As AI moves from hype to practical implementation, tech leaders from across APAC share how human-centric, results-driven Artificial Intelligence is reshaping workflows, empowering employees and driving long-term business value.
Simon Ma, Managing Director, Asia, Freshworks
AI has moved beyond the hype cycle and into a stage where its impact is being measured by how effectively it solves real problems.
The most valuable AI today isn’t necessarily the most complex – it’s the kind that is easy to adopt, fits into existing workflows and delivers tangible results without adding friction.
At Freshworks, the focus has been on making work simpler for people. By automating repetitive tasks and surfacing intelligent recommendations, employees can concentrate on high-value interactions that require empathy, creativity and human judgment.
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. AI that can self-learn, require minimal tuning and work across systems is what ultimately delivers sustainable value.
Rather than replacing jobs, this technology is helping people do their jobs better. The aim is not to overwhelm users with complex features but to create tools that are intuitive, fast to implement and flexible enough to meet the needs of businesses both large and small. The path forward lies in keeping AI human-centric – practical in design, purposeful in use and accessible to all.
Jeremy Ung, Chief Technology Officer, BlackLine
Artificial Intelligence is not just transforming industries but fundamentally reshaping how we work and create value.
At BlackLine, we’ve witnessed firsthand the profound impact of AI, particularly in the finance sector where precision and trust are paramount.
The evolution of AI from traditional data science to sophisticated agentic AI combined with large language models is enabling us to generate more human-like reasoning and outputs. This isn’t about replacing human intelligence but augmenting it. Our focus is on empowering finance professionals by automating manual workflows and freeing them to concentrate on strategic high-value activities. 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 foster a continuous learning loop.
AI powers true Digital Transformation, driving us beyond fragmented data silos. With data as a central asset, AI can fuel intelligent workflows that will elevate finance to unprecedented heights.
Han-Tiong Law, Regional CTO ASEAN and Greater China, Rimini Street
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. For enterprise software environments, that means aligning AI initiatives with operational excellence, agility and long-term strategy.
Many organisations managing mature, mission critical and complex ERP environments are weighing these decisions carefully. Embarking on migrations purely to stay “current” often brings significant cost, disruption and uncertain returns. With extended support, management and innovation solutions available from independent providers like Rimini Street, organisations can continue to run their existing ERP platform well beyond vendor-set maintenance end timelines along with the ability to self-fund and to flexibly explore AI on their own terms.
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.
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?” For many, the answer lies in staying agile, informed and intentional about their ERP roadmap.
Luca Spinelli, Managing Director for Singapore, SAS Institute
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 surpassing understanding, trust and responsible innovation must take centre stage.
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.
After having dedicated decades to helping organisations operationalise AI with the essential guardrails for robust governance and the depth required for risk-based decisioning, we prioritise trust, traceability and measurable outcomes. Especially in financial services, government and other regulated industries, these qualities are foundational and engineered for auditability, fairness and scalability.
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.
Dinesh Varadharajan, Chief Product Officer at Kissflow
This National AI Appreciation Day, 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.
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 GenAI-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 co-pilot of modern enterprise innovation.
Attribution: Lim Hsin Yin, Vice President of Sales, ASEAN, Cohesity
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 it 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.
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 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.
Today, the use of legacy backup systems is no longer effective or efficient. The challenge isn’t just about storage; it’s about accessibility and intelligence. This is where modern data storage and indexing solutions come in. Traditional backup systems treat data as write-once, read-rarely archives. At Cohesity, we fundamentally change this paradigm by making backup data searchable, queryable and analytically useful through advanced AI capabilities.
Through the use of advanced retrieval-augmented generation (RAG) technology – the real game-changer – the Cohesity Gaia AI platform transforms enterprise backup data into actionable business intelligence, offering unprecedented insights from previously inaccessible data repositories.
The impact? Businesses gain actionable intelligence from better-organised data, smoother workflows, cost savings and regulatory compliance. Many companies may underestimate the power of their own backups, which offer a trove of information – spanning from predicting buying patterns based on customer behaviour and more informed decision-making to understanding how a cyberattack occurred.
With AI-powered data security and management capabilities, businesses can ensure a reliable and strong data source, ingestion and storage.
It is imperative for organisations to have a fundamental mindset shift for their data assets. Rather than viewing backup and archival data as a necessary cost centre, there is no better time than now to begin treating these repositories as a strategic asset of intelligence. As AI capabilities continue to gain speed and integration becomes more seamless, the line between operational and analytical data will continue to blur. Enterprises that are capitalising on their backup data today will hold a significant winning edge over those who rely on traditional business intelligence tools.
