The 2024 technology predictions bonanza

Frontier Enterprise presents an insightful compilation of 2024 technology predictions. The incoming year’s forecast coverage includes AI/ML, automation, the cloud, data centres, digital transformation, the future of work, supply chain management, and more.

Image by Unsplash


Optimising LLMs: Techniques like retrieval-augmented generation (RAG) and performance efficient fine tuning (PEFT) will gain traction. RAG, requiring no training of LLMs, uses a knowledge base for context, while PEFT, a fine-tuning approach, provides high performance with lower costs. The adoption of fine-tuning methods is anticipated to grow, especially in organisations with strong data science capabilities. I believe that RAG will continue to be an accessible approach to generative AI for many organisations in 2024.

– Daniel Hand, Field CTO for APJ, Cloudera


  • Retrieval-augmented generation will be paramount for grounded, contextual outputs when leveraging AI: The excitement around large language models and their generative capabilities will continue to bring with it a problematic phenomenon of model hallucinations. These are instances when models produce outputs that, though coherent, might be detached from factual reality or the input’s context.

    As modern enterprises move forward, it’ll be important to demystify AI hallucinations and implement an emerging technique called retrieval-augmented generation (RAG) that when coupled with real-time contextual data can reduce these hallucinations, improving the accuracy and the value of the model. RAG brings in context about the business or the user, reducing hallucinations and increasing truthfulness and usefulness.
  • Real-time data will become the standard for businesses to power generative experiences with AI; Data layers should support both transactional and real-time analytics: The explosive growth of generative AI in 2023 will continue strong into 2024. Even more enterprises will integrate generative AI to power real-time data applications and create dynamic and adaptive AI-powered solutions​. As AI becomes business critical, organisations need to ensure the data underpinning AI models is grounded in truth and reality by leveraging data that is as fresh as possible.

    Just like food, gift cards and medicine, data also has an expiration date. For generative AI to truly be effective, accurate and provide contextually relevant results, it needs to be built on real-time, continually updated data. The growing appetite for real-time insights will drive the adoption of technologies that enable real-time data processing and analytics. In 2024 and beyond, businesses will increasingly leverage a data layer that supports both transactional and real-time analytics to make timely decisions and respond to market dynamics instantaneously.

– Rahul Pradhan, VP, Product & Strategy, Couchbase


Revving up for 2024’s AI race, smart organisations will drive innovation with developer platforms built for data

The artificial intelligence (AI) race to turbocharge progress has accelerated rapidly in 2023, ending the year with two major events at OpenAI and Microsoft that may determine AI regulation and development speed for years to come. Whatever a perfect balance looks like, one thing is certain: organisations will need to weave AI into every part of their fabric in 2024 to stay ahead.

An IDC report predicts that 80% of CIOs in the Asia Pacific will leverage organisational changes to harness AI to drive an agile digital business by 2028. To lead the AI race next year, organisations need speed and agility as they experiment with AI to drive innovation. Multi-cloud developer data platforms that run on any cloud will become the fuel helping organisations get their AI ideas to market faster and easier while staying in full control of their data. 2024 will be a year of blistering AI development, and only organisations that think on their feet will fully benefit from this revolutionary technology.

– Stewart Garrett, Regional Vice President, ASEAN, MongoDB


  • LLMs will power virtual assistants: A synergy of automation, generative AI, and specialised AI is enhancing virtual assistants. This is redefining interactions with machines and significantly boosting productivity.

    Autopilots are now capable of quickly learning and executing a wide range of activities. These include handling data in various formats, managing emails, and generating reports. By understanding work contexts and automating repetitive tasks, they free up employee time for more valuable activities, thus increasing workstream efficiency.

    As virtual assistants become more accessible and easier to adopt, they are expected to become integral in workplaces across Asia-Pacific, particularly for knowledge workers facing increasing work pressures. Their implementation is seen as a crucial step towards more efficient and sustainable organisational cultures.
  • Safe AI will be a primary focus for leaders
    Currently, there is no universal AI regulatory standard, but governments in the region are proactively establishing trusted AI frameworks that emphasise privacy, security, and ethical data handling practices. For example, Singapore’s Infocomm Media Development Authority (IMDA) and the AI Verify Foundation have launched the Gen AI Evaluation Sandbox to set new benchmarks for evaluating generative AI.

    With evolving data privacy and protection regulations surrounding AI, executive leaders are taking proactive steps to mitigate the risks associated with AI misuse and miscalculations. This is leading to the development of new safeguards and innovations, refining the AI risk-benefit equation.

    Effective AI governance is becoming crucial for achieving strong AI outcomes. In 2024, an increasing number of organisations will experience the shift of AI governance from concept to practice, driven by innovation. Enterprise software companies are incorporating AI controls into their products, and AI providers and scientists are focusing on building additional trust layers. This ensures organisations can confidently utilise new AI capabilities, secure in the knowledge that their data is protected.

– Jess O’Reilly, Area Vice President, Asia, at UiPath


Embracing generative AI in APAC: Asia-Pacific is leading in generative AI adoption as per IDC, with two-thirds of companies investing or exploring its uses. As generative AI tools like DALL-E and ChatGPT become more common, organisations need to boost AI literacy to maintain trust. AI could complicate the distinction between real and fake, posing a challenge that APAC could lead in addressing, ensuring deepfakes don’t harm legitimate businesses and aiding in distinguishing fact from fiction.

– Robert Blumofe, Executive Vice President and Chief Technology Officer, Akamai


  • AI and ML will become a key component of enterprise data protection: As enterprises recognise the need to prevent data loss across their footprint, it is likely that they will increasingly leverage AI to identify and protect their data. One challenge they often face is a lack of visibility into all the places where their critical data lives and are thus unable to classify and protect it effectively.

    As a result, we anticipate that enterprises will increasingly leverage AI as a way to gain data visibility and improve their data hygiene. Using ML, for instance, it is now possible to discover and classify sensitive data, and set policies automatically, such as financial and legal documents, PII and medical data, and much more.
  • AI will transform how enterprises understand risk and security from the top down: While enterprises currently leverage AI to unleash new potential and insights across IT, technology, marketing, customer experience, and more, they will increasingly look to AI and ML to transform how they view risk. Here are three key roles that AI will increasingly play for security:
    • Provide a comprehensive view of risk: In much the same way that AI is helping discover and classify data, enterprises will increasingly use AI to visualise and quantify risk across their entire footprint. This includes gaining comprehensive insights and risk scoring across their attack surface and across their business entities —including their workforce, applications, assets, and third parties.
    • Deliver top-down visualisation and reporting: Similarly, enterprises will leverage AI to gain top-down and board-level visualisations of their risk to uncover and drill down into their top contributing factors to risk, including the ability to quantify the financial impact of exposures. This helps enterprises make informed decisions on which threats and vulnerabilities to address first.
    • Drive prioritised remediation: Finally, enterprises will seek AI tools that allow them to automatically gain prioritised security actions and policy recommendations, which are tied to their key risk drivers and which quantifiably improve the security of their organisation.
  • Increasing regulations around generative AI: While APAC governments have had an overall proactive stance on new technologies, including generative AI, with issues of fraud, copyright infringements and other cybercrimes surfacing, governments in the region are looking to create regulatory frameworks that provide guardrails without inhibiting innovation.

    In 2023, we saw the establishment of the AI Verify Foundation, a not-for-profit organisation aimed at facilitating the adoption of responsible AI and promoting best practices and standards for AI. And in mid-November, the Monetary Authority of Singapore (MAS) announced the successful conclusion of phase one of Project Mindforge. The project is aimed at developing a risk framework to encourage the responsible use of generative AI for the financial sector – and this will likely pave the way or act as best practice for other sectors.

– Mohan Veloo, VP Solutions Consulting, Zscaler


AI’s prominence in the enterprise technology space will persist in 2024, driving transformative changes in software development. It will remain a top priority for businesses with an increasing demand for AI-driven solutions to develop more sophisticated applications. These include intelligent applications that leverage data and incorporate predictive and prescriptive analytics to deliver personalised user experiences.

To capture attention in the AI space, many low-code platforms will rebrand as AI-powered application development tools. With this integration, the next phase of AI-powered software development will highlight developers assigning routine tasks to AI-powered mentors, easing the burden of mundane work. Developers will focus on expert-level coding, while their AI companions manage code duplication, manual testing, UI updates, and script configurations.

Low-code tools will also evolve to empower organisations to build AI applications from scratch. For example, high-performance low-code platforms could integrate large language model connectors, enabling developers to embed capabilities like ChatGPT into applications, provide personalised recommendations, and power virtual assistants.

Data management will become crucial for organisations. Implementing AI and building intelligent applications will require large amounts of data for insights and decision-making. Businesses must ensure their data is AI-ready and understand effective data management practices, including data collection, cleansing, labelling, security, and governance.

On the talent front, AI is transforming work structure, with 40% of working hours across industries expected to be influenced by large language models. This shift will alleviate skilled professional shortages in diverse sectors in APAC. Within software development, AI can automate code generation, testing, and deployment, allowing developers to focus on complex problem-solving with innovative applications. Natural language inputs for app development will also broaden the talent pool.

AI will impact the job landscape significantly. It is predicted to replace 85 million jobs but create 97 million new roles by 2025. Analysts expect a 40% increase in AI and machine learning specialists by 2027. New jobs will include prompt engineering, utilising AI experts to design and refine generative AI text prompts for various applications, particularly with the rise of natural language processing tools.

– Leonard Tan, Regional Director, Singapore and Greater China Region, OutSystems


Generative AI has made a crashing entrance in the global technology and business conversation in late 2022 and 2023, with expectations of significant business impact. In 2024, will it live up to the massive amount of hype it has generated? The short answer is yes.

While current large language models will continue to thrive, there is also an increasing need for smaller, more cost-efficient models. These models will get smaller and smaller to run on low-footprint installations with limited processing capabilities, including on the edge or on smaller enterprise architectures. In 2024, new AI platforms will also increasingly battle hallucinations by combining generative AI models with high quality information from knowledge graphs. In support of all this, platforms will arise, providing tools for companies to leverage generative AI without the need for deep internal technical expertise. This will lead, in the long run, to the creation of interconnected networks of models designed and fine-tuned for specific tasks, and to develop true multi-agent generative ecosystems. 

Why it matters: These developments in generative AI are indicating an evolution towards a more accessible, versatile and cost-effective technology. These innovations will enable organisations to scale their generative AI use cases faster while also deriving more long-term value from the technology. 

– Pascal Brier, Chief Innovation Officer, Capgemini


  • Increased adoption of generative AI will drive the need for clean data. Data forms the foundation of generative AI, and for it to function properly, it requires clean data. Regardless of the source – whether from modelling or a warehouse – quality data is essential. Poor data can lead to bad recommendations, inaccuracies, bias, and so forth. As more companies utilise generative AI, a robust data governance strategy becomes increasingly vital. Ensuring data stewards can access and control this data is also key.
  • Generative AI will fall from the peak of inflated expectations to the trough of disillusionment. The hype around generative AI has led some companies to adopt it just to keep up, rather than to address specific problems. We’re likely to see multiple failed generative AI projects — thus, the descent into disillusionment. Senior leaders, afflicted with “shiny new object syndrome,” will feel pressured to implement generative AI programs. Limiting failed projects requires companies to understand the purpose and objectives for using generative AI, ensuring it’s linked to defined business outcomes and a method for measuring investment success is established.

– Rex Ahlstrom, Chief Technology Officer, Syniti


  • AI’s shift to necessity: AI, expected to grow significantly in value, will become essential for businesses. However, many organisations, especially in ASEAN, aren’t fully prepared to leverage it, as found by Cisco’s AI Readiness Index. Only a small percentage are ready for AI deployment, with concerns about business impacts if not acted upon swiftly. Most companies are increasing their urgency to deploy AI and are developing AI strategies, yet gaps remain in infrastructure, data, governance, talent, and culture. 2024 will challenge ASEAN companies to integrate AI comprehensively.
  • Responsible AI governance: Ethical management of AI and data is becoming crucial. Most ASEAN organisations acknowledge the importance of AI governance, but improvements are needed, especially in data privacy and bias detection. Companies must keep abreast of evolving regulations and establish strong internal policies for data security and ethical AI use. This includes cybersecurity measures for AI systems and continuous employee training.

– Bee Kheng Tay, President, Cisco ASEAN


  • AI knowledge gap in leadership: The gap between companies that invest in AI and those that don’t is widening. AI-savvy businesses will see productivity gains, while others lag behind. This divide will determine future economic leaders.
  • AI model breaches: With the growing reliance on AI models for critical business functions, the risk of AI model tampering and breaches will increase. Companies adopting AI without adequate security measures may become vulnerable targets, affecting sectors like healthcare, banking, and energy.
  • Managing rising AI costs: As AI experimentation increases, so will the associated costs. Developer teams will face pressure from CFOs to justify AI expenditures and demonstrate ROI. Tools for managing, monitoring, and setting boundaries on AI spending will become crucial.

– Jonathon Dixon, Vice President and Managing Director, APJC, Cloudflare


Generative AI reshaping the workplace: A glimpse into the transformative impact across Asia in 2024

In the past year, rapid digitalisation has fuelled the momentum of generative AI in Asia, transforming operations across industries from retail to government services. Roughly two-thirds of organisations in the region are either exploring or have already invested in the technology to drive enterprise intelligence, marketing and R&D, among others. 

Looking ahead to 2024, the ubiquity and accessibility of generative AI will also continue to extend its impact in the workplace, redefining our relationship to work and significantly shaping how teams communicate. From AI-powered universal search, to intelligent workspace features that can quickly extract insights from working material, generative AI tools will empower faster, more organised and intuitive internal processes. This allows the modern knowledge worker to tap on technology to achieve better focus and flow, creating an environment that is genuinely conducive for enriching collaboration among teams. 

With AI transforming the nature of work, it is critical that business leaders also spearhead efforts in exploring new workplace models and practices in tandem with this paradigm shift. Executives need to pay closer attention to how employees are working with AI and better understand the value of AI for their entire workforce and business. As organisations in Asia embed generative AI into their workflow and operations, companies that embrace intentional flexibility will come out ahead. Ultimately, in this competitive climate, empowering employees to bring their best selves and best work to the table is the factor that will make all the difference to the bottom line.

– Doreen Tan, Head of Asia, Dropbox


AI will continue to play a critical role in transforming the landscape of media and advertising in Asia-Pacific. Generative AI, in particular, has elevated content consumption and creation to unprecedented heights by quickly producing content at scale. While this presents a wealth of benefits, challenges loom on the horizon. Maintaining quality inventory, safeguarding against unsafe or inappropriate content, and mitigating the risk of invalid traffic will remain pressing concerns. However, the silver lining is that AI models can also be trained to recognise patterns of unsafe content or fraudulent activity. Adopting a proactive approach here will empower advertisers to detect, block, and prevent instances that could compromise campaign integrity.

– Conrad Tallariti, Regional Vice President, DoubleVerify


Generative AI vs classic AI

AI adoption has evolved significantly. In the 2000s, sectors like banking used AI for handling unstructured data. The 2010s saw a surge in enterprise AI, thanks to affordable public cloud services. This democratisation led to user-friendly AI platforms. While generative AI is gaining attention, it’s vital to recognise the untapped potential of classic AI.

AI: Practicality and personalisation

AI is becoming more practical and personalised. Unlike past trends like the metaverse or blockchain, AI is being integrated into everyday applications. AI at the edge, for instance, is making AI processes more efficient, removing the need for extensive hardware. This shift allows for hyper-personalised user experiences, tailored to individual patterns and preferences.

– Linda Yao, Chief Operating Officer and Head of Strategy, Lenovo Solutions & Services Group


Generative AI will augment, not replace, SOC analysts in cybersecurity

As the cybersecurity landscape evolves, generative AI’s role within security operations centres (SOCs) will be characterised by augmentation rather than replacement of human analysts due to its maturity limitations. For the Asia-Pacific region, which faces a critical shortage of 2.7 million cybersecurity workers, generative AI will be able to assist and enhance the capabilities of short-staffed SOC teams with the necessary expertise to interpret its output, proving especially valuable for mid-level analysts. Organisations will need to discern genuine generative AI contributions amid marketing hype, and the debate between investing in more technology like generative AI or hiring additional SOC analysts will persist, with the human factor remaining crucial. Success will depend on aligning these tools with analyst workflows rather than relying on superficial intelligence.

Generative AI adoption will lead to major confidential data risks

Just as there was initially a lack of understanding regarding the shared responsibility model associated with cloud computing, we find ourselves in a situation where generative AI adoption lacks clarity. Many are uncertain about how to effectively leverage generative AI, where its true value lies, and when and where it should not be employed. This predicament is likely to result in a significant risk of confidential information breaches through generative AI platforms. This echoes findings from a recent survey of channel partners by LogRhythm, which found 47% to have grave concerns about AI tools causing data leaks, while 18% are particularly anxious about potential leaks of proprietary business data.

– Andrew Hollister, CISO & VP Labs R&D, LogRhythm


AI’s evolution will unveil new possibilities: In 2024, AI will continue to evolve, revealing new opportunities. Despite common perceptions of its overuse in headlines, the real value of AI will emerge as we move beyond the initial hype. Understanding AI’s risks will be key to leveraging its full potential.

AI design to enhance DevOps: The year will see a shift in AI design philosophy, emphasising the importance of operationalization. The focus will be on maintaining AI systems efficiently, requiring a specialised approach that integrates development and operations.

AI hot take: With AI becoming more profitable, there’s a shift towards using it for financial goals and ethical applications. The challenge lies in ensuring cybersecurity and ethical considerations keep pace with AI’s profitability, which attracts attention from good guys and bad guys.

– Mona Ghadiri, Senior Director of Product Management, BlueVoyant


Responsible AI adoption and leadership (John Cannava, CIO): Cannava discusses the growing integration of AI in the workforce and its implications. He foresees CIOs becoming AI leaders in 2024, ensuring secure and ethical AI use. The prediction also includes the emergence of new roles like Chief AI Officer, who will work alongside CIOs to navigate AI adoption and compliance with emerging regulations.

– Ping Identity


Automation’s role in crafting effective campaigns

As brands contend for attention from a diverse APAC audience, the optimisation of campaigns will need to keep pace with rapidly evolving channels and factors that influence effectiveness. Automation will be a pivotal tool in this endeavour, enabling advertisers to adapt with agility. Advertisers should consider where they can leverage automation to not only streamline workflows but drive better campaign outcomes. This will help advertisers focus on the more strategic campaign metrics and enable them to not only survive, but thrive in a dynamic media environment.

By ensuring that marketing strategies are attuned to the changing dynamics of the media landscape in the APAC region, the path forward lies in  embracing holistic measurement strategies that account for evolving complexities in the media landscape. AI presents both challenges and opportunities for marketers, while the rise of retail media networks necessitates a focus on quality. Automation, as a powerful ally, will enable campaign optimization, with the agility required to stand out in a competitive arena. By combining these elements, marketers can navigate the future with confidence, achieving success in the midst of a fragmented and ever-evolving media landscape.

– Conrad Tallariti, Regional Vice President, DoubleVerify


AI will revitalise “auto” in automation and enhance self-automation capabilities: Historically, automation has required considerable manual input to function effectively. This is changing, with the emergence of “hands-free” automation enhancements that reduce time, expertise, and effort needed for intelligent automated workflows.

No-code tools are enabling teams to transform natural language into automated processes for various tasks. Additionally, new generative AI and analytics techniques are simplifying behaviour modelling, automating complex tasks in model training like document processing and data management.

These advancements in automation are not only detecting execution issues but are also capable of self-correction, autonomously resolving identified problems. This is particularly relevant in regions like Singapore, where a significant portion of workers rely on automation for resolving IT and technical challenges. This evolution of automation is solidifying its role in overcoming technical obstacles and laying the foundation for innovation and digital transformation in organisations.

– Jess O’Reilly, Area Vice President, Asia, at UiPath


The fusion of cloud and edge computing makes AI at edge ready for mainstream adoption

The conversion of cloud and edge computing allows the seamless integration of AI capabilities directly into edge devices and services. By leveraging the cloud’s vast computing power and storage capabilities, AI models can be trained, refined, and deployed more efficiently. The edge, in turn, facilitates real-time processing and decision-making, reducing latency and enhancing performance for AI applications.

This fusion optimises the distribution of computing resources, enabling organisations to deploy AI at the edge for faster, more responsive, and context-aware applications. As a result, the combination of cloud and edge computing provides a robust infrastructure that makes AI at the edge readily accessible and practical for a wide range of applications, fostering its mainstream adoption.

– Chin Keng Lim, Senior Director, APCJ, F5 Inc


Challenges with cloud infrastructure: IT teams are grappling with complex, expensive cloud environments. The focus will shift towards vendor consolidation and platforms that offer better connectivity and observability. Cloud services that restrict data mobility will struggle.

– Jonathon Dixon, Vice President and Managing Director, APJC, Cloudflare


AI will cause a shakeup in cloud computing: We expect to see a shakeup in the cloud computing space with the emergence of a new generation of specialised cloud providers concentrated on AI-specific services such as graphics processing unit (GPU) cloud will disrupt the established status quo of IaaS hyperscalers.

  • This new breed of hyperscalers will grow rapidly on the back of GPU chip manufacturers channelling demand from a broad base of customers to cloud providers.
  • This space will also see M&A activities as the incumbent IaaS hyperscalers move to acquire AI cloud capabilities.

2024 will see the rise of the sovereign cloud: There is increasing desire for sovereign cloud based on tightening of regulations pertaining to the use and location of data, especially within industries such as financial services. Additionally, AI systems like generative AI raise issues of sovereignty during the training process.

  • 2024 will see the rise of the sovereign cloud, as more organisations respond to government regulations requiring them to store data within their own jurisdictions for greater data control.
  • Countries that are taking the lead include Australia, New Zealand, Japan, and Indonesia.

– Pure Storage

Customer experience

To meet desired customer outcomes, the larger platform play will gain traction. In today’s economy, merely selling tools and solutions is insufficient. Customers increasingly demand vendors to demonstrate a stronger link between their offerings and ROI to justify expenditure. Hence, more organisations will transition from myriad point solutions to a platform approach. Consequently, vendors offering only one solution will be incentivised to explore acquisitions or partnerships, expanding into comprehensive platforms.

– Rex Ahlstrom, Chief Technology Officer, Syniti


The rapid technological advancements require companies to maintain a strong focus on IT and innovation. Crucially, these developments must not overlook the customer journey and experience, which are integral to a company’s technological approach.

  • Increased competition for goldfish attention spans: The growing reliance on multiple devices among consumers leads to shrinking attention spans. Companies now face the challenge of capturing and retaining customer attention in brief interactions. Technology’s role as the initial touchpoint is crucial in creating positive brand experiences.
  • Sentiment-driven CX becomes more viable: Sentiment analytics, now more accessible due to AI advancements, enables businesses to track and react to customer emotions throughout their journey. This progress allows for real-time detection of emotions, informing decisions on whether to direct customers to automated channels or human agents. Understanding customer sentiment, whether positive or negative, aids in making strategic decisions, like the timing for review requests or amends. This deeper insight into how sentiment influences loyalty, satisfaction, and advocacy is pivotal for business growth strategies in 2024, enhancing brand preference and loyalty.
  • Embracing the AI colleague: The age of having AI as colleagues is upon us. As companies embrace AI, a key question arises: what is the role of humans, and why is this important? This is especially pertinent in customer experience (CX), where human connection is key.

    Think of an anxious customer who needs to visit a sick relative abroad but cannot find an available flight, or an e-commerce business owner dealing with payment gateway issues. These are high-tension moments which make or break the brand promise. In such situations, a chatbot will struggle to empathise with the urgency of the situation. Hence, we believe strongly in a human-led collaboration with AI for greater outcomes.

– Angie Tay, EVP and Group Chief Operating Officer, TDCX


  • MLOPS and data integration for gen AI: Organisations face data privacy challenges with SaaS-based large language models (LLMs) like ChatGPT and open-source alternatives. In 2024, I expect organisations to continue to focus on developing strong Machine Learning Operations (MLOPS) and data integration capabilities.
  • Cloud strategy evolution: A shift from “cloud-first” to “cloud-considered” approach is expected, driven by factors like economic considerations and data management regulations. Organisations are likely to adopt a cloud-native architecture, balancing public and private clouds for data and cloud strategy.
  • Data management trends: The exponential increase in data will drive the need for automation in data platform management. The focus will be on data democratisation, zero-trust security, and hybrid cloud-native architectures. Zero-trust security, emphasising continuous authentication and minimal permissions, is expected to be simplified and more widely implemented. In 2024, I expect technology to increasingly simplify the implementation and enforcement of zero-trust both within organisations and – more so – across them, as data federation becomes an increased area of interest.
  • Open data lake house migration: The growing adoption of Apache Iceberg for data lake house implementations indicates a shift towards open data lakehouse architectures. In 2024, I expect to see a steady migration of data and workloads into open data lake house architectures across public and private clouds.

– Daniel Hand, Field CTO for APJ, Cloudera


  • Adaptive data protection will autonomously fight hackers without organisations lifting a finger: More than two-thirds of organisations are looking to boost their cyber resiliency with the help of AI. However, given AI’s dual nature as a force for both good and bad, the question going forward will be whether organisations’ AI-powered protection can evolve ahead of hackers’ AI-powered attacks. In the current hybrid work model, the growing data sprawl means more vulnerabilities with greater attack surface.

    Part of that evolution in 2024 will be the emergence of AI-driven adaptive data protection. AI tools will be able to constantly monitor for changes in behavioural patterns to see if users might have been compromised. If the AI tool detects unusual activity, it can respond autonomously to increase the level of protection. For example, initiating more regular backups, sending them to different optimised targets and overall creating a safer environment in defence against bad actors.
  • Tool bloat will force a “one in, one out” approach to enterprise security: Estimates put the average enterprise security tool set at 60-80 distinct solutions, with some enterprises reaching as many as 140. Too much of a good thing is bad—enterprise security tool sprawl leads to a lack of integration, alert fatigue and management complexity. The outcome is a weakened security posture, the exact opposite of what was intended.

    Recognising this paradox, in 2024, many enterprises will hit their maximum capacity, forcing either a “one in, one out” mindset to their enterprise security tool sets or consolidating to more comprehensive integrated solutions that bring together data protection, data governance, and data security capabilities.
  • For every organisation that makes the jump to the cloud, another will develop an on-premises data centre as hybrid cloud equilibrium sets in: Data storage in the cloud has grown to 57%, with 43% remaining on-premises. This increase is due to both established companies transitioning to the cloud and new companies using cloud-based infrastructure from the start. IDC notes that 70-80% of companies annually repatriate some data from the cloud, driven by concerns over data security, scalability, and data sovereignty regulations.

    Consequently, many companies are integrating on-premises solutions with their cloud infrastructure, leading to a balance in 2024: for every organisation moving to the cloud, another will develop an on-premises data centre.

– Andy Ng, Vice President and Managing Director for Asia South and Pacific Region, Veritas Technologies


  • The shift to data fabric will accelerate thanks to AI. When I surveyed the landscape at the end of last year, I anticipated more organisations would move from a data mesh approach to a data fabric; this would help flatten information silos and make data more readily available to business users. While the transition has been gradual, this trend is certainly gaining momentum. In 2024, this shift will be driven largely by the increased adoption of AI and other self-discovering technologies. Data fabric, a long-discussed topic, will become a larger goal for organisations with the advancement of AI.
  • Data quality will become an executive-level topic. Although data ownership and quality are critical for business success, executives and boards often overlook this. A recent survey of executives highlighted a discrepancy between perception and reality. Over 80% of executives surveyed believe they trust their data, but improving data quality to a usable level requires significant effort. As data quality becomes more crucial, it will rise to an executive-level discussion.

– Rex Ahlstrom, Chief Technology Officer, Syniti


  • Critical role of storage in AI: Effective AI deployment depends on data availability for training and inference. The shortage of GPUs in public clouds highlights the need for efficient data storage and management, especially with rising regulations.
  • AI in enhancing data privacy and compliance: AI will play a significant role in data privacy, using techniques like anonymization, encryption, and privacy-preserving machine learning. AI can classify sensitive data and enforce privacy frameworks in real time, aiding in compliance with regulations like the “right to be forgotten.”

– Jonathon Dixon, Vice President and Managing Director, APJC, Cloudflare


Data governance and collaboration will be key to AI regulation

This year, we have seen an exponential growth in organisations across APAC adopting generative AI and large language models (LLMs). While this has brought immense potential and opportunity, the speed at which AI evolves has made it challenging for regulatory frameworks to keep up. Increasingly, governments in Singapore and across the region are turning their attention towards AI regulatory frameworks and standards to govern both its use and the data that powers it.

In this climate, it is crucial for CTOs and CDOs to consider how they can build more reliable and competent AI models. As the cornerstone of AI, data will be the field in which these efforts play out. Data streaming, where data is continually processed and analysed in real-time to ensure its validity, is a straightforward way to address this challenge. End-to-end encryption and granular access controls in data streaming help establish the necessary governance frameworks and trustworthy data lineage for innovation in AI to continue.

Yet the same cannot be said for complexities around data sovereignty. In fact, companies are likely to focus more on such complexities in the year ahead. Accessible data often does not belong to a single country, and it is a growing challenge to set the right parameters that limit and govern how AI interacts with each other.

Looking ahead to 2024, the element of real-time data will remain materially important, especially in providing the latest context. To address the critical questions posed by AI, it is paramount that both governments and enterprises collaborate towards a holistic approach, and find the right balance between risk appetite and potential AI innovation.

– Kamal Brar, Senior Vice President APAC & Japan, Confluent


Emerging technologies like generative AI have significantly intensified the explosion of data. In APAC, six out of 10 companies in Asia are overwhelmed by the amount of data they manage and the majority of business leaders also expect data storage needs to double by 2025, according to Hitachi Vantara’s Data Infrastructure report. In addition, the surge of sprawled environments creating siloed data is exacerbating the strain on existing infrastructure, with 73% of surveyed business leaders in APAC expressing concerns that their current infrastructure will be unable to scale to meet impending demands, leaving them exposed to security and sustainability challenges.

Today’s enterprises recognise the importance of managing data across storage environments and minimising compromise and complexity to remain competitive. In 2024, we anticipate a major architectural overhaul – a unified data ecosystem that allows seamless integration into existing infrastructure to address all environments with simplicity and scale across diverse applications. One data platform to manage all applications will enable complete visibility and interoperability of enterprise data to unlock deeper insights faster and respond to market needs quickly.

– Joe Ong, Vice President and General Manager, ASEAN, Hitachi Vantara

Data centres

In 2023, AI went mainstream – 2024 will see AI completely transform the way we live and work. AI’s impact will increase exponentially as businesses begin to embed multi-modal generative AI tools. AI workloads will become more demanding, and there will be a greater need for the infrastructure that houses these applications and enables their smooth operation — data centres. They will have to flex to respond to these changing demands — being agile, adaptable, and providing customers with options that allow them to scale or shift direction to make the most of the opportunities AI offers, will be critical.

– Chris Sharp, Chief Technology Officer, Digital Realty

Digital transformation

We monitor major trends for the coming year, conceptualising them as a set of pressure gauges with readings indicating the level of intensity of the impact across industries. In Singapore, the ageing workforce will be the focus for 2024, with the population aged 65 and above expected to surpass 21% and the country set to attain the “super-aged” status in 2026. The answer to navigating past this challenge lies in a strategy that drives resilience, agility, and adaptiveness.

Most companies are entrenched in the early stages of their digital transformation journey. While improvements in the traceability and accessibility of data across the organisation are applaudable, they are insufficient in addressing the pressures coming in the new year. They must progress in their digital transformation maturity to do more than unlock the company’s data, employing advanced technologies like AI to support the automation of tasks and optimise the production process to address the gaps in the workforce.

– Alex Teo, Vice President & Managing Director of Southeast Asia, Siemens Digital Industries Software


Businesses will become more human-centric to curb digital transformation waste.

In 2024, businesses will realise that digital investments need to be human-centric, or they will fail. In recent years some businesses have been ‘keeping up with the Joneses’: digitally transforming because everybody else is, without fully considering the impact on employees. This has led to businesses spending millions on new tech without fully realising the benefits they were expecting. 

That kind of tech-driven waste will become a thing of the past as we move into the new year, with businesses now focusing less on the technology itself, and more on the people it serves. In 2024, we will see IT teams putting a focus on consolidation, automation, and AI to make technologies more efficient for employees and to make them part of a more holistic approach. It goes without saying that the technology matters — apps need to work and operating systems need to be secure — but if employees do not use their software and unlock the intended benefits, then businesses have failed. This means ‘digital adoption’ is becoming an increasingly important piece of the puzzle. 

Businesses will place more of a priority on making sure the tech stack makes sense from an employee’s point of view. They will find a more intuitive approach, helping workers carry out their duties without needing a drawer full of instruction manuals on how hundreds of different pieces of software work and without spending endless hours in training sessions learning how to use tools that will never be relevant to their role. Becoming more human-centric will enable employees to get on with the task at hand and, ultimately, drive productivity across the business.

– Uzi Dvir, Chief Information Officer, WalkMe


People as the core of digital transformation: With ongoing digitisation in ASEAN, the tech talent shortage presents challenges and opportunities. Skills-to-job programs aim to bridge this gap by training millions in digital skills. Companies need to cultivate a purpose-driven culture to foster stakeholder support and adaptability in a dynamic world.

– Bee Kheng Tay, President, Cisco ASEAN


AI will catalyse rapid innovation in conversational interfaces, specifically chatbots. The advancement of AI will propel chatbots beyond script-based, morphing them into intelligent conversational agents. Chatbot performance will soon be measured by their ability to comprehend natural language, their awareness of context, and their capacity to tailor user experiences.

Further, embedded AI will emerge as a cornerstone in software development. What was once considered a box-ticking exercise to keep up with competitors will evolve into a core component of product value. Businesses will be pressed to integrate AI not just to stay on trend, but to address concrete challenges and enhance user experiences.

This integration will spur an era of frictionless user experiences as consumer expectations align with the potential of AI to deliver streamlined, intuitive interfaces. That being said, as AI shoulders more organisational responsibilities, the ethical implications will move to the forefront of corporate governance. Ethical oversight of AI will evolve from a specialised focus to a broad-based imperative across industries, emphasising transparency, fairness and accountability.

Content personalisation is also undergoing a significant transformation on the horizon. We will witness a shift from static, demographic-based targeting to dynamic content strategies that adapt in real-time to the context of each user. This will demand more agile content management workflows capable of keeping pace with the instantaneous nature of user interactions.

In 2024, regulatory considerations will heavily influence the technological landscape, particularly around customer data. With global data privacy regulations becoming more stringent, Customer Data Platforms (CDPs) will emerge as critical business tools. Companies that offer CDPs with robust compliance frameworks will not only navigate the regulatory maze with ease but will also turn their ability to adhere to these regulations into a competitive edge.

The persistence of remote work will continue to blur the boundaries between digital and physical realms in the coming year. Businesses must revisit and revise their customer journey mappings, incorporating innovative forms of digital engagement that can effectively supplement—or even replace—traditional physical touchpoints.

Lastly, edge computing will be the definitive facilitator in delivering hyper-personalised content and enabling real-time, seamless experiences. This will be driven by the decentralised processing of data—reducing latency and costs—and by integrating machine learning models to enhance the responsiveness and personalisation of user interactions.

– Jay Sanderson, Senior Product Marketing Manager for Digital Experience at Progress


2024: Transforming operations, training, and customer support via IT-OT convergence

In 2024, Asia-Pacific’s industrial landscape is poised for a transformative shift. The IDC FutureScape: Worldwide IT/OT Convergence 2021 Predictions – Asia Pacific (excluding Japan) forecasts that by 2024, half of the region’s industrial players will integrate edge OT data with cloud analytics, achieving comprehensive operational awareness. This trend, propelled by increased manufacturing spending, is creating a divide between businesses integrating OT into their IT systems and those that are not, impacting both employee and customer experiences.

This convergence will revolutionise aftersales support and training. Merging IT and OT systems will enhance operational quality and productivity, with augmented reality (AR) software providing visual assistance. This synergy is expected to extend enterprise adoption, particularly in digital-twin and AR use cases, improving efficiency in sectors like warehouses, logistics, and retail.

The narrative shifts focus to the broader impacts of AI beyond generative models like ChatGPT. The real business value lies in automation and AI analytics, particularly at the edge, where AI transcends traditional data collection roles. Implementing AI responsibly, focusing on business process efficiencies, will support the workforce in becoming more productive and accurate, overcoming the skills shortage challenge.

The transition from traditional factories to tech-savvy environments is another key trend. The growth in smart factories will predominantly stem from existing factories adapting innovative technologies. Emphasising operational data and analytics, these factories will develop smart capabilities, with AR increasingly used for staff training and on-site problem-solving. The trend towards understanding shop floor processes and utilising operational data is crucial in converting traditional factories into smart factories.

– Mei Dent, Chief Product and Technology Officer, TeamViewer


IT spending: Focused on business outcomes

Businesses are now aligning IT spending with specific business outcomes. They seek operational flexibility, predictable cash flows, and direct support for business goals. Consequently, investment is shifting from legacy infrastructure to next-generation technology, fostering a move towards hybrid cloud environments and personalised tech solutions.

– Linda Yao, Chief Operating Officer and Head of Strategy, Lenovo Solutions & Services Group


The 2024 Southeast Asian business landscape is poised for unprecedented innovation, driven by enthusiasm for accessible and secure AI-infused decision-making technology. IDC predicts that by 2026, tech providers will allocate half of R&D, staffing, and investments to AI and automation. In Singapore, business leaders acknowledge that AI is already significantly impacting what their organisations can achieve, and many are planning to invest in these advanced technologies to respond to the changing market environment.

As organisations across Singapore continue to lay the foundations for successfully harnessing large language models (LLMs) to deliver business value, this vision has also reignited digital transformation strategies. Forrester predicts that 30% of firms in the Asia-Pacific region will experience a significant transformation due to generative AI. As LLM usage becomes more pervasive across the business, it accentuates the imperative for data-centric infrastructures, necessitating substantial investments in robust data management systems. Forward-thinking IT leaders see a direct correlation between facilitating value extraction from data at the speed and scale needed for real-time intelligence and AI-ready transformation.

While technology is set to shape how future enterprises operate and perform, preparing for this increasingly complex, data-driven future requires a focus on skill transformation within the workforce. Beyond technology, people remain key to the success of digital transformation. As we move into 2024 and beyond, embracing upskilling in data analytics and machine learning emerges as the catalyst for driving the path towards sustained business growth and success. Therefore, the organisations that will flourish are those that have nurtured and equipped their domain experts with essential critical thinking, domain knowledge, data literacy, and analytical skills to navigate this era of AI-driven intelligence.

– Philip Madgwick, Senior Director, Asia, Alteryx


As we approach 2024, businesses in the Asia-Pacific region are embracing a wave of optimism despite uncertain economic conditions. Key factors such as a burgeoning digital economy and the rapid advancement in technologies like AI are setting the stage for significant transformation. There’s a shift from mere hype to actual implementation of technology, propelling investments aimed at strengthening operations and enhancing business resilience.

Eric Wong, Head of Asia Pacific, Expereo, states: “As organisations in APAC look to expand their global footprint in the coming year, they must make a calculated and strategic shift towards building a more sustainable and resilient business. The growing digital economy is still lush with opportunity, but businesses must continue to invest in the three pillars of connectivity, technology, and people as key pillars of strategic advantage, or risk getting left behind.”

Expereo outlines three key trends underpinning this perspective:

Trend #1: Connectivity as the backbone of enterprise growth

Connectivity is evolving into a strategic business asset, particularly in APAC. Emerging technologies like low-Earth-orbit satellites are enhancing communication in challenging terrains, such as rural areas in Indonesia and the Philippines. This evolution supports more agile and scalable business operations, crucial for global market expansion. The growing markets in the region, including China and Singapore, are driving the demand for sophisticated digital infrastructure to support high-speed connectivity and AI applications.

Trend #2: AI’s transition from hype to reality

AI is transforming business operations and customer engagement. It’s also poised to play a significant role in employee retention and recruitment, addressing the talent crunch faced by many APAC companies. AI’s potential to drive personalised interactions and employee experiences marks its shift from a buzzword to a practical business tool.

Trend #3: Balancing sustainability and growth

Businesses are increasingly pressured to align their sustainability goals with growth strategies. The computational demands of training and running AI models pose environmental and ethical challenges. As AI integration becomes more prevalent, addressing its environmental impact is imperative for businesses.

– Expereo


Trend #1: AI delivering a golden opportunity for ASEAN businesses to leapfrog

Amidst geopolitical tensions in other parts of the world, ASEAN has emerged as a favourable business destination. Global enterprises such as Hyundai and Procter & Gamble are investing in the region, with new factories and R&D centres. With advancements in AI, ASEAN businesses face a significant opportunity to leapfrog and elevate themselves to a global stage, particularly as AI is projected to contribute SG$1.36 trillion to the ASEAN economy by 2030. ASEAN countries have made steady progress in preparation for AI adoption – Singapore currently leads the APAC region in overall AI readiness, while Thailand and Indonesia recorded one of the largest improvements in government AI readiness. New AI policy initiatives, such as the ASEAN Guide on AI Governance and Ethics, and Singapore’s IMDA AI Verify Foundation, will serve as a guiding light for their respective countries to deploy responsible and innovative AI.

Businesses will need access to trusted technology, AI training and guard rails for responsible AI adoption. Done right, businesses can harness the full potential of AI supercharge growth in the region.

Trend #2: A new era for customer engagement: everything, everywhere, all at once

Customer expectations are increasing and competition is fiercer than ever. Leveraging innovations across AI, data, and CRM will give businesses a better understanding of their customers, and enable the delivery of personalised experiences. New services, revenue channels, and pathways for customer engagement can also come to life. This builds stronger customer relationships, loyalty, and retention.

As digital adoption accelerates, we’re also seeing greater demand for industry-specific solutions. For example, banks are introducing digital solutions such as mobile banking apps and digital payments to cater to tech-savvy customers. Many are innovating on financial products to meet the needs of different customer segments. Banking-specific solutions can help deepen customer engagement and build customer loyalty, giving banks a better idea of who their customers are, what financial products they use, and what more they might need.

Trend #3: Trusted data sharing will supercharge ASEAN economies

The launch of negotiations for a new ASEAN Digital Economy Framework Agreement in September marks a milestone for facilitating seamless and secure data flows across ASEAN member states. With negotiations set to conclude by 2025, the next two years will be a window of opportunity for ASEAN to realise its ambitions for digital integration and write its own rules for data governance.

Having a framework that makes trusted data sharing the default without jeopardising data sovereignty will help enhance competitiveness in the region, and unlock ASEAN’s next phase of growth.

– Sujith Abraham, Senior Vice President and General Manager, ASEAN for Salesforce

Future of work

Career impact of AI tool selection for developers: Front-end developers need to adapt in the AI era, where AI’s proficiency in code generation challenges traditional roles. The choice of development tools and frameworks will significantly influence career paths and the job market. (Future of work)

– Jonathon Dixon, Vice President and Managing Director, APJC, Cloudflare


Driving industry and workplace transformation with AI

In 2024, AI will continue to transform the workplace, how organisations deliver customer experiences and transform industries.

In the workplace, purposeful work is not just what employees work on, but how they work. Finding the right balance between motivation and productivity necessitates strategic, AI-powered solutions that help employees be more productive. Automating tasks like note-taking and meeting summaries can help trim time on time-intensive activities, streamlining workflows. Employees can then spend time collaborating with their teams and driving more effective communication with customers. Keeping employees engaged, informed, and connected with the right technology that supports inclusivity, equity and meaningful connection is the linchpin of modern collaboration.

We will also continue to see a platform-first approach that enables the smooth transition between channels, be it video, voice, or chatbots. This will help organisations boost customer experience in a cost-effective way to help deliver better business outcomes and drive industry transformation. Driven by AI, sales tools to help forecast, track, and analyse work performance allows employees who engage with customers – from sales teams to customer service, to focus on delivering excellent service to drive customer loyalty.

As more organisations evaluate which AI solutions they need, they must remember that more is not always better. They should start with AI capabilities that will have the most impact on daily activities. The benefits of AI should also be available to all employees without having to pay a premium price tag or have a minimum number of subscriptions. Lastly, a quick rollout of such solutions is essential to gain a competitive advantage.

2024 will be the year of balancing AI innovation and human connection.

– Ricky Kapur, Head of Asia Pacific, Zoom


The developer community in Singapore is among the fastest-growing in the world, experiencing a 39% year-over-year increase in developers building on GitHub, as highlighted in our 2023 State of the Octoverse report. If this growth continues — coupled with the ascent of AI-powered developer tools like GitHub Copilot — Singapore’s developers could significantly boost the national economy. In fact, our own research found that AI developer tools could boost global GDP by US$1.5 trillion. This trajectory will not only propel Singapore toward smart nation excellence but also solidify its position as a leading digital hub. By empowering its thriving developer community to build at a pace 55% faster and beyond with generative AI tools, Singapore is set to supercharge its digital economy in 2024.

Our Octoverse report also found that, despite its relatively small population, Singapore continues to punch above its weight, with its developer community ranking tenth globally in contributions to generative AI projects on GitHub. Developers in Singapore are clearly positioning the nation for substantial longer-term gains, enabling Singapore to stand tall among global giants in the age of AI. Looking ahead to 2024, this indicates that we’ll witness Singapore gearing up to become a powerhouse in AI, creating social and economic impact. Singapore’s National AI Strategy 2.0 is already setting the stage for success with plans to triple the number of AI practitioners in the country to 15,000 to meet growing AI demands.

– Pierluigi Cau, Regional Director, Field Services APAC at GitHub


2024 will see another talent crunch, this time focused on AI: Whenever new technologies emerge, we see demands for talent and skills in those areas shoot up and it’s no different with generative AI. The war for talent will cause salaries to rise and we will also see many AI projects stall because of the talent crunch.

  • Besides generative AI, the talent crunch will also persist in hot areas such as cloud computing, Kubernetes, data architecture, and cybersecurity.
  • This war for talent will be waged even in traditionally less tech-driven industries such as agriculture, forestry, and fishing as they shift towards data analytics.  Professionals skilled in IoT, data analytics, AI, and environmental technology will be highly sought after in these industries.
  • This will become one of the biggest headwinds for the broad adoption of AI.

– Pure Storage


Rise of tech-savvy executives

As technology becomes central to business strategies, more CIOs are likely to ascend to CEO roles. A deeper understanding of tech, including AI, is becoming essential for all executives. This trend indicates a future where all leadership roles will require a significant degree of digital and technological fluency.

– Linda Yao, Chief Operating Officer and Head of Strategy, Lenovo Solutions & Services Group


Intuitive network infrastructure: To effectively utilise AI, businesses must focus on their digital infrastructure. Building a modern and intelligent network is key for integrating AI workloads. Companies will recognize the importance of integrated security platforms for comprehensive organisational visibility, crucial for detecting and mitigating security threats in a complex cyber environment.

– Bee Kheng Tay, President, Cisco ASEAN

Supply chain management

  • Supply chain orchestration: The traditional supply chain, once rooted in physical goods, now incorporates digital assets and services. This shift, coupled with the historical environmental impact of material extraction, mandates a synchronised strategy – supply chain orchestration. This modern approach aligns with corporate goals, emphasising sustainability and financial success.
  • Circular supply chains and digital shift: A shift towards circular supply chain models is required, in combination with a surge in digital assets and services. This integration necessitates evolved capabilities, and a refresh of the traditional Integrated Business Planning (IBP) process, considering physical and digital products and sustainability. Supply chain professionals are increasingly intertwined with finance, steering towards delivering holistic top and bottom-line performance.
  • Sustainable practices: With scientific evidence emphasising environmental accountability, supply chain management is pivoting towards efficiency and waste reduction. Circular supply chain models, adopting trends like leasing and emphasising reuse, are gaining prominence. Technology, including data from embedded sensors, plays a pivotal role in enhancing supply chain planning accuracy and reducing costs.
  • AI and machine learning revolution: As we head into 2024, the supply chain industry is witnessing the transformative power of AI and machine learning. These technologies not only automate repetitive tasks but also provide unprecedented insights, making supply chains more resilient, sustainable, and efficient. Despite this automation, human intelligence remains indispensable for complex decision-making and strategic partnerships.
  • Transition phase and opportunity: Supply chain professionals find themselves at a critical juncture in 2024. Tools and techniques of the past three decades are insufficient for the evolving landscape. The scope of supply chain management expands to include physical, digital, and financial assets. Supply chains are steering a revolution towards efficiency, utilising fewer resources and championing a circular economy. The integration of technology and greater transparency is making supply chains more resilient and sustainable.

– Matt Spooner, Industry Thought Leader, Kinaxis


Intensifying supply chain issues with AI: AI proliferation will exacerbate supply chain challenges. Businesses must focus on software optimizations and develop more task-focused AI models to manage computational demands.

– Jonathon Dixon, Vice President and Managing Director, APJC, Cloudflare