Author: Tim Sheedy

At the Nutanix .NEXT 2024 event in Barcelona, it became clear that the discourse around cloud computing has evolved significantly. The debate that once polarised organisations over whether on-prem/co-located data centres or public cloud was better has been decisively settled. Both cloud providers and on-prem equipment providers are thriving, as evident from their earnings reports. 

Hybrid cloud has emerged as the clear victor, offering the flexibility and control that organisations demand. This shift is particularly relevant for tech buyers in the Asia Pacific region, where diverse market maturities and unique business challenges require a more adaptable approach to IT infrastructure. 

The Hybrid Cloud Advantage 

Hybrid cloud architecture combines the best of both worlds. It provides the scalability and agility of public cloud services while retaining the control and security of on-prem systems. For Asia Pacific organisations, that often operate across various regulatory environments and face unique data sovereignty issues, this dual capability is invaluable. The ability to seamlessly move workloads between on-prem, private cloud, and public cloud environments enables enterprises to optimise their IT strategies, balancing cost, performance, and compliance. 

Market Maturity and Adoption in Asia Pacific 

The region shows a wide spectrum of technological maturity among its markets. Countries like Australia, Japan, and Singapore lead with advanced cloud adoption and robust IT infrastructures, while emerging markets such as Vietnam, Indonesia, and the Philippines are still in the nascent stages of cloud integration. 

However, regardless of their current maturity levels, organisations in Asia Pacific are recognising the benefits of a hybrid cloud approach. Mature markets are leveraging hybrid cloud to refine their IT strategies, focusing on enhancing business agility and driving innovation. 

Ecosystm research shows that 75% of organisations in Australia have a hybrid, multi-cloud strategy. Over 30% of organisations have repatriated workloads from the public cloud, and only 22% employ a “cloud first” strategy when deploying new services.  

Meanwhile, emerging markets see hybrid cloud as a pathway to accelerate their digital transformation journeys without the need for extensive upfront investments in on-prem infrastructure. Again, Ecosystm data shows that when it comes to training large AI models and applications, organisations across Southeast Asia use a mix of public, private, hybrid, and multi-cloud environments. 

Strategic Flexibility Without Compromise 

One of the most compelling messages from the Nutanix .NEXT 2024 event is that hybrid cloud eliminates the need for compromise when deciding where to place workloads – and that is what the data above represents. The location of the workload is no longer a limiting factor. Being “cloud first” locks organisations into a tech provider, whereas agility was once exclusively in favour of public cloud providers. Whether it’s for performance optimisation, cost efficiency, or regulatory compliance, tech leaders can now choose the best environment for every workload without being constrained by location. 

For example, an organisation might keep sensitive customer data within a private cloud to comply with local data protection laws while leveraging public cloud resources for less sensitive applications to take advantage of its scalability and cost benefits. I recently spoke to an organisation in the gaming space that had 5 different regulatory bodies to appease – which required data to be stored in 5 different locations! This strategic flexibility ensures that IT investments are fully aligned with business objectives, enhancing overall operational efficiency. 

Moving Forward: Actionable Insights for Asia Pacific Tech Leaders 

To fully capitalise on the hybrid cloud revolution, APAC tech leaders should: 

1. Assess Workload Requirements. Evaluate the specific needs of each workload to determine the optimal environment, considering factors like latency, security, and compliance. 
2. Invest in Integration Tools. Ensure seamless interoperability between on-premises and cloud environments by investing in advanced integration and management tools. 
3. Focus on Skill Development. Equip IT teams with the necessary skills to manage hybrid cloud infrastructures, emphasising continuous learning and certification. 
4. Embrace a Multi-Cloud Strategy. Consider a multi-cloud approach within the hybrid model to avoid vendor lock-in and enhance resilience. 

Conclusion 

The hybrid cloud has definitively won the battle for enterprise IT infrastructure, particularly in the diverse Asia Pacific region. By enabling organisations to place their workloads wherever they make the most sense without compromising on performance, security, or compliance, hybrid cloud empowers tech leaders to drive their digital transformation agendas forward with confidence. Based on everything we know today*, the future of cloud is hybrid. Reform your sourcing practices to put business needs, not cloud service providers or data centres, at the centre of your data decisions. 

*In this fast-changing world, it seems naïve to make sweeping statements about the future of technology! 

In my earlier post this week, I referred to the need for a grown-up conversation on AI. Here, I will focus on what conversations we need to have and what the solutions to AI disruption might be. 

The Impact of AI on Individuals 

AI is likely to impact people a lot! You might lose your job to AI. Even if it is not that extreme, it’s likely AI will do a lot of your job. And it might not be the “boring bits” – and sometimes the boring bits make a job manageable! IT helpdesk professionals, for instance, are already reporting that AIOps means they only deal with the difficult challenges. While that might be fun to start with, some personality types find this draining, knowing that every problem that ends up in the queue might take hours or days to resolve. 

Your job will change. You will need new skills. Many organisations don’t invest in their employees, so you’ll need to upskill yourself in your own time and at your own cost. Look for employers who put new skill acquisition at the core of their employee offering. They are likelier to be more successful in the medium-to-long term and will also be the better employers with a happier workforce.  

The Impact of AI on Organisations 

Again – the impact on organisations will be huge. It will change the shape and size of organisations. We have already seen the impact in many industries.  The legal sector is a major example where AI can do much of the job of a paralegal. Even in the IT helpdesk example shared earlier, where organisations with a mature tech environment will employ higher skilled professionals in most roles. These sectors need to think where their next generation of senior employees will come from, if junior roles go to AI. Software developers and coders are seeing greater demand for their skills now, even as AI tools increasingly augment their work. However, these skills are at an inflection point, as solutions like TuringBots have already started performing developer roles and are likely to take over the job of many developers and even designers in the near future. 

Some industries will find that AI helps junior roles act more like senior employees, while others will use AI to perform the junior roles. AI will also create new roles (such as “prompt engineers”), but even those jobs will be done by AI in the future (and we are starting to see that).  

HR teams, senior leadership, and investors need to work together to understand what the future might look like for their organisations. They need to start planning today for that future. Hint: invest in skills development and acquisition – that’s what will help you to succeed in the future. 

The Impact of AI on the Economy 

Assuming the individual and organisational impacts play out as described, the economic impacts of widespread AI adoption will be significant, similar to the “Great Depression”. If organisations lay off 30% of their employees, that means 30% of the economy is impacted, potentially leading to drying up of some government and an increase in government spend on welfare etc. – basically leading to major societal disruption.  

The “AI won’t displace workers” narrative strikes me as the technological equivalent of climate change denial. Just like ignoring environmental warnings, dismissing the potential for AI to significantly impact the workforce is a recipe for disaster. Let’s not fall into the same trap and be an “AI denier”.  

What is the Solution?  

The solutions revolve around two ideas, and these need to be adopted at an industry level and driven by governments, unions, and businesses: 

• Pay a living salary (for all citizens). Some countries already do this, with the Nordic nations leading the charge.  And it is no surprise that some of these countries have had the most consistent long-term economic growth. The challenge today is that many governments cannot afford this – and it will become even less affordable as unemployment grows. The solution? Changing tax structures, taxing organisational earnings in-country (to stop them recognising local earnings in low-tax locations), and taxing wealth (not incomes).  Also, paying essential workers who will not be replaced by AI (nurses, police, teachers etc.) better salaries will also help keep economies afloat. Easier said than done, of course! 

• Move to a shorter work week (but pay full salaries). It is in the economic interest of every organisation that people stay gainfully employed. We have already discussed the ripple effect of job cuts. But if employees are given more flexibility, and working 3-day weeks, this not only spreads the work around more workers, but means that these workers have more time to spend money – ensuring continuing economic growth. Can every company do this? Probably not. But many can and they might have to. The concept of a 5-day work week isn’t that old (less than 100 years in fact – a 40-hour work week was only legislated in the US in the 1930s, and many companies had as little as 6-hour working days even in the 1950s). Just because we have worked this way for 80 years doesn’t mean that we will always have to. There is already a move towards 4-day work weeks. Tech.co surveyed over 1,000 US business leaders and found that 29% of companies with 4-day workweeks use AI extensively. In contrast, only 8% of organisations with a 5-day workweek use AI to the same degree. 

AI Changes Everything 

We are only at the beginning of the AI era. We have had a glimpse into the future, and it is both frightening and exciting. The opportunities for organisations to benefit from AI are already significant and will become even more as the technology improves and businesses learn to better adopt AI in areas where it can make an impact. But there will be consequences to this adoption. We already know what many of those consequences will be, so let’s start having those grown-up conversations today. 

The issue is that very few senior people in businesses or governments are planning for a future where maybe 30% of jobs done by knowledge workers go to AI. This could lead to the failure of economies. Government income will fall off a cliff. It will be unemployment on levels not seen since the great depression – or worse. And if we have not acknowledged these possible outcomes, how can we plan for it?

This is what I call the “grown up conversation about AI”. This is acknowledging the opportunity for AI and its impacts on companies, industries, governments and societies. Once we acknowledge these likely outcomes we can plan for it.

And that’s what I’ll discuss shortly – look out for my next Ecosystm Insight: The Three Possible Solutions for AI-driven Mass Unemployment.

However, legacy modernisation and migration initiatives carry significant risks.  For instance, TSB faced a USD 62M fine due to a failed mainframe migration, resulting in severe disruptions to branch operations and core banking functions like telephone, online, and mobile banking. The migration failure led to 225,492 complaints between 2018 and 2019, affecting all 550 branches and required TSB to pay more than USD 25M to customers through a redress program.

Modernisation Options

• Rip and Replace. Replacing the entire legacy system with a modern, cloud-based solution. While offering a clean slate and faster time to value, it’s expensive, disruptive, and carries migration risks.
• Refactoring. Rewriting key components of the legacy system with modern languages and architectures. It’s less disruptive than rip-and-replace but requires skilled developers and can still be time-consuming.
• Encapsulation. Wrapping the legacy system with a modern API layer, allowing integration with newer applications and tools. It’s quicker and cheaper than other options but doesn’t fully address underlying limitations.
• Microservices-based Modernisation. Breaking down the legacy system into smaller, independent services that can be individually modernised over time. It offers flexibility and agility but requires careful planning and execution.

Financial Systems on the Block for Legacy Modernisation

Data Analytics Platforms. Harnessing customer data for insights and targeted offerings is vital. Legacy data warehouses often struggle with real-time data processing and advanced analytics.

CRM Systems. Effective customer interactions require integrated CRM platforms. Outdated systems might hinder communication, personalisation, and cross-selling opportunities.

Payment Processing Systems. Legacy systems might lack support for real-time secure transactions, mobile payments, and cross-border transactions.

Core Banking Systems (CBS). The central nervous system of any bank, handling account management, transactions, and loan processing. Many Asia Pacific banks rely on aging, monolithic CBS with limited digital capabilities.

Digital Banking Platforms. While several Asia Pacific banks provide basic online banking, genuine digital transformation requires mobile-first apps with features such as instant payments, personalised financial management tools, and seamless third-party service integration.

Modernising Technical Approaches and Architectures

Numerous technical factors need to be addressed during modernisation, with decisions needing to be made upfront. Questions around data migration, testing and QA, change management, data security and development methodology (agile, waterfall or hybrid) need consideration.

Best practices in legacy migration have taught some lessons.

Adopt a data fabric platform. Many organisations find that centralising all data into a single warehouse or platform rarely justifies the time and effort invested. Businesses continually generate new data, adding sources, and updating systems. Managing data where it resides might seem complex initially. However, in the mid to longer term, this approach offers clearer benefits as it reduces the likelihood of data discrepancies, obsolescence, and governance challenges.

Focus modernisation on the customer metrics and journeys that matter. Legacy modernisation need not be an all-or-nothing initiative. While systems like mainframes may require complete replacement, even some mainframe-based software can be partially modernised to enable services for external applications and processes. Assess the potential of modernising components of existing systems rather than opting for a complete overhaul of legacy applications.

Embrace the cloud and SaaS. With the growing network of hyperscaler cloud locations and data centres, there’s likely to be a solution that enables organisations to operate in the cloud while meeting data residency requirements. Even if not available now, it could align with the timeline of a multi-year legacy modernisation project. Whenever feasible, prioritise SaaS over cloud-hosted applications to streamline management, reduce overhead, and mitigate risk.

Build for customisation for local and regional needs. Many legacy applications are highly customised, leading to inflexibility, high management costs, and complexity in integration. Today, software providers advocate minimising configuration and customisation, opting for “out-of-the-box” solutions with room for localisation. The operations in different countries may require reconfiguration due to varying regulations and competitive pressures. Architecting applications to isolate these configurations simplifies system management, facilitating continuous improvement as new services are introduced by platform providers or ISV partners.

Explore the opportunity for emerging technologies. Emerging technologies, notably AI, can significantly enhance the speed and value of new systems. In the near future, AI will automate much of the work in data migration and systems integration, reducing the need for human involvement. When humans are required, low-code or no-code tools can expedite development. Private 5G services may eliminate the need for new network builds in branches or offices. AIOps and Observability can improve system uptime at lower costs. Considering these capabilities in platform decisions and understanding the ecosystem of partners and providers can accelerate modernisation journeys and deliver value faster.

Don’t Let Analysis Paralysis Slow Down Your Journey!

Yes, there are a lot of decisions that need to be made; and yes, there is much at stake if things go wrong! However, there’s a greater risk in not taking action. Maintaining a laser-focus on the customer and business outcomes that need to be achieved will help align many decisions. Keeping the customer experience as the guiding light ensures organisations are always moving in the right direction.

• Organisations are seeking further cost reductions. Managed services providers will see more opportunities to take cost and complexity out of organisation’s IT functions. The focus in 2024 will be less on “managing” services and more on “transforming” them using ML, AI, and automation to reduce cost and improve value.
• Big app upgrades are back on the agenda. SAP is going above and beyond to incentivise their customers and partners to migrate their on-premises and hyperscale hosted instances to true cloud ERP. Initiatives such as Rise with SAP have been further expanded and improved to accelerate the transition. Salesforce customers are also looking to streamline their deployments while also taking advantage of the new AI and data capabilities. But many of these projects will still be complex and time-consuming.
• Cloud deployments are getting more complex. For many organisations, the simple cloud migrations are done. This is the stage of replatforming, retiring, and refactoring applications to take advantage of public and hybrid cloud capabilities. These are not simple lift and shift – or switch to SaaS – engagements.  
• AI will drive a greater need for process improvement and transformation. This will happen along with associated change management and training programs. While it is still early days for GenAI, before the end of 2024, many organisations will move beyond experimentation to department or enterprise wide GenAI initiatives.
• Increasing cybersecurity and data governance demands will prolong the security skill shortage. More organisations will turn to managed security services providers and cybersecurity consultants to help them develop their strategy and response to the rising threat levels.

Choosing the Right Cost Model for IT Services

Buyers of IT services must implement strict cost-control measures and consider various approaches to align costs with business and customer outcomes, including different cost models:

Fixed-Price Contracts. These contracts set a firm price for the entire project or specific deliverables. Ideal when project scope is clear, they offer budget certainty upfront but demand detailed specifications, potentially leading to higher initial quotes due to the provider assuming more risk.

Time and Materials (T&M) Contracts with Caps. Payment is based on actual time and materials used, with negotiated caps to prevent budget overruns. Combining flexibility with cost predictability, this model offers some control over total expenses.

Performance-Based Pricing. Fees are tied to service provider performance, incentivising achievement of specific KPIs or milestones. This aligns provider interests with client goals, potentially resulting in cost savings and improved service quality.

Retainer Agreements with Scope Limits. Recurring fees are paid for ongoing services, with defined limits on work scope or hours within a given period. This arrangement ensures resource availability while containing expenses, particularly suitable for ongoing support services.

Other Strategies for Cost Efficiency and Effective Management

Technology leaders should also consider implementing some of the following strategies:

Phased Payments. Structuring payments in phases, tied to the completion of project milestones, helps manage cash flow and provides a financial incentive for the service provider to meet deadlines and deliverables. It also allows for regular financial reviews and adjustments if the project scope changes.

Cost Transparency and Itemisation. Detailed billing that itemises the costs of labour, materials, and other expenses provides transparency to verify charges, track spending against the budget, and identify areas for potential savings.

Volume Discounts and Negotiated Rates. Negotiating volume discounts or preferential rates for long-term or large-scale engagements, makes providers to offer reduced rates for a commitment to a certain volume of work or an extended contract duration.

Utilisation of Shared Services or Cloud Solutions. Opting for shared or cloud-based solutions where feasible, offers economies of scale and reduces the need for expensive, dedicated infrastructure and resources.

Regular Review and Adjustment. Conducting regular reviews of the services and expenses with the provider to ensure alignment with the budget and objectives, prepares organisations to adjust the scope, renegotiate terms, or implement cost-saving measures as needed.

Exit Strategy. Planning an exit strategy that include provisions for contract termination, transition services, protects an organisation in case the partnership needs to be dissolved.

Conclusion

Many businesses swing between insourcing and outsourcing technology capabilities – with the recent trend moving towards insourcing development and outsourcing infrastructure to the public cloud. But 2024 will see demand for all types of IT services across nearly every geography and industry. Tech services providers can bring significant value to your business – but improved management, monitoring, and governance will ensure that this value is delivered at a fair cost.

• ADVANCE.AI provides digital transformation, fraud prevention, and process automation solutions for enterprise clients. The company offers services in security and compliance, digital identity verification, and biometric solutions. They partner with over 1,000 enterprise clients across Southeast Asia and India across sectors, such as Banking, Fintech, Retail, and eCommerce. 
• Megvii is a technology company based in China that specialises in AI, particularly deep learning. The company offers full-stack solutions integrating algorithms, software, hardware, and AI-empowered IoT devices. Products include facial recognition software, image recognition, and deep learning technology for applications such as consumer IoT, city IoT, and supply chain IoT. 
• I’mCloud is based in South Korea and specialises in AI, big data, and cloud storage solutions. The company has become a significant player in the AI and big data industry in South Korea. They offer high-quality AI-powered chatbots, including for call centres and interactive educational services. 
• H2O.ai provides an AI platform, the H2O AI Cloud, to help businesses, government entities, non-profits, and academic institutions create, deploy, monitor, and share data models or AI applications for various use cases. The platform offers automated machine learning capabilities powered by H2O-3, H2O Hydrogen Torch, and Driverless AI, and is designed to help organisations work more efficiently on their AI projects. 
• Frame AI provides an AI-powered customer intelligence platform. The software analyses human interactions and uses AI to understand the driving factors of business outcomes within customer service. It aims to assist executives in making real-time decisions about the customer experience by combining data about customer interactions across various platforms, such as helpdesks, contact centres, and CRM transcripts. 
• Uizard offers a rapid, AI-powered UI design tool for designing wireframes, mockups, and prototypes in minutes. The company’s mission is to democratise design and empower non-designers to build digital, interactive products. Uizard’s AI features allow users to generate UI designs from text prompts, convert hand-drawn sketches into wireframes, and transform screenshots into editable designs. 
• Moveworks provides an AI platform that is designed to automate employee support. The platform helps employees to automate tasks, find information, query data, receive notifications, and create content across multiple business applications. 
• Tome develops a storytelling tool designed to reduce the time required for creating slides. The company’s online platform creates or emphasises points with narration or adds interactive embeds with live data or content from anywhere on the web, 3D renderings, and prototypes. 
• Jasper is an AI writing tool designed to assist in generating marketing copy, such as blog posts, product descriptions, company bios, ad copy, and social media captions. It offers features such as text and image AI generation, integration with Grammarly and other Chrome extensions, revision history, auto-save, document sharing, multi-user login, and a plagiarism checker. 
• Eightfold AI provides an AI-powered Talent Intelligence Platform to help organisations recruit, retain, and grow a diverse global workforce. The platform uses AI to match the right people to the right projects, based on their skills, potential, and learning ability, enabling organisations to make informed talent decisions. They also offer solutions for diversity, equity, and inclusion (DEI), skills intelligence, and governance, among others. 
• Arthur provides a centralised platform for model monitoring. The company’s platform is model and platform agnostic, and monitors machine learning models to ensure they deliver accurate, transparent, and fair results. They also offer services for explainability and bias mitigation. 
• DNSFilter is a cloud-based, AI-driven content filtering and threat protection service, that can be deployed and configured within minutes, requiring no software installation. 
• Spot AI specialises in building a modern AI Camera System to create safer workplaces and smarter operations for every organisation. The company’s AI Camera System combines cloud and edge computing to make video footage actionable, allowing customers to instantly surface and resolve problems. They offer intelligent video recorders, IP cameras, cloud dashboards, and advanced AI alerts to proactively deliver insights without the need to manually review video footage. 
• People.ai is an AI-powered revenue intelligence platform that helps customers win more revenue by providing sales, RevOps, marketing, enablement, and customer success teams with valuable insights. The company’s platform is designed to speed up complex enterprise sales cycles by engaging the right people in the right accounts, ultimately helping teams to sell more and faster with the same headcount.  

These examples highlight a few startups worth considering, but the landscape is rich with innovative options for organisations to explore. Similar to other emerging tech sectors, the AI startup market will undergo consolidation over time, and incumbent providers will continue to improve and innovate their own AI capabilities. Till then, these startups will continue to influence enterprise technology adoption and challenge established providers in the market.

Earlier in the year, Microsoft unveiled its vision for Copilot, a digital companion that aims to provide a unified user experience across Bing, Edge, Microsoft 365, and Windows. This vision includes a consistent user experience. The rollout began with Windows in September and expanded to Microsoft 365 Copilot for enterprise customers this month.

Many organisations across Asia Pacific will soon face the question on whether to invest in Microsoft 365 Copilot – despite its current limitations in supporting all regional languages. Copilot is currently supported in English (US, GB, AU, CA, IN), Japanese, and Chinese Simplified. Microsoft plans to support more languages such as Arabic, Chinese Traditional, Korean and Thai over the first half of 2024. There are still several languages used across Asia Pacific that will not be supported until at least the second half of 2024 or later.

Access to Microsoft 365 Copilot comes with certain prerequisites. Organisations need to have either a Microsoft 365 E3 or E5 license and an Azure Active Directory account. F3 licenses do not currently have access to 365 Copilot. For E3 license holders the cost per user for adding Copilot would nearly double – so it is a significant extra spend and will need to deliver measurable and tangible benefits and a strong business case. It is doubtful whether most organisations will be able to justify this extra spend.

However, Copilot has the potential to significantly enhance the productivity of knowledge workers, saving them many hours each week, with hundreds of use cases already emerging for different industries and user profiles. Microsoft is offering a plethora of information on how to best adopt, deploy, and use Copilot. The key focus when building a business case should revolve around how knowledge workers will use this extra time.

Maximising Copilot Integration: Steps to Drive Adoption and Enhance Productivity

Identifying use cases, building the business proposal, and securing funding for Copilot is only half the battle. Driving the change and ensuring all relevant employees use the new processes will be significantly harder. Consider how employees currently use their productivity tools compared to 15 years ago, with many still relying on the same features and capabilities in their Office suites as they did in earlier versions. In cases where new features were embraced, it typically occurred because knowledge workers didn’t have to make any additional efforts to incorporate them, such as the auto-type ahead functions in email or the seamless integration of Teams calls.

The ability of your organisation to seamlessly integrate Copilot into daily workflows, optimising productivity and efficiency while harnessing AI-generated data and insights for decision-making will be of paramount importance. It will be equally important to be watchful to mitigate potential risks associated with an over-reliance on AI without sufficient oversight.

Implementing Copilot will require some essential steps:

• Training and onboarding. Provide comprehensive training to employees on how to use Copilot’s features within Microsoft 365 applications.
• Integration into daily tasks. Encourage employees to use Copilot for drafting emails, documents, and generating meeting notes to familiarise them with its capabilities.
• Customisation. Tailor Copilot’s settings and suggestions to align with company-specific needs and workflows.
• Automation. Create bots, templates, integrations, and other automation functions for multiple use cases. For example, when users first log onto their PC, they could get a summary of missed emails, chats – without the need to request it.
• Feedback loop. Implement a feedback mechanism to monitor how Copilot is used and to make adjustments based on user experiences.
• Evaluating effectiveness. Gauge how Copilot’s features are enhancing productivity regularly and adjust usage strategies accordingly. Focus on the increased productivity – what knowledge workers now achieve with the time made available by Copilot.

Changing the behaviours of knowledge workers can be challenging – particularly for basic processes that they have been using for years or even decades. Knowledge of use cases and opportunities for Copilot will not just filter across the organisation. Implementing formal training and educational programs and backing them up with refresher courses is important to ensure compliance and productivity gains.