longer about potential – it’s about accountability at scale.

Here are technology leaders’ reactions to AI Appreciation Day (newest at top):

Table of Contents

Garry Valenzisi, VP & GM at Iron Mountain ANZ 

AI is transforming the way organisations work, helping unlock new levels of productivity, insight and innovation. But while everyone wants the promise of AI, far fewer are confronting the data reality required to deliver it.

Australia is widely regarded as being among the world’s leaders in AI adoption, yet it is often considered to lag in AI sophistication and maturity. This highlights a critical challenge across Australian industries: organisations are racing to adopt AI while attempting to scale it on fragmented information, disconnected systems and inconsistent governance. 

When the information feeding AI cannot be trusted, neither can its outputs. Meanwhile, critical information that could fuel growth remains trapped in legacy systems. As organisations move from AI experimentation to enterprise deployment, these information challenges are becoming barriers to delivering meaningful business value 

On AI Appreciation Day, it’s worth recognising that AI’s greatest potential doesn’t come from increasingly powerful models alone. It depends on information that is accurate, well-governed and available to the people and systems that need it. When organisations can confidently connect, govern, protect and activate information across physical and digital environments, AI has a far stronger foundation for delivering meaningful business outcomes.

“The organisations that succeed in the AI era will be those that invest in these foundations today, building the operational confidence needed to scale AI and translate ambition into measurable business outcomes.

Kumar Mitra, Commercial Leader, Greater Asia Pacific, Lenovo

AI Appreciation Day usually means celebrating what technology can do. This year, the more useful question for Asia Pacific businesses is different: what is AI actually doing inside their operations, and what still needs fixing before it delivers at scale.

Adoption has moved past the pilot stage. Lenovo’s fourth annual CIO Playbook, with IDC, shows 96 percent of organizations across Asia Pacific plan to increase AI investment this year, by an average of 15 percent. Sixty-six percent have moved beyond initial exploration into business-wide adoption. Close to half of AI proof-of-concepts have reached production. Two years ago, most conversations with CIOs were about whether AI worked. Today they’re about how to run it reliably, at scale.

Governance hasn’t kept pace with adoption. This is the part of the story that gets skipped in most AI Appreciation Day content, and it shouldn’t be. While 60 percent of organisations in the region are in late-stage AI adoption, only around a quarter have a comprehensive AI governance framework in place. Data quality gaps, integration complexity, and a shortage of in-house expertise are the main reasons proof-of-concepts stall before reaching production. Agentic AI has overtaken generative AI as the top CIO priority for 2026, but only about one in five organisations report significant use of it today. The gap between ambition and readiness is real, and businesses should plan for it rather than assume it will close on its own.

Agentic AI has a cost problem nobody is talking about. Here’s a number CIOs should know: 92 percent of organisations deploying agentic AI report costs exceeding what they budgeted. This isn’t a minor overrun. It’s driving finance teams to pause and reassess agentic programs before scaling them further. The cause is structural. An AI agent doesn’t answer one question and stop, it chains together many model calls – reasoning, retrieving information, checking a result, calling a tool, checking again. Most of that work runs on cloud infrastructure priced per token, built for occasional use, not for a process running continuously at volume. The result is that enterprises pay frontier-model prices for a lot of routine, repetitive reasoning that doesn’t need a frontier model.

Matching the workload to the right environment fixes this. While bursty, unpredictable work still belongs in the cloud, sustained, predictable, high-volume reasoning such as customer service routing, HR queries, retrieval-augmented search are better suited to on-premises or edge inferencing.

Physical AI is moving out of demos and into daily operations. Across the region, AI is starting to act, not just answer. A six-legged robot inspects energy infrastructure in hazardous environments. Robot dogs monitor water utility pumps. Autonomous vehicles run on enterprise AI platforms in commercial deployment, not pilot mode. This is the next phase of enterprise AI, where intelligent systems are augmenting people by taking on repetitive, hazardous and time-sensitive tasks in the physical world.

The FIFA World Cup 2026 offers a powerful example of AI solving real operational problems. As FIFA’s Official Technology Partner, Lenovo is helping improve decision-making, resilience and speed through technologies such as FIFA AI Pro™, the Intelligent Command Center, AI Stabilisation technology enabling Referee View™ broadcasts, and AI-powered 3D player avatars that precisely replicate each player, giving referees more detail to make the right decisions on the field while providing fans with greater visual context to better understand those decisions. Together, these technologies demonstrate how AI delivers measurable outcomes in one of the world’s most demanding operating environments.

This is a go-to-market problem as much as a technical one. The cost-economics issue today looks less like an infrastructure question and more like an advisory gap. Most organisations in this region, particularly outside the largest enterprises, don’t have a team that can independently work out which agentic workloads belong on which infrastructure, at what cost, and how to govern AI responsibly. That has to be translated for them by a partner who can bring the full stack – devices, infrastructure, edge, cloud, software and services – and by a channel network equipped to deploy it, not just sell it. That’s the thinking behind how we’ve built out the Lenovo 360 partner framework: so partners across the region, from large system integrators to specialised local players, can put this economics conversation in front of customers before the first invoice, not after.

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The takeaway for this AI Appreciation Day: adoption is real, the opportunity is real, and so is the gap between what businesses expect AI to cost and what it actually costs when workloads and infrastructure aren’t matched properly. The organisations that come out ahead this year won’t be the fastest adopters. They’ll be the ones that got the architecture, the governance, and the commercial model right from the start.

MJ Robotham, Director, APAC, NinjaOne

AI Appreciation Day is a timely reminder that the conversation around Artificial Intelligence has changed. It has shifted from whether or not organisations should adopt AI, to where it can deliver the greatest operational value.

Most IT teams in the country are already realising the value of AI by reducing the manual work that slows them down. They are managing a greater number of endpoints, applications and security risks than ever before, often without additional resources. AI can help reduce that operational burden by automating repetitive tasks, improving visibility across increasingly complex environments and giving IT teams more time to focus on strategic initiatives that move the business forward.

As AI adoption accelerates, businesses need to be more judicious in its deployment. The greatest return comes from applying AI to solve specific operational challenges while maintaining the visibility and control needed to keep environments secure.

The organisations getting the most from AI aren’t necessarily using the greatest number of AI tools. Rather, they are using AI deliberately to simplify operations, strengthen resilience and enable their IT teams to focus on higher-value work.

Dino Tius, CIO, BizCover

Quoting insurance through ChatGPT is just the start. At BizCover, AI strengthens our compliance and risk management, elevates customer service, powers what we build in tech, and makes our teams more efficient. It’s proven one thing to us: if you can imagine it, AI can help get you there.

Sonia Eland, EVP & Country Manager, ANZ, HCLTech

As we mark AI Appreciation Day, it’s clear the conversation around artificial intelligence has changed significantly. Most Australian organisations are no longer asking whether AI matters; they’re focused on how to use it effectively and responsibly. Whilst enthusiasm remains high, many businesses are still working through practical challenges around data, governance, workforce skills and getting real value from their AI investments.

The reality is that Australia’s biggest AI challenge is no longer access to technology; it’s execution. The organisations seeing the strongest results are moving beyond experimentation and focusing on practical applications that improve productivity, enhance customer experiences and help employees spend more time on higher-value work. At HCLTech, we’re seeing increasing demand from organisations looking to scale AI in ways that deliver measurable business outcomes, not just proof-of-concept projects.

This AI Appreciation Day, businesses should look beyond the hype and appreciate AI for what it really represents: an opportunity to rethink how work gets done. The greatest competitive advantage will come from integrating AI thoughtfully, with the right foundations and clear business goals. Australia has a significant opportunity ahead, but success will ultimately depend on turning AI ambition into trusted, measurable results at scale.

Carla Ramchand, Managing Director for ANZ, Cognizant

AI agents are now a part of our teams. They can manage work, make recommendations, and hand decisions back to people when human judgement is needed. But AI’s potential to transform a business will only go so far if it’s treated like an add-on to existing systems. While it may save time on one task, it’s unlikely to make much improvement on speed and quality of end-to-end business outcomes.

AI also doesn’t behave like traditional software. It can’t simply be taken off the shelf and expected to understand how an organisation works. This is why the gap between AI investment and tangible business outcomes is widening. Many organisations aren’t taking the right steps to build AI properly from the ground up.  

The real opportunity with AI lies in looking at the process from the start to finish and rethinking how work should flow. AI needs to be built around an organisation’s unique processes, data, industry knowledge, and practical experience of its people. When leaders set clear boundaries, keep people accountable for important decisions, and give employees the confidence to challenge an output when it doesn’t look right, they build a culture of trust and innovation. 

To solve business issues and see real improvements with AI, organisations must combine the technology with deep business and industry context. In doing so, AI can help people focus on higher-value work while supporting the delivery of the measurable results businesses are looking for.

Aaron Bugal, Field CISO for APJ, Sophos

While AI Appreciation Day is ‘celebration’ of the benefits of AI, it also serves as a timely reminder about the responsibility that comes with using it securely and safely.

There is no question that AI is changing cybersecurity. It helps defenders analyse threats faster and respond more efficiently, but also gives cybercriminals new ways to scale familiar attacks. The technology is evolving rapidly, yet the fundamentals of good cybersecurity remain remarkably consistent.

Even in an era of highly sophisticated technologies available to attackers, 79% of ransomware attacks in the APJ region still begin with identity-based techniques such as phishing, malicious emails and compromised credentials – according to the finding of the Sophos Ransomware Report released today.  This shows that AI isn’t replacing the tactics attackers rely on but it is making them faster, more convincing and easier to execute at scale. 

Therefore, there is an imminent need to solidify the foundations of a robust defence system against these attacks which not just focuses on speed and scale but is also sustainable in the long run. That comes with embedding governance, visibility and security into AI initiatives from the outset, rather than treating them as an afterthought.  

AI is an incredibly powerful tool, but like any tool, its value depends on how it’s used. The organisations that will benefit most are those using AI to strengthen human expertise, accelerate response and build resilience, rather than assuming technology alone will solve their cybersecurity challenges.

Mike Goldsworth, Director, Solution Advisory, BlackLine

Artificial intelligence (AI) is opening up new possibilities for finance but, as adoption grows, trust must grow with it.

AI is advancing faster than the controls around it and, in finance, that gap carries real risk. As the Australian Securities and Investments Commission (ASIC) sharpens its focus on AI governance, the conversation is moving from adoption to accountability. Rising transaction volumes, tighter compliance obligations and more complex reporting requirements across ANZ mean the next phase of finance transformation will be led by organisations that can make AI traceable, explainable and auditable – moving from opaque ‘black box’ systems to a ‘glass box’ approach.

On AI Appreciation Day, it’s worth recognising that the value of AI in finance will not be measured by speed alone, but also the transparency and trust behind every outcome. Agentic Financial Operations represents this next step: glass box AI embedded within governed financial workflows, supported by human oversight and the controls needed to help finance teams scale with confidence and meet regulatory expectations.

Mark Coyle, CEO ANZ, HeadFirst Global

AI Appreciation Day comes at an exciting point for Australian workplaces, as organisations move beyond experimentation and begin using AI to improve productivity and rethink how work gets done.

The immediate impact of AI is not a simple equation of headcounts and job cuts. The more significant shift is in how work itself is structured, moving away from rigid, fixed roles and towards outcomes delivered by a mix of permanent staff, contractors, specialist partners, and AI. Routine, repetitive tasks are increasingly handled by technology, freeing people up to focus on the judgement calls, context and problem-solving that AI still can’t do.

Australia’s mining, healthcare, infrastructure and government sectors already manage some of the country’s most complex contingent workforces, so this shift tends to emerge here first. Skills shortages and reforms like Fair Work’s Closing Loopholes legislation mean organisations must rethink workforce strategies while operating under increasing scrutiny.

Success here won’t come from adopting more technology or running isolated pilots. It will come from making these changes deliberately, so performance, accountability, and human contribution remain strong as the workforce becomes more blended. That is where AI’s real value lies: not in replacing work, but in helping organisations build better, more resilient ways of delivering it.

George Harb, Vice President Australia and New Zealand, OpenText

As enterprises embrace AI at scale and it becomes more embedded in business processes, resilience will depend on three capabilities. Understanding what AI can retrieve, controlling how it interacts with systems and governing the data it consumes.

Many organisations focus on AI performance, productivity gains and automation opportunities. Equally important is understanding the new breach pathways that emerge when AI is connected to data, user credentials and business workflows at scale.

AI agents are becoming active participants that can search, retrieve, analyse and act across enterprise systems. The challenge is that these agents often inherit user privileges from employees, service accounts or connected applications. Without strong governance, they can aggregate sensitive information across multiple systems and expose data in ways never anticipated.

To prevent AI agents from retrieving data they shouldn’t, organisations should assess whether these agents operate within the same security and oversight framework as human employees.

Traditional identity and access management were designed for people. AI introduces a new class of digital actors that continuously request information, perform tasks and interact with systems.

As more agents are deployed, organisations face increasing volumes of automated requests, delegated privileges and machine-to-machine interactions. Security frameworks built around periodic reviews and manual approvals can quickly become overwhelmed.

This results in permission sprawl, dormant credentials and security pathways that are difficult to monitor or audit. In many cases, existing security and risk processes struggle to keep pace with the scale and speed of automated access.

Another consideration is that many enterprises are connecting AI solutions to data spread across cloud platforms, SaaS applications, file shares, collaboration tools and legacy systems.

When data management practices are inconsistent, models can be trained on and retrieve information from data stores that lack proper classification, ownership and security controls. As a result, AI may surface information that should never have been available.

This highlights the importance of ensuring strong oversight over the quality, security and provenance of the data feeding AI systems.

The next generation of AI risk lies at the intersection of AI, digital identity and data governance. As AI becomes more embedded in core business processes, organisations must ensure the foundations supporting it are equally intelligent, secure and accountable.

As organisations mark AI Appreciation Day, the focus should extend beyond AI’s capabilities to the systems, identities and data that will determine whether it can be deployed securely, responsibly and at scale.

Ben Mudie, Field CTO, Asia Pacific and Japan, Tenable

AI Appreciation Day shouldn’t just be a celebration of productivity. For Australian businesses, it needs to be a reality check for how they’re managing risk.

The defining feature of this moment is the sheer velocity of AI adoption. Two in three Australian workers are already using AI tools at work, and timelines that used to take days are collapsing into seconds. That pace is unlocking real innovation. But convenience always wins until the consequences catch up and, in Australia, they’re starting to.

Melbourne Business School’s 2025 global trust-in-AI research found 60 per cent of Australian workers have concealed their AI use from their employer, and 48 per cent admit to breaching company policy by entering sensitive data into public AI tools. Separate research published this month by Employment Hero found one in three Australian workers are using AI at work without their employer knowing at all. That’s not a handful of edge cases. That’s a shadow AI footprint most boards can’t see, let alone govern and it’s the same ‘reasonable steps’ question the OAIC is now actively testing under the Privacy Act.

We saw this exact failure mode with rushed cloud migrations a decade ago: convenience outran governance, and organisations spent years unwinding the exposure. This time it’s happening faster, and at a far greater scale.

This isn’t an argument against AI. Its benefits are real. But Australian businesses are building an exponential future on a fragile foundation, and AI Appreciation Day is a reasonable moment to ask whether anyone in the organisation actually owns that risk.

Steve Yurisich, Regional Managing Director APAC, Thoughtworks

It should be about the people learning how to work with it responsibly, creatively and effectively.

Over the past year, AI has moved well beyond experimentation. It’s helping developers write code, supporting customer service teams, assisting knowledge workers and accelerating decision-making across almost every industry.

But the organisations seeing the greatest value aren’t necessarily those deploying the most AI. They’re the ones investing in the engineering practices, skills and governance needed to use it with confidence.

As AI becomes embedded across every business function, success will depend less on the sophistication of individual models and more on how effectively organisations integrate AI into everyday work, maintain human judgement and deliver outcomes that are transparent and trustworthy.

The next chapter of AI won’t be defined by who can generate the most content or automate the most tasks. It will be defined by who can combine human expertise with AI to solve meaningful problems, improve customer experiences and create lasting business value.

That’s what I appreciate on AI Appreciation Day.

Not AI replacing people, but AI helping people achieve outcomes that simply weren’t possible before.

Damien Brennan, Strategic AI & Emerging Tech Partnership Manager, Sinch

AI has become a powerful customer communications tool, that is enabling brands to build stronger connections with their customers, rather than simply managing a higher volume of requests. This marks a significant evolution beyond its early promise of being an ‘automation at scale’ tool.

Developments in conversational AI mean customers can now reach a brand at many more times in the day, with responses that understand context and intent rather than matching keywords to scripts. That same understanding extends naturally into voice AI, which now supports real-time conversation, allowing customers to speak with a brand without navigating rigid menu structures.

Collectively, these capabilities allow brands to remain consistently present for customers, without compromising the importance of personalisation in interactions. The results are measurable, including faster resolution times and stronger engagement, and these outcomes are precisely why AI has become embedded in how organisations communicate.

AI Appreciation Day offers a timely opportunity to recognise that progress. Conversational and voice AI are already strengthening customer connection at scale, underscoring how far the technology has advanced beyond simple automation.

AI Appreciation Day 2026 arrives at a genuinely interesting moment for the home security industry. A year ago, the conversation centred on what AI could do: object detection, false alarm reduction, and smart alerts. The more important question in 2026 is whether those capabilities are still working for them. Consumer expectations have matured after years of cloud outages and subscription fatigue. People want systems that understand context, surface what genuinely matters, and provides meaningful alerts for important moments.

The industry’s broader shift toward on-device processing reflects where those expectations are heading. Processing footage locally means faster responses and stronger protection against the vulnerabilities that come with storing data in the cloud. Reolink’s own Local AI Video Search reflects this thinking, running entirely on the device so there’s no footage sent elsewhere and no data sitting on external servers exposed to breach or interception. Keeping these AI features subscription-free is also a deliberate commitment. As AI becomes more widely available, we know our consumers will want capable AI without an ongoing payment plan.

The category is moving toward something people can genuinely rely on: capable, private by design, and accessible regardless of the hardware they already own.

Mike Powrie Founder and CEO, NeonNow

Prime Minister Anthony Albanese’s address on AI in Australia’s interests today put a sharper point on a debate contact centres have been living in for years: where AI should sit, and where it shouldn’t. Contact centres are where AI meets real customers every day, at scale, in real time, so that debate has always mattered here first.

The lesson from 2026 so far is clear. AI works best when it takes on volume: routine queries, repetitive tasks, and the interactions a machine can handle well. People still own the moments that need judgement, empathy, or a decision only a human can make. We built NeonNow on that split deliberately, because customers can tell the difference and they reward the companies who get it right.

True appreciation of AI means being honest about its limits, as well as its capability. Enterprises earning customer trust are the ones drawing that line clearly. With Australia’s national conversation on AI standards now catching up to what contact centres already knew, that discipline deserves marking on a day named for AI.

Hayley Fisher, Country Manager ANZ, Adyen

AI is quickly becoming a core part of modern commerce, particularly in payments where decisions are made in milliseconds.

In Australia, AI-powered shopping has grown by 45% over the past year, and more than half of consumers say they would be comfortable making purchases through AI. That shows just how fast we are moving towards more automated, AI-driven transactions.

Behind every transaction, AI is playing a bigger role in how payments are approved, how fraud is detected and how risk is managed. As digital commerce becomes more complex, these capabilities are no longer a nice-to-have. They are essential to keeping payments fast, seamless and secure.

Businesses are also recognising that AI is about more than efficiency. It’s helping them respond more quickly to changing customer expectations, enabling more personalised experiences, smarter payment and fraud decisions, and better service without adding complexity to the customer journey.

What hasn’t changed is the importance of trust. As more transactions happen with less direct customer input, security, transparency and responsible data use become even more critical. Approaches built around identity and minimising data exposure are becoming key to making sure these AI-driven systems are both effective and trustworthy.  

AI Appreciation Day is a reminder that the real value of AI isn’t just what it can do, but how it’s used to deliver better, more reliable experiences at scale.

Alex Newman, Country Manager, ANZ, Informatica from Salesforce

AI Appreciation Day is an opportunity for us to look beyond the technology itself – and recognise what it truly takes to make AI successful at scale.

We’re seeing strong ambition from organisations to move from their AI pilot to production. But as AI becomes embedded in business operations, a hard truth is emerging: humans can compensate for poor-quality data, AI cannot. For years, organisations have been able to work around data issues with people, processes, and manual intervention. In today’s agentic world, that’s no longer possible.

That’s why trusted and connected data is rapidly becoming one of the biggest determinants of AI success. Informatica’s CDO Insights latest research found that data reliability remains a significant barrier which limits 92% Australian data leaders’ ability to move more AI initiatives from pilot to production. And nearly half cite data quality and reliability as a key challenge in deploying AI agents into production environments. These findings underscore the critical importance of trusted, governed, and connected data as a foundation for AI success.

The opportunity with AI is significant, but organisations don’t need more AI for AI’s sake. They need confidence in the data that powers it. Building AI on poor quality data is like constructing a new building on unstable foundations. Organisations that invest in trusted, governed and connected data today will be the ones best positioned to move from experimentation to lasting business value.

Ling Lu, Head of New Product Development, Jabra

AI has already transformed the way we work and the next shift will be how we interact with it.

Over the coming years, talking to AI at work will become as natural as typing into it today. Jabra research suggests voice interaction with AI will reach mainstream adoption by 2028. Whether summarising meetings, reviewing documents, getting quick feedback, and brainstorming ideas, speaking to AI will become an increasingly common part of the working day. As AI evolves from a productivity tool into a more active collaborator, the keyboard won’t disappear, but conversation will become the most intuitive way people interact with generative AI, especially as it takes on more complex tasks at work. A voice-first approach will make work more natural, ambient, and autonomous in the age of generative AI productivity.

But this shift also creates a new challenge. If AI relies on our voice, it also inherits the same audio problems that have frustrated hybrid work for years. In fact, 99% of knowledge workers say poor audio negatively impacts online meetings. AI is only as effective as what it hears.

That’s why the next wave of AI innovation won’t be defined by smarter models alone. It will also be driven by smarter audio. Technologies that isolate voices, reduce background noise and deliver clear, reliable voice capture will become foundational to how people work with AI. The businesses that recognise this early won’t just improve communication between people, they’ll unlock more value from AI by ensuring every conversation starts with clear, accurate audio.

Jessica Zhang, Senior Vice President, ADP APAC

While businesses across Australia and New Zealand are moving AI from experimentation to everyday operations, AI Appreciation Day is a reminder that success will not be defined by the latest tools organisations adopt, but by how effectively they help people use them.

ADP Research shows that 44% of Australian workers are already using AI at least multiple times a week, yet only 13% expect it to positively impact their job responsibilities in the year ahead. The disconnect highlights a challenge in trust and communication. Employees may be using AI, but many still don’t understand how it will make their jobs better rather than simply different.

The priority for local organisations now is to be more deliberate about how AI is applied. At ADP, we refer to this as “The Great Job Unbundling”, identifying which tasks are best suited to AI, and which still require human judgement, creativity, context and collaboration. The organisations that get AI right won’t necessarily be the ones adopting it fastest. They’ll be the ones that invest just as heavily in people as they do in technology.

Itzik Swissa, Country Manager A/NZ & Sr. Director at JFrog

AI Appreciation Day is a good moment to take stock of how far we’ve come – and what it takes to keep moving forward responsibly.

In Australia, that progress is real. The JFrog 2026 Software Supply Chain Security State of the Union found 68% of Australian organisations now self-host their AI models, 47% automate blocking of unapproved developer tools at the workstation layer, and 67% have full production provenance visibility – all leading figures globally. 

However, the next step is closing the governance gaps: 62% of Australian organisations aren’t actively scanning for exposed credentials, API keys, or tokens. Secrets detection is the most under-deployed security control relative to threat level in markets like Australia and that’s a risk. 

This is one of the key reasons JFrog joined both Chainguard’s Project Athena and IBM/Red Hat’s Lightwell coalitions. Both exist to ensure vulnerabilities in open source are found, fixed, remediated and put into production at enterprise scale for the broader community.

Appreciating what AI enables means investing in the conditions that make it trustworthy. That is what JFrog stands for and we’re proud to say that work is already well underway in Australia.

Jay Tuseth, Vice President & General Manager APJ, Nutanix

A year ago, agentic AI in Asia-Pacific and Japan (APJ) was mostly confined to pilots. Today, 75% of APJ organisations have already deployed it in at least some initiatives — real proof of how fast this technology has scaled. Yet moving fast is not the same as moving safely, and a lot of enterprises are trying to run that bullet train on tracks built for steam engines.

Three things are putting AI infrastructure to the test. Shadow AI is one: 79% of global organisations already have AI applications or agents running outside IT’s knowledge. Sovereignty is another, with 80% now calling data sovereignty a high infrastructure priority. And then there’s legacy gravity, as most enterprises run agentic AI on top of decades-old systems never built for autonomous agents working at this speed.

None of this is a reason to slow down — it’s a reason to get the basics right. Organisations need a platform that runs AI applications consistently across Kubernetes and virtual machines, wherever they sit. They need one place to see which agent is accessing what, and at what cost. They also need the freedom to keep sensitive data and models within their own borders, on infrastructure they control, without overdependence on any single provider.

This AI Appreciation Day, the point worth making to APJ leaders is simple: it’s not about who has the fastest train, it’s about who laid the tracks to carry it. Ask yourself: if you had to move your AI models out of the public cloud by next week, could you? Technology is only part of the solution; you must also solve for the people and process barriers that cause AI initiatives to stall. Get the foundation right, and agentic AI will take enterprises exactly where they need to go.

Adam Frank, Vice President and General Manager APAC, SugarAI

As organisations race to implement AI, AI Appreciation Day is a chance to sit back, take stock of those decisions, and ask a critical question; why are we implementing AI?

No serious business is implementing AI to automate customer service via a chatbot and calling it a day. Sure, this is something AI can do, but the reason AI is even considered in the first place is usually to drive the business forward. Automating customer service doesn’t move the needle. 

What does make an impact is when AI is used to improve commercial outcomes or deliver outsized productivity gains.

Consider two very different industries: manufacturing and aged care.

Modern manufacturing is already optimised to the nth degree after years of automation, robotics, and productivity boosting projects. Factory floors already hum with machines generating data, while ERP and CRM systems hold a gold mine of business, customer, and sales data.

Where AI can truly change the game in this sector is by analysing these fragmented data sets and delivering clear, actionable intelligence that helps teams sell with greater precision. With the right insight at the right moment, manufacturers unlock a huge commercial advantage by predicting what their customers will need even before they know themselves.

In aged care, the proposition is slightly different but the impact no less profound. When a family engages an aged care provider, they are doing so during an extremely stressful and emotional time. Australia’s aging population isn’t getting any younger and the current demands on the sector mean hundreds of thousands are stranded on waiting lists.

The pathway from first contact through to admission and care needs to be simpler, shorter, and easier to navigate. AI can help connect data that already exists so the right person reaches the right place without the holdups currently slowing things down. That means clearer communication at every stage of the process, better coordination between providers, and faster delivery of care.

While AI-generated responses to customer queries might save a few hours in a day (assuming the customer gets the response they’re looking for), this is far from the real possibilities AI can deliver. 

Kristen Pimpini (KP), VP and General Manager APJ at Workiva

AI has crossed the line from buzzword to business-critical, reshaping how teams handle financial reporting, sustainability, audit, and risk. Despite the many forward-looking claims coming from across the tech sector, the change is already underway. Workiva’s 2026 Executive Benchmark Survey found 64 per cent of Australian organisations were applying AI to parts of their quarterly and annual disclosures this year, while 55 per cent now rely on AI heavily throughout the reporting cycle.

The exhausting reporting seasons of long hours, repetitive tasks, and mounting pressure are giving way to something far more manageable, and the people living this shift are feeling the difference. Teams are developing trust in the tools with 75 per cent of organisations putting their AI models through internal audit scrutiny. Even if it is just small pockets of time handed back to reporting professionals it is genuinely valuable, and allows them to redirect their focus on strategic work moving the business forward.

And behind every one of these breakthroughs sits the quiet work of the researchers, engineers, and innovators who built this technology. AI Appreciation Day is a fitting moment to thank them for their efforts that are pointing the world toward a smarter and more productive way to work.

Renée Chaplin, VP – Asia Pacific at Constant Contact

For many small businesses, AI has become the extra set of hands they never had the budget to hire, and it’s exactly why adoption has taken off so quickly across Australia and New Zealand. Constant Contact’s latest Small Business Now report revealed that across the region, AI adoption in SMB marketing has reached 88.7 per cent, the highest rate of any surveyed region. It’s clear AI use has moved well beyond early adopters into everyday practice.

What’s driving it is completely practical. More than half of ANZ SMBs using AI point to saving time as the biggest win, whether it’s drafting emails and subject lines, analysing data, or creating visual content. For a business owner wearing every hat at once, those reclaimed hours are incredibly valuable and can go straight back into customers and growth to drive the business forward. 

That said, the shift comes with some real concerns. Many SMB owners fear AI use could lead their customers to feel a loss of personal touch, or raise privacy, authenticity and trust issues. Addressing these concerns boils down to how tools are used and for what purpose. Used thoughtfully, AI should deepen the human connection, not dilute it.

Vinayak Sreedhar, Country Head A/NZ, ManageEngine

AI Appreciation Day is here again and this year, it’s worth remembering AI isn’t just generating content or analysing data anymore – it’s beginning to make decisions, trigger actions, adapt in real time, and automate complex processes. The move toward agentic AI is changing how organisations manage technology, risk, and trust. But it’s also exposing a gap in how many approach security. Traditional automation was predictable. Agentic systems analyse multiple variables, weigh trade-offs, adjust course, and decide what action to take. That’s worth celebrating, absolutely. But autonomy brings a completely new category of risk.

When machines act on an organisation’s behalf, identity and access governance becomes mission critical. Every autonomous system is effectively a new digital identity inside the organisation. One capable of accessing systems and executing workflows at that. Over-permissioned agents don’t just speed deployment, they dramatically increase the attack surface. The answer is ‘safe autonomy’ where agents operate within human oversight, tightly defined boundaries, clear permissions, and constant monitoring.

So today isn’t just about appreciating what AI can do. It’s about appreciating the discipline required to deploy it responsibly. The question isn’t whether to deploy AI. It’s whether it can be deployed safely. As machines take on more decisions, governance over identity and access will be what protects trust.

Jason Baden, Regional Vice-President A/NZ, F5

2025’s AI Appreciation Day saw businesses debating how and when to experiment with AI. This year, the conversation looks very different. In many cases, the tools are deployed, the pilots are done, and the real test has begun. After a year spent speaking with executives, technologists, and customers across A/NZ, the enthusiasm hasn’t surprised me, it’s how rarely anyone pauses to ask the most basic question before committing budget and resources. Not “can we do this?” but “should we do this, for this problem, right now?” That discipline – knowing what you’re solving before reaching for the tool – is rarer than it sounds, and far more valuable.

I’ve watched organisations spin up proof-of-concept projects, hit a wall, and struggle to understand why. The answer is almost never the technology. It’s that nobody defined the problem clearly enough before the project started. That’s exactly what’s happening in boardrooms and strategy offsites across the region, where the pressure to demonstrate progress has become its own kind of risk. The business wants to move quickly, and use cases are appearing everywhere. I understand that pressure and I feel it myself. But speed without clarity is how organisations end up with expensive infrastructure, unsettled people, and governance functions scrambling to catch up with decisions already made.

If there’s one thing worth appreciating on 2026’s AI Appreciation Day, it’s not the models but the foundation underneath them. Most AI initiatives don’t stumble because of the technology. They stumble because the data feeding it isn’t governed or even understood properly. That’s the harder work nobody wants to celebrate, but it’s the work that will actually determine whether AI delivers.

Zak Menegazzi, APJ Director, Armis from ServiceNow

The conversation around AI has shifted from mere productivity gains to the restructuring of enterprise security. While we reflect on the opportunities of AI and how it has become embedded across organisations, establishing a comprehensive cybersecurity framework to match the speed of the adoption is just as vital.

Over the past few years, GenAI platforms have matured from pattern-matching large language models (LLMs) to tool-calling agents. This transition marks the agentic era, where virtually every cybersecurity solution has implemented conversational AI capable of making recommendations. However, manual remediation cannot keep pace with AI-powered cyberattacks. Threat actors have upped the ante, using agentic attacks to shape offence faster than human defences can respond.

The Risk of the Flat Network

The agentic enterprise is, in many ways, a security nightmare. By connecting AI to every facet of the organisation, we are inadvertently creating a flat network. This runs counter to the principles of network segmentation and isolation that the security industry has advocated for decades. AI agents possess the autonomy to execute tasks but often lack the discernment to avoid harming their enterprise. Organisations must implement guardrails to prevent AI-induced outages and data leaks, ensuring that agents do not become destructive simply because the logic dictated a path of least resistance.

AI vs. AI: The New Defensive Paradigm

We are moving from a Human vs. Human conflict to an AI vs. AI paradigm. The scale of the challenge is immense; a typical enterprise with 10,000 employees may soon contend with over a million agents. To survive, cybersecurity must follow the AI paradigm shift from disconnected tools and ad hoc manual processes to unified, autonomous platforms. This requires:

  • Preemptive Protection: Moving beyond reactive detection to operationalising alert generation into prioritised exposure management.

  • Machine-Speed Remediation: Transitioning from manual, human-in-the-loop processes to autonomous identification and remediation.

  • Continuous Learning: Using AI to detect drift and gaps in near real-time before exploitation occurs.

Defenders still hold the ultimate advantage as they know what matters most to their business. By adopting agentic cybersecurity, organisations can finally even the odds against asymmetrical, machine-speed threats.

Chris Ellis, Director Solution Engineering, Nintex

As organisations shift from initial AI experiments to multi-agent networks at scale, AI Appreciation Day is a chance to consider the foundations that will make this transformation a reality.

Multi-agent systems accelerate execution, but they do not automatically improve the underlying process. If an organisation has inconsistent procedures or conflicting policies, those weaknesses will be amplified by AI agents operating at scale. Before deploying agent networks, organisations must first understand, document, and optimise the underlying processes.

The principle is the same as traditional automation projects: garbage in means garbage out. Agents can only make decisions based on the information, rules, and context they are provided. Poor data quality or undocumented business rules can quickly propagate across an entire agent network, creating errors at a pace impossible in manual environments.

When something goes wrong, you should be able to reconstruct the decision path rather than treat the system as a black box. This matters as much for governance as it does for debugging. More importantly, organisations can use these insights to continuously improve both the process and the agent network itself.

Multi-agent AI is the near-term future of enterprise automation. To prepare for this future, organisations must think about how to deploy it in a way that captures the rewards while avoiding the risks. At the end of the day, trustworthy AI outcomes are built on trustworthy processes.

Mohammed Rafee Tarafdar, Chief Technology Officer at Infosys

On AI Appreciation Day, it’s worth reflecting on how the conversation around AI has evolved. For many organisations, the challenge is no longer proving AI’s potential but realising sustainable value at scale. As adoption accelerates, the focus is shifting from experimentation to execution, and from isolated use cases to enterprise-wide transformation.

Making AI work at scale is less about excitement and more about strong foundations and disciplined execution. Success depends not just on technology, but on aligning mindset, operating models, cost-aware architecture, and responsible-by-design governance with rapid innovation. Organisations that get this right will move beyond pilots and unlock long-term value.

At the same time, AI’s greatest potential lies in augmenting human capabilities. The most successful organisations will embrace a Human + AI approach, combining human judgement with intelligent systems to drive better decisions, accelerate innovation, and reimagine work. As AI becomes more embedded, trust, transparency, and accountability will be critical.

Ultimately, leaders in the next era of AI will be those who balance rapid innovation with strong foundations, responsible governance, and a commitment to empowering people – unlocking AI’s full potential to create lasting value.

Shane Buckley, President and CEO, Gigamon

AI Appreciation Day is a reminder that we’re entering a new era of enterprise AI. Models like Mythos are compressing months of programming expertise into minutes, accelerating innovation at a pace we’ve never seen before. But the same advances that transform business also transform cyber risk. Organizations that succeed will be those with the visibility to understand, govern, and secure AI as confidently as they deploy it.

Peter Marelas, Senior Director of Product Management, New Relic

The most significant shift in AI isn’t that it produces fluent answers. It’s that agents can now reason through complex, multi-step problems, testing and refining their own work until they reach a reliable result. We’ve moved from tools that respond, to systems that think through a problem.

However, the value we get from that still depends on us. The difference between a mediocre result and a genuinely useful one rarely comes down to the model. It comes down to how the problem is framed. The people getting real leverage from AI treat it less like a vending machine and more like a conversation, exploring a subject with it first, stating not just what they want but why, and asking it to explain and verify its own reasoning.

A great example of how visible this is right now is in how organisations keep their digital services running. When a banking app stalls or a checkout fails, engineers are often buried under thousands of alerts with no clear sense of what actually broke. AI has already changed this, sifting through the noise, correlating signals across systems, and pointing to a likely cause in a fraction of the time it once took. It has made the response time fix these systems meaningfully faster.

The next step is letting AI act on what it finds, not just advise. However, an agent is only as good as what it can see. Give it fragmented data and it will move toward the wrong fix, but give it a clear, connected view of the system and it can be trusted to act confidently.

That’s the real frontier for AI. Not building more capable models, but building the environments that let them act with confidence. The organisations that get this right will be the ones that turn AI’s promise into something they can rely on.

Related: AI Appreciation Day 2026: Industry Reacts

Manav Khurana, Chief Product and Marketing Officer at GitLab

As we mark AI Appreciation Day, the AI Accountability Report shows AI coding adoption and ROI are strong. 91% of organisations have two or more AI coding tools in active use, and 78% report that developers are writing and committing code faster since adopting AI tools. But speed is running ahead of control, with 43% of respondents reporting that they cannot reliably distinguish AI-generated code from human-written code in their own codebase. This comes with a forward-looking concern. 73% of respondents are concerned about the maintainability of AI-generated code in their organisation’s codebase, and 82% say it risks creating a new form of technical debt their organisation is not yet prepared to manage.

AI coding tools have delivered on their promise of speed. But the events of the past few months, including supply chain attacks, reliability issues, and regulators tightening expectations around AI traceability and provenance are making clear that speed without control is a liability, not an advantage. The teams thinking ahead are already asking the harder question: can we actually control all the code we’re generating? The organisations that will ship trusted software faster are the ones building the foundations of accountability with context, traceability, and governance baked into the platform, not just bolted on after the fact.

Andrew Kay, Senior Director, Systems Engineering APJ, Illumio

AI Appreciation Day isn’t just a celebration of innovation—it’s stark reminder of just how much cybersecurity has fundamentally changed in a mere 12 months. AI has accelerated at a pace some predicted but few were prepared for, giving organisations unprecedented opportunities while simultaneously handing cybercriminals faster, smarter, and more scalable ways to attack.

One thing Frontier AI has made impossible to ignore is the reality of cyber risk. It has stripped away any ambiguity about the speed of change and what organisations need to do now. Frontier AI capabilities are no longer exclusive or controllable; they exist, they are spreading rapidly, and becoming operationalised by threat actors. Governments and regulators around the world have been synonymous in their recognition of this very real threat in recent months.

Organisations that still rely on prevention alone are fighting yesterday’s battle. In the age of Frontier AI, resilience is measured by how effectively you contain the inevitable breaches, not by the illusion that you can stop them. If an attacker gains access, the priority is stopping them from reaching critical systems and sensitive data before they can cause catastrophic damage. This is what I hope to see when this notable day comes around next year – a meaningful shift toward breach containment.

Matt Caffrey, Senior Solutions Architect, Barracuda, Australia 

As we mark AI Appreciation Day on 16 July, it’s worth recognising that AI’s greatest success may also be creating one of organisations’ fastest-growing security blind spots: shadow AI. Employees are embracing AI to work faster, write better and solve problems more efficiently, in some cases using tools that have never been approved by IT or security teams. The challenge isn’t AI itself, but the lack of visibility into how it’s being used. 

Attempts to ban AI are unlikely to succeed and may simply push usage further underground, increasing the risk of sensitive data exposure, compliance breaches and unmanaged security risks. Instead, organisations should focus on discovering AI usage across business operations, assessing the risk level of tools and establishing sensible guardrails. By implementing practical governance that enables, rather than restricts, innovation, businesses can empower employees to harness AI’s productivity benefits while protecting critical data.

Kash Sharma, ANZ Country Manager, BlueVoyant

On AI Appreciation Day, the real opportunity is to celebrate AI responsibly by ensuring innovation and security evolve together, not in competition. 

Across APAC, AI has stepped up from something people prompt to something that acts on its own. A growing list of third-party agents are reading data, calling other systems and completing multi-step tasks on behalf of staff, often faster and more consistently than a person managing the same workload manually. Security teams are seeing genuine gains too: alert triage that used to take analysts hours now happens in minutes, and case summaries that took up a whole shift can be ready before an analyst has finished their coffee – real progress worth marking.

However, most businesses are sitting on years of ‘security debt’. These could be – files shared too widely, permissions nobody has reviewed, accounts with more access than they need, and an agent will happily draw on all of it when answering a question. The good news is this is one of the most solvable problems in security. Reviewing who has access to what, labelling sensitive data so protection travels with it, and holding agents to the same identity rules as staff are all well-established practices, not new inventions. It’s housekeeping, and the payoff is being able to hand agents bigger jobs with confidence.

The next 12 months will decide who gets the most out of this shift. AI agents will take on bigger jobs, working together across entire workflows rather than single tasks, and the region is well placed to lead here. APAC businesses have adopted this technology faster than most of the world, and the ones that pair that speed with proper controls will set the standard for what secure AI adoption looks like globally. That’s the opportunity worth talking about this AI Appreciation Day: not just what AI can do, but proving it can be done right.

Dr. Rebecca Hinds, Head of the Work AI Institute at Glean

The debate over whether AI will replace jobs is still too binary. The most immediate change is happening inside jobs, as AI takes over individual tasks and changes how people learn, contribute, and demonstrate their value.

Forty-eight percent of Australian digital workers fear AI could eliminate their role, while 58% say it has already automated meaningful work they would have preferred to keep. But the human work has not disappeared. Employees are still supplying the context, checking the outputs, correcting mistakes, and taking responsibility when AI gets something wrong.

The real risk is not simply that AI replaces people. It’s that organisations automate the parts of work through which people develop judgement, expertise and ownership, while leaving them with the clean-up. Leaders should stop asking how many roles AI can remove and start asking how work should be redesigned – what AI should do, what humans must continue to own, and how the productivity gains will be reinvested in people. Companies that use AI only as a headcount lever may cut costs in the short term, but they will also hollow out the skills and institutional knowledge they need to compete.

Luke Boyle, VP Operations APAC, Avetta

Australia’s AI conversation is shifting from experimentation to accountability. For organisations with a large workforce or those operating in high-risk environments, the challenge lies in leveraging AI to accelerate productivity while simultaneously meeting rising expectations on workplace health and safety (WHS), including psychosocial safety, privacy, sustainability, auditability, and operational resilience.

In particular, remote sites pose unique safety and data challenges. For example, mining and energy industries, which commonly operate sites in remote locations with poor connectivity, face more complex data needs for real-time logging of worker presence and location. Furthermore, workers in regional towns tend to adopt safety technology more cautiously, valuing trust and human involvement over rapid adoption of automation or AI solutions.

This is why businesses need to take a proactive, accountability-led approach to AI and WHS in tandem, rather than one being an afterthought to the other. With AI, organisations have the opportunity to reduce the surface risk earlier, but it must be implemented strategically with other intelligence tools that enable control, oversight, and transparency across the AI-influenced environments.

Lindsay Keating, Executive Vice President and General Manager APAC, Pax8

With AI Appreciation Day upon us, it’s worth looking at where AI is heading, toward software that doesn’t just assist but actually does the work, toward AI being consumed the way everything else is now, through marketplaces and partners. Not one-off direct deals, but consistent monthly consumption models.

My strong view is that the channel becomes the delivery mechanism that brings AI to the masses, particularly the millions of small and mid-sized businesses that would otherwise never build this themselves. That’s the democratisation piece.

I’d expect a shift to outcome-based models, more consolidation, and agents working alongside people as genuine co-workers. The winners won’t be whoever has the flashiest model — they’ll be whoever makes it usable, governable, and trusted at scale.

James Greenwood, AVP Solutions Engineering, APAC, Tanium

Anthropic’s Mythos disclosure findings have made it clear: the window from CVE disclosure to weaponisation is now measured in hours, not days, not the weeks businesses have planned around. AI is already building working exploits from known vulnerabilities in hours for under US$50. Most businesses and CISOs simply aren’t ready for what’s to come. Technical capability is not the obstacle. Organisations need to get out of their own way, shifting from a posture of manual reaction to one of autonomous control, with their people focused on the decisions that actually require human judgement.

Organisations need to move to an autonomous remediation state where routine patching, compliance validation, and vulnerability closure happen at machine speed, with humans setting policy, reviewing exceptions, and approving high-risk changes. That shift is only possible when security teams have complete, real-time visibility and control of every endpoint across the estate.

Ruhee Meghani, CEO and Founder, Allied Collective

AI is rapidly transforming the way we work, learn, solve problems, and relate with other humans. Promising higher returns, increasing productivity and analysing data in seconds, it’s got the world in a chokehold with businesses rushing to adopt AI.

Sure, it might seem like the silver bullet to usher us into the next new age of technology, however, AI shouldn’t be celebrated in isolation. AI is an amplifier of human input. Behind every AI tool are human decisions about how it’s designed, trained and used. That means its impact isn’t determined by the technology alone, but by the choices we make on how we use it.

With the jury still out on whether it moves the needle on productivity gains and impact on wellbeing, the question is whether AI will enhance human capability, or replace it. It can’t build trust, navigate difficult conversations with curiosity or understand the cultural and social context behind a decision using critical thinking. That’s why organisations need thoughtful leadership and strong governance to ensure AI supports better, not just faster decision-making.

As AI increasingly becomes part of everyday business, uniquely human qualities become more valuable. The best leaders won’t just ask, “should we use AI?” They’ll also ask, “How does this impact our future?” and “Who might this affect?”. The future won’t be defined by technology alone, but by how responsibly, inclusively and thoughtfully we choose to use it.

Mike Goldsworthy, Director, Solution Advisory at BlackLine

Artificial intelligence (AI) is opening up new possibilities for finance but, as adoption grows, trust must grow with it.

AI is advancing faster than the controls around it and, in finance, that gap carries real risk. As the Australian Securities and Investments Commission (ASIC) sharpens its focus on AI governance, the conversation is moving from adoption to accountability. Rising transaction volumes, tighter compliance obligations and more complex reporting requirements across ANZ mean the next phase of finance transformation will be led by organisations that can make AI traceable, explainable and auditable – moving from opaque ‘black box’ systems to a ‘glass box’ approach.

On AI Appreciation Day, it’s worth recognising that the value of AI in finance will not be measured by speed alone, but also the transparency and trust behind every outcome. Agentic Financial Operations represents this next step: glass box AI embedded within governed financial workflows, supported by human oversight and the controls needed to help finance teams scale with confidence and meet regulatory expectations.

Rucha Sawant, Managing Director, Regional Practices Lead, Australia, Avanade

This World AI Appreciation Day, the conversation has shifted from whether organisations should adopt AI to how they can scale agentic AI responsibly. AI agents are already beginning to reshape the way work gets done, but their success depends on more than deploying new technology. They need trusted data, strong governance, robust security and people with the confidence and skills to work alongside them. At Avanade, we’re increasingly working with organisations that are moving beyond AI pilots and looking to embed agentic AI into everyday business processes in a way that is secure, scalable and delivers meaningful outcomes.

Accenture research shows only 25% of organisations feel equipped with the AI capabilities their workforce needs, while more than half are still determining their approach towards the transformation. As organisations embed AI into everyday operations, the ones making great progress will be those who will invest deliberately in trust, skills, change adoption and workforce readiness while simultaneously modernising their technology foundations.

That’s why I believe the next chapter of AI transformation will move from being about productivity, algorithms and models to total enterprise reinvention.

On AI Appreciation Day, the key takeaway for business leaders is that success in the agentic era will be defined by those who build the culture, capability and confidence to scale it responsibly and turn possibility and innovation into sustained business value. And then the defining challenge becomes redesigning organisations where humans and agents can learn, decide and create value together.

Jarrod Kinchington, VP & GM, APAC, at Smartsheet

AI Appreciation Day is a useful moment to step back from the hype and recognise how quickly the conversation has matured. From where I sit, the focus has clearly shifted from whether to adopt AI to how to scale it, govern it and translate it into measurable performance.

What’s emerging now is a much more pragmatic mindset. Organisations are no longer trying to prove they are using AI; they are focused on what it is actually delivering. The questions I hear most often from senior executives are grounded and outcome-focused: what is improving, where is value being created, and how is it changing the way work gets done?

Most businesses are already seeing pockets of individual productivity gains, but faster outputs do not automatically translate into stronger organisational performance. The real gap is organisational adoption. Too many organisations are still layering AI onto existing workflows rather than redesigning processes, decisions and operating models around it.

Across APJ, this plays out differently by market. Australia and New Zealand show strong executive intent and experimentation, but scaling outcomes remains uneven. Singapore tends to align AI more closely to execution. Across the region, organisations are increasingly disciplined about linking AI to measurable business impact rather than simply driving usage.

That means focusing on outcomes over activity, sharing proven use cases, encouraging experimentation within clear guardrails, and measuring productivity, quality and customer impact. Despite these differences, the core challenge is consistent: moving from experimentation to outcomes while managing limited execution capacity and competing priorities.

At the same time, AI is reshaping how teams collaborate. Work is evolving from human-to-human to human-to-human-to-AI, with specialised agents supporting everything from research to execution. In this environment, human judgement becomes more important, particularly in areas like critical thinking, decision-making and communication.

The organisations making the most progress are treating AI as an operating model transformation, not a software rollout. They are investing in data, governance and leadership capability, and importantly, using governance to enable scale rather than constrain it.

What stands out to me about this moment is that AI is no longer just accelerating how people work; it is forcing organisations to rethink how work happens and how it translates into real business outcomes. 

Peter Marelas, Senior Director of Product Management, New Relic

The most significant shift in AI isn’t that it produces fluent answers. It’s that agents can now reason through complex, multi-step problems, testing and refining their own work until they reach a reliable result. We’ve moved from tools that respond to systems that think through a problem.

However, the value we get from that still depends on us. The difference between a mediocre result and a genuinely useful one rarely comes down to the model. It comes down to how the problem is framed. The people getting real leverage from AI treat it less like a vending machine and more like a conversation, exploring a subject with it first, stating not just what they want but why, and asking it to explain and verify its own reasoning.

A great example of how visible this is right now is in how organisations keep their digital services running. When a banking app stalls or a checkout fails, engineers are often buried under thousands of alerts with no clear sense of what actually broke. AI has already changed this, sifting through the noise, correlating signals across systems, and pointing to a likely cause in a fraction of the time it once took. It has made the response time fix these systems meaningfully faster.

The next step is letting AI act on what it finds, not just advise. However, an agent is only as good as what it can see. Give it fragmented data and it will move toward the wrong fix, but give it a clear, connected view of the system and it can be trusted to act confidently.

That’s the real frontier for AI. Not building more capable models, but building the environments that let them act with confidence. The organisations that get this right will be the ones that turn AI’s promise into something they can rely on.

Noah Drake, Chief Executive Officer, Xenith IG

Across Asia-Pacific, hyperscalers alone have committed over US$160 billion to AI-related infrastructure. APAC is now also a significant investment region for neoclouds.

AI Appreciation Day will encompass discussions on the ongoing advancements of AI technologies, and how companies are applying them to increase productivity and drive innovation. Doing so ethically must also be part of the conversation.

But responsible AI isn’t only about how the technology is applied. As AI workloads become more pervasive across all facets of work and social life, ensuring integrity of the foundations they run on – data centres, fibre connections and energy supplies – is equally critical.

Ongoing investments in AI infrastructure designed for resilience will allow AI to scale successfully and sustainably in the years ahead.

Nigel Lindsay-Smith, Managing Director ANZ, NiCE

This AI Appreciation Day, I’d like to highlight one of AI’s most overlooked strengths: helping organisations stay resilient when demand suddenly spikes.

Australian businesses are operating in an increasingly unpredictable environment. Whether it’s extreme weather, cyber incidents, service outages or workforce shortages, customer demand can quickly exceed what human teams alone can manage. And in today’s economic climate where customer loyalty is hardwon and margins remain under pressure, many businesses simply can’t afford to drop the ball when demand surges.

AI provides the flexibility to absorb demand surges and ensures customers continue to receive support while human agents focus on the conversations that require empathy and complex problem-solving. In other words, AI helps organisations build the capacity to respond when they need it most. That doesn’t mean AI replaces people. In fact, NiCE’s recent research, the Agentic AI CX Frontline Report, shows 95% of AI initiatives fail to scale, often because organisations focus on the technology rather than how people and AI work together.

That’s what we should acknowledge and appreciate this AI Appreciation Day: AI’s ability to complement human expertise and strengthen organisational resilience, helping businesses navigate an increasingly unpredictable world.

Anthony Daniel, MD, ANZ & The Pacific Islands, WatchGuard Technologies

We have officially moved past the novelty era of artificial intelligence. Not long ago, the cyber threat landscape followed a manageable rhythm: attackers found a technique, defenders patched it, and the cycle repeated at a pace security teams could plan around. Today, that cycle no longer exists.  

In 2025, WatchGuard’s threat intelligence recorded unique malware climbing every single quarter, culminating in a staggering 1,548% jump between Q3 and Q4 alone. Crucially, nearly a quarter of everything blocked had never been seen before, bypassing traditional signature-based tools by design. 

This is where AI’s value becomes tangible. Its greatest contribution is not simply that it can detect threats faster, although that capability is critical. It is what that speed allows people to do. Security teams have spent years managing overwhelming alert volumes and piecing together information across disconnected systems. By absorbing repetitive work, AI gives cyber professionals something they’ve rarely had: time to think. Time to investigate the threats that actually matter, build stronger relationships, and make the judgment calls no algorithm can replace.  

AI Appreciation Day is the right moment to recognise that shift. But the deeper impact may be cultural. AI is encouraging organisations to rethink how people and technology work together. When it takes on speed, scale, and repetition, human defenders are left to bring what machines cannot: empathy, perspective, accountability, and purpose. That is the real promise of AI, not less human involvement, but a far more meaningful human contribution.

Last Updated on July 21, 2026 by Nick Ross

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Nick Ross

Nick Ross is a veteran tech journalist. He is Editor in Chief of SMBtech, an Australian-focused website for technology and business, and High Performance Laptops.

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