The financial services sector stands at a pivotal moment. Shaped by shifting customer expectations, fintech disruption, and rising demands for security and compliance, the industry is undergoing deep, ongoing transformation. From personalised digital engagement to AI-driven decisions and streamlined operations, BFSI is being fundamentally reshaped.
To thrive in this intelligent, interconnected future, financial organisations must embrace new strategies that turn challenges into opportunities.
Click here to download “Future Forward: Reimagining Financial Services” as a PDF.
Scaling for Impact
CreditAccess Grameen, a leading microfinance institution in India, struggled to scale its operations to meet the rising demand for microloans. Its manual processes were inefficient, causing delays and hindering its ability to serve an expanding customer base.
To overcome this, CreditAccess Grameen digitised its operations, automating processes to handle over 80,000 loans per day, streamlining loan approvals and improving operational efficiency.
This transformation significantly reduced loan processing times, from seven to ten days down to a more efficient, timely process. It also enhanced customer satisfaction, empowered financial independence, and strengthened CreditAccess Grameen’s position as a leader in financial inclusion, driving economic growth in rural India.
Seamless Operations, Improved Reporting
After merging three separate funds, Aware Super, one of Australia’s largest superannuation funds, faced fragmented operations, inconsistent documentation, and poor visibility into workflows. These inefficiencies hampered the organisation’s ability to optimise operations, ensure compliance, and deliver a seamless member experience.
To overcome this, Aware Super implemented a business process management suite to standardise and automate key processes, providing a unified platform for continuous improvement.
The transformation streamlined operations across all funds, improving reporting accuracy, reducing waste, and boosting procurement efficiency. The creation of a Centre of Excellence fostered a culture of ongoing process improvement and regulatory compliance, elevating Aware Super’s process maturity and solidifying its leadership in the financial services sector.
Empowering Employees and Improving Operations
The Norinchukin Bank, a major financial institution serving Japan’s agriculture, forestry, and fisheries sectors, struggled with outdated, paper-based processes and disconnected systems. Manual approvals and repetitive data entry were hindering operations and frustrating staff.
The digital team implemented a low-code platform that quickly automated approvals, integrated siloed systems, and streamlined processes into a single, efficient workflow.
The results were striking: approval times dropped, development cycles halved, and implementation costs fell by 30% compared to legacy upgrades. Employees gained real-time visibility over requests, cutting errors and speeding decisions. Crucially, the shift sparked a wave of digital adoption, with teams across the bank now embracing automation to drive further efficiency.
Eliminating Handoffs, Elevating Experience
Axis Bank, one of India’s largest private sector banks, struggled with slow, manual corporate onboarding processes, which hindered efficiency and customer satisfaction. The bank sought to streamline this process to keep up with growing demand for faster, digital services.
The bank implemented a robust API management solution, automating document handling and onboarding tasks, enabling a fully digital and seamless corporate client experience.
This transformation reduced corporate onboarding time by over 50%, eliminated manual handoffs, and enabled real-time monitoring of API performance, resulting in faster service delivery. As a result, Axis Bank saw a significant increase in customer satisfaction, a surge in API traffic, and a deeper, more loyal corporate client base.
Taming Latency, Unleashing Bandwidth
WebSpace, renowned for its in-store payment systems, faced challenges as it expanded to wholesalers. The migration to a new architecture required low-latency cloud connectivity, but its legacy network, relying on hardware routers, caused performance slowdowns, complexity, and high costs.
WebSpace adopted a cloud-based routing solution, replacing physical routers with a virtual, automated system for multicloud connectivity, enabling on-demand configuration changes from a central control point.
With the new solution, WebSpace achieved faster cloud connectivity, reducing latency and increasing bandwidth. The modern, agile network reduced management costs and complexity, while usage-based billing ensured that WebSpace only paid for the resources it used, supporting its strategic expansion and enhancing overall efficiency.
“SaaS is dead!” – this paraphrased comment from Satya Nadella during an interview was taken wildly out of context. It reminded me of those 2014-2017 industry reports predicting that voice commerce would be a USD 500B market by 2025, or that self-driving cars would be everywhere by 2027 – just two years from now. As it turns out, people still prefer ordering groceries themselves rather than relying on smart speakers connected to IoT fridges. And those early chatbot pop-ups? More annoying than intelligent. As for autonomous cars, we might still be better drivers – though that’s starting to shift. But I digress.
Back to SaaS. A global industry with over 30,000 companies, mostly in the US, now finds itself under the shadow of the latest buzz: AI agents (still software, not humanoid robots). These agents – programs built on top of LLMs – take actions within set parameters, showing a degree of autonomy.
But to make AI agents enterprise-ready, we’ll need to rethink access control, ethics, authentication, and compliance. So far, they’ve mostly tackled low-value, repetitive tasks. And despite the hype, we’re still some distance from real, meaningful impact.
Predictions Are Fine – But Best Taken with a Pinch of Salt
Salesforce, the world’s largest SaaS company, has played its part in driving this shift — alongside, of course, Microsoft. Microsoft’s aggressive push into AI, with a massive USD 80 billion CapEx on AI data centres and a flurry of product launches like Copilot chat, may just be the beginning. Microsoft even describes Copilot as the “UI for AI.” Despite its size, Salesforce has moved quickly, rolling out Agentforce, its enterprise AI agent suite. While still early days, Salesforce is leveraging its formidable sales and marketing muscle to push the AI agent narrative — while upselling Agentforce to thousands of existing customers.
For context: Salesforce, the largest player, generates around USD 35 billion in annual revenue. Across the industry, there are roughly 300 SaaS unicorns – but even combined, the entire global SaaS sector brings in only about USD 300B a year. Beyond big names like Salesforce, HubSpot, and Atlassian, the market is dominated by a long tail of smaller, vertical SaaS firms that serve niche sub-industries and specialised use cases.
Today, about 70% of enterprise software is delivered through SaaS. But beyond the top 30 vendors, the landscape is highly fragmented — and arguably primed for disruption by AI agents that can automate and streamline more bespoke, industry-specific workflows.
But the thousands of smaller SaaS firms haven’t all moved as quickly as Salesforce has. Most will likely stick to announcements and incremental upgrades rather than radical deployments – especially as enterprises tread carefully while every vendor suddenly becomes “AI-inside”, the new “Intel-inside.”
AI Washing, Hype, and a Flood of Start-Ups
Since ChatGPT’s historic launch in late 2022, the GenAI AI hype curve hasn’t slowed. In SaaS, the early impact has largely been “AI washing”: companies hastily sprinkling “Generative AI” across their websites, collateral, and social feeds while snapping up .ai domains at premium prices.
Meanwhile, over 3,000 AI-first start-ups have emerged, building wrappers around foundational models to deliver bespoke inferences and niche services. Thanks to ongoing hype, some of these are flush with venture capital – even without revenue. At the same time, traditional SaaS firms face tough investor scrutiny over profitability and free cash flow. The contrast couldn’t be starker.
Yet, both the AI upstarts and the older SaaS players face similar go-to-market challenges. Early product-market fit (PMF) is no guarantee of real traction, especially as most enterprise clients are still experimenting, rather than committing, to AI agents. That’s prompting start-ups to build agentic layers atop inference services to bridge the gap.
The Real Race: Embedding AI with Real Impact
It’s too early to call winners. Whether it’s cloud-first SaaS firms evolving into “AI-inside” platforms, or AI agent start-ups challenging the status quo, success will hinge on more than just AI. It will come down to who can combine proprietary data, compelling use cases, and proven workflow impact.
McKinsey sees AI agents serving two broad patterns: the “factory” model for predictable, routine tasks, and the “artisan” model for augmenting more strategic, executive functions. Another compelling narrative does not make the distinction between the earlier crop of cloud-first and the recent crop of AI-first companies. They see this as a natural progression of the SaaS business model, with VSaaS or “vertical Saas with AI-inside” becoming the broader industry.
I’d argue the original cloud-first SaaS firms might actually be better positioned. Their biggest moat? Existing customer relationships. AI start-ups haven’t yet faced the reality of renewing their first multi-year enterprise contracts. That’s where theory meets enterprise buying behaviour – and where this battle will get interesting.
The Playbook for SaaS Winners in the Age of AI Agents
The SaaS companies that will thrive over the next few years will, in my view, focus on these key elements:
- Leverage Early Clients as a Moat. Invest in the success of your first enterprise clients, ensuring they extract real, sustainable value before chasing new logos. Build enough trust, and you could co-create AI agents trained on their proprietary data, enhancing your core product in the process. Snowflake, with its broad enterprise footprint, has a head start here, but start-ups like Collectivei and Beam are targeting similar use cases, while platforms like Letta help companies deploy their own agents.
- Codify the Use Case. Build products that go deep – not broad. Focus on specific use cases or verticals that a horizontal SaaS company is unlikely to prioritise. Eventually, most enterprise users will care less about which foundation model powers your tool and more about the outcomes.
- Operate with a GTM-First Mindset. Many SaaS firms struggle with margins because of high sales and marketing costs, often wavering between sales-led and product-led growth without a clear go-to-market (GTM) plan. AI start-ups, too, are learning that pure product-led growth doesn’t scale in crowded markets and often pivot to sales-led motions too late. Companies like Chargeflow show why a GTM-first approach is key to building real traction and a growth flywheel.
- Rethink Bundling. Bundling has long been a SaaS pricing play – slicing features into tiers. AI-first start-ups are poised to disrupt this. The shift will be towards outcome-based pricing rather than packaging features. Winners will iterate constantly, tuning bundles to different user cohorts and business goals.
- Charge for Success, Not Seats. AI’s biggest impact may be on pricing. Traditional seat-based models will give way to success or outcome-based pricing, with minimal or no set-up fees. Professional services for customisation will still have value, especially where products align deeply with client workflows and outcomes.
- Prioritise Renewal Over Acquisition. Many AI-first start-ups focus on acquiring logos but underestimate that enterprises are still experimenting – switching costs are low, and loyalty is thin. Building for retention, renewal, and upselling will separate winners from the rest. Focus on churn early.
The Next Chapter in Enterprise Automation
Automation has always been a continuum. Remember when cloud vs. on-prem dominated enterprise debates? Or when RPA was expected to replace most workflows as we knew them? The reality was more measured, and we’re seeing a similar pattern with AI today. Enterprises will first focus on making AI co-pilots work safely, reliably, and effectively before they’re ready to hand over the keys to AI agents running workflows on autopilot. This shift won’t happen overnight.
We’re already seeing early winners capable of negotiating this shift, on both sides: established SaaS giants adapting and AI-native start-ups rising. But make no mistake, this will be a long, hard-fought race. Sustained value capture will demand more than just better tech; it will require a fundamental shift in mindset, go-to-market strategies, and sales motions.
Don’t be surprised if the acronym flips along the way – with Software-as-a-Service giving way to Service-as-Software, as AI agents begin to run entire business processes end to end.
Through it all, one principle will remain timeless: an obsession with customer success – whether the agent is human or machine.
India’s digital economy is on a meteoric rise, expected to reach USD 1 trillion by 2025. This surge in digital activity is fuelling the rapid expansion of its data centre market, positioning the country as a global player. With a projected market value of USD 4.5 billion by 2025, India’s data centre industry is set to surpass traditional regional hubs like Malaysia, Hong Kong, and Singapore.
This growth is driven by factors such as the proliferation of smartphones, internet connectivity, and digital services, generating massive amounts of data that need storage and processing. Government initiatives like Digital India and the National e-Governance Plan have promoted digitalisation, while favourable market conditions, including cost-effective infrastructure, skilled talent, and a large domestic market, make India an attractive destination for data centre investments.
As companies continue to invest, India is solidifying its role as a critical hub for Asia’s digital revolution, driving economic development and creating new opportunities for innovation and job creation.
What is Fuelling India’s Data Centre Growth?
India’s data centre industry is experiencing rapid growth in 2024, driven by a combination of strategic advantages and increasing demand. The country’s abundance of land and skilled workforce are key factors contributing to this boom.
- Digitisation push. The digital revolution is fueling the need for more sophisticated data centre infrastructure. The rise of social media, online gaming, and streaming apps has created a surge in demand for faster networks, better data storage options, and increased data centre services.
- Internet and mobile penetration. With 1.1 billion mobile phone subscribers, Indians use an average of 8.3 GB of data per month. As more people come online, businesses need to expand their data infrastructure to handle increased traffic, enhance service delivery, and support a growing digital economy.
- Increasing tech adoption. India’s AI market is projected to reach around USD 17 billion by 2027. As businesses integrate AI, IoT, cloud, and other technologies, data centres will become instrumental in supporting the vast computational and storage requirements.
- Government & regulatory measures. Apart from India being one of the world’s largest data consumption economies, government initiatives have also accelerated the ‘data based’ environment in the country. Additionally, states like Maharashtra, Karnataka, and Tamil Nadu have implemented favourable real estate policies that reduce the costs of setting up data centres.
A Growing Network of Hubs
India’s data centre landscape is rapidly evolving, with major cities and emerging hotspots vying for a piece of the pie.
Mumbai-Navi Mumbai remains the undisputed leader, boasting a combined 39 data centres. Its strategic location with excellent submarine cable connectivity to Europe and Southeast Asia makes it a prime destination for global and domestic players.
Bangalore, India’s IT capital, is not far behind with 29 data centres. The city’s thriving tech ecosystem and skilled talent pool make it an attractive option for businesses looking to set up data centres.
Chennai, located on the east coast, has emerged as a crucial hub with 17 data centres. Its proximity to Southeast Asia and growing digital economy make it a strategic location. The Delhi-NCR region also plays a significant role, with 27 data centres serving the capital and surrounding areas.
Smaller cities like Pune, Jaipur, and Patna are rapidly emerging as data centre hotspots. As businesses seek to serve a growing but distributed user base across India, these cities offer more cost-effective options. Additionally, the rise of edge data centres in these smaller cities is further decentralising the data centre landscape.
A Competitive Market
India ranks 13th globally in the number of operational data centres, with 138 facilities in operation and an additional 45 expected to be completed by the end of 2025. Key initiatives include:
- AWS. AWS is investing USD 12.7 billion to establish four new data centres over the next two years.
- Meta. Meta is set to build a small data centre, potentially focused on cache with a 10-20 MW capacity.
- AdaniConnex. In partnership with EdgeConneX, AdaniConnex aims to develop a 1 GW network of hyperscale data centres over the next decade, all powered by 100% renewable energy.
- Google. Google is set to build an 80-storey data centre by 2025 and is in advanced talks to acquire a 22.5-acre land parcel for its first captive data centre.
- NTT. NTT is investing USD 241 million in a data campus, which will feature three data centres.
Data Centres: Driving Digital India’s Success
The Digital India initiative has transformed government services through improved online infrastructure and increased connectivity. Data centres play a pivotal role in supporting this vision by managing, storing, and processing the vast amounts of data that power essential services like Aadhaar and BharatNet.
Aadhaar, India’s biometric ID system, relies heavily on data centres to store and process biometric information, enabling seamless identification and authentication. BharatNet, the government’s ambitious project to connect rural areas with high-speed internet, also depends on data centres to provide the necessary infrastructure and support.
The impact of data centres on India’s digital transformation is far-reaching. Here are some key areas where data centres have made a significant contribution:
- Enabling Remote Work and Education. Data centres have been instrumental in supporting the surge in remote work and online learning during the pandemic. By providing the necessary infrastructure and connectivity, data centres have ensured business continuity and uninterrupted education.
- Fostering Start-Up Innovation. Data centres provide the essential infrastructure for start-ups to thrive. By offering reliable and scalable computing resources, data centres enable rapid growth and innovation, contributing to the expansion of India’s SaaS market.
- Supporting Government Services. Data centres underpin key government initiatives, including e-governance platforms and digital identity systems. They enhance the accessibility, transparency, and efficiency of government services, bridging the urban-rural divide and improving public service delivery.
Securing India’s Data Centre Future
Data centres are the backbone of India’s digital transformation, fuelling economic growth, government services, innovation, remote work, and technological progress. The Indian government’s ambitious plan to invest over USD 1 billion in hyperscale data centres over the next five years underscores the country’s commitment to building a robust digital infrastructure.
To secure the long-term success of India’s data centre industry, alignment with global standards and strategic investment are crucial. Prioritising reliability, efficiency, and sustainability will attract global providers and position India as a prime destination for digital infrastructure investments. Addressing challenges like legacy upgrades, modernisation, and cybersecurity risks will require collaboration across stakeholders, with government support and technological innovation playing key roles.
A unified effort from central and state governments is vital to enhance competitiveness. By fostering a favourable regulatory environment and offering incentives, the government can accelerate the development of world-class data centres. As India advances digitally, data centres will be instrumental in driving economic growth, improving quality of life, and solidifying India’s status as a global digital leader.
Ecosystm research reveals that customer-centricity is the primary driver for tech investments in the Philippines, with 62% of organisations investing in AI specifically to enhance customer experience.
Learn about other major trends transforming The Philippines’ technology landscape.
Ecosystm research shows low GenAI adoption in Indonesia, with 83% of organisations hesitant due to governance or language barriers.
Learn about the key trends transforming the Indonesian technology landscape and watch this space for more data-backed insights on Southeast Asia’s tech markets.
To mitigate the challenges of cloud vendor lock-in, 44% of organisations in Thailand will prioritise data centre consolidation and infrastructure modernisation in 2024.
Explore the key trends impacting Thailand’s technology adoption. Keep an eye out for more data-backed insights on tech markets across Southeast Asia.
ASEAN, poised to become the world’s 4th largest economy by 2030, is experiencing a digital boom. With an estimated 125,000 new internet users joining daily, it is the fastest-growing digital market globally. These users are not just browsing, but are actively engaged in data-intensive activities like gaming, eCommerce, and mobile business. As a result, monthly data usage is projected to soar from 9.2 GB per user in 2020 to 28.9 GB per user by 2025, according to the World Economic Forum. Businesses and governments are further fuelling this transformation by embracing Cloud, AI, and digitisation.
Investments in data centre capacity across Southeast Asia are estimated to grow at a staggering pace to meet this growing demand for data. While large hyperscale facilities are currently handling much of the data needs, edge computing – a distributed model placing data centres closer to users – is fast becoming crucial in supporting tomorrow’s low-latency applications and services.
The Big & the Small: The Evolving Data Centre Landscape
As technology pushes boundaries with applications like augmented reality, telesurgery, and autonomous vehicles, the demand for ultra-low latency response times is skyrocketing. Consider driverless cars, which generate a staggering 5 TB of data per hour and rely heavily on real-time processing for split-second decisions. This is where edge data centres come in. Unlike hyperscale data centres, edge data centres are strategically positioned closer to users and devices, minimising data travel distances and enabling near-instantaneous responses; and are typically smaller with a capacity ranging from 500 KW to 2 MW. In comparison, large data centres have a capacity of more than 80MW.
While edge data centres are gaining traction, cloud-based hyperscalers such as AWS, Microsoft Azure, and Google Cloud remain a dominant force in the Southeast Asian data centre landscape. These facilities require substantial capital investment – for instance, it took almost USD 1 billion to build Meta’s 150 MW hyperscale facility in Singapore – but offer immense processing power and scalability. While hyperscalers have the resources to build their own data centres in edge locations or emerging markets, they often opt for colocation facilities to familiarise themselves with local markets, build out operations, and take a “wait and see” approach before committing significant investments in the new market.
The growth of data centres in Southeast Asia – whether edge, cloud, hyperscale, or colocation – can be attributed to a range of factors. The region’s rapidly expanding digital economy and increasing internet penetration are the prime reasons behind the demand for data storage and processing capabilities. Additionally, stringent data sovereignty regulations in many Southeast Asian countries require the presence of local data centres to ensure compliance with data protection laws. Indonesia’s Personal Data Protection Law, for instance, allows personal data to be transferred outside of the country only where certain stringent security measures are fulfilled. Finally, the rising adoption of cloud services is also fuelling the need for onshore data centres to support cloud infrastructure and services.
Notable Regional Data Centre Hubs
Singapore. Singapore imposed a moratorium on new data centre developments between 2019 to 2022 due to concerns over energy consumption and sustainability. However, the city-state has recently relaxed this ban and announced a pilot scheme allowing companies to bid for permission to develop new facilities.
In 2023, the Singapore Economic Development Board (EDB) and the Infocomm Media Development Authority (IMDA) provisionally awarded around 80 MW of new capacity to four data centre operators: Equinix, GDS, Microsoft, and a consortium of AirTrunk and ByteDance (TikTok’s parent company). Singapore boasts a formidable digital infrastructure with 100 data centres, 1,195 cloud service providers, and 22 network fabrics. Its robust network, supported by 24 submarine cables, has made it a global cloud connectivity leader, hosting major players like AWS, Azure, IBM Softlayer, and Google Cloud.
Aware of the high energy consumption of data centres, Singapore has taken a proactive stance towards green data centre practices. A collaborative effort between the IMDA, government agencies, and industries led to the development of a “Green Data Centre Standard“. This framework guides organisations in improving data centre energy efficiency, leveraging the established ISO 50001 standard with customisations for Singapore’s context. The standard defines key performance metrics for tracking progress and includes best practices for design and operation. By prioritising green data centres, Singapore strives to reconcile its digital ambitions with environmental responsibility, solidifying its position as a leading Asian data centre hub.
Malaysia. Initiatives like MyGovCloud and the Digital Economy Blueprint are driving Malaysia’s public sector towards cloud-based solutions, aiming for 80% use of cloud storage. Tenaga Nasional Berhad also established a “green lane” for data centres, solidifying Malaysia’s commitment to environmentally responsible solutions and streamlined operations. Some of the big companies already operating include NTT Data Centers, Bridge Data Centers and Equinix.
The district of Kulai in Johor has emerged as a hotspot for data centre activity, attracting major players like Nvidia and AirTrunk. Conditional approvals have been granted to industry giants like AWS, Microsoft, Google, and Telekom Malaysia to build hyperscale data centres, aimed at making the country a leading hub for cloud services in the region. AWS also announced a new AWS Region in the country that will meet the high demand for cloud services in Malaysia.
Indonesia. With over 200 million internet users, Indonesia boasts one of the world’s largest online populations. This expanding internet economy is leading to a spike in the demand for data centre services. The Indonesian government has also implemented policies, including tax incentives and a national data centre roadmap, to stimulate growth in this sector.
Microsoft, for instance, is set to open its first regional data centre in Thailand and has also announced plans to invest USD 1.7 billion in cloud and AI infrastructure in Indonesia. The government also plans to operate 40 MW of national data centres across West Java, Batam, East Kalimantan, and East Nusa Tenggara by 2026.
Thailand. Remote work and increasing online services have led to a data centre boom, with major industry players racing to meet Thailand’s soaring data demands.
In 2021, Singapore’s ST Telemedia Global Data Centres launched its first 20 MW hyperscale facility in Bangkok. Soon after, AWS announced a USD 5 billion investment plan to bolster its cloud capacity in Thailand and the region over the next 15 years. Heavyweights like TCC Technology Group, CAT Telecom, and True Internet Data Centre are also fortifying their data centre footprints to capitalise on this explosive growth. Microsoft is also set to open its first regional data centre in the country.
Conclusion
Southeast Asia’s booming data centre market presents a goldmine of opportunity for tech investment and innovation. However, navigating this lucrative landscape requires careful consideration of legal hurdles. Data protection regulations, cross-border data transfer restrictions, and local policies all pose challenges for investors. Beyond legal complexities, infrastructure development needs and investment considerations must also be addressed. Despite these challenges, the potential rewards for companies that can navigate them are substantial.
For many organisations migrating to cloud, the opportunity to run workloads from energy-efficient cloud data centres is a significant advantage. However, carbon emissions can vary from one country to another and if left unmonitored, will gradually increase over time as cloud use grows. This issue will become increasingly important as we move into the era of compute-intensive AI and the burden of cloud on natural resources will shift further into the spotlight.
The International Energy Agency (IEA) estimates that data centres are responsible for up to 1.5% of global electricity use and 1% of GHG emissions. Cloud providers have recognised this and are committed to change. Between 2025 and 2030, all hyperscalers – AWS, Azure, Google, and Oracle included – expect to power their global cloud operations entirely with renewable sources.
Chasing the Sun
Cloud providers are shifting their sights from simply matching electricity use with renewable power purchase agreements (PPA) to the more ambitious goal of operating 24/7 on carbon-free sources. A defining characteristic of renewables though is intermittency, with production levels fluctuating based on the availability of sunlight and wind. Leading cloud providers are using AI to dynamically distribute compute workloads throughout the day to regions with lower carbon intensity. Workloads that are processed with solar power during daylight can be shifted to nearby regions with abundant wind energy at night.
Addressing Water Scarcity
Many of the largest cloud data centres are situated in sunny locations to take advantage of solar power and proximity to population centres. Unfortunately, this often means that they are also in areas where water is scarce. While liquid-cooled facilities are energy efficient, local communities are concerned on the strain on water sources. Data centre operators are now committing to reduce consumption and restore water supplies. Simple measures, such as expanding humidity (below 20% RH) and temperature tolerances (above 30°C) in server rooms have helped companies like Meta to cut wastage. Similarly, Google has increased their reliance on non-potable sources, such as grey water and sea water.
From Waste to Worth
Data centre operators have identified innovative ways to reuse the excess heat generated by their computing equipment. Some have used it to heat adjacent swimming pools while others have warmed rooms that house vertical farms. Although these initiatives currently have little impact on the environmental impact of cloud, they suggest a future where waste is significantly reduced.
Greening the Grid
The giant facilities that cloud providers use to house their computing infrastructure are also set to change. Building materials and construction account for an astonishing 11% of global carbon emissions. The use of recycled materials in concrete and investing in greener methods of manufacturing steel are approaches the construction industry are attempting to lessen their impact. Smaller data centres have been 3D printed to accelerate construction and use recyclable printing concrete. While this approach may not be suitable for hyperscale facilities, it holds potential for smaller edge locations.
Rethinking Hardware Management
Cloud providers rely on their scale to provide fast, resilient, and cost-effective computing. In many cases, simply replacing malfunctioning or obsolete equipment would achieve these goals better than performing maintenance. However, the relentless growth of e-waste is putting pressure on cloud providers to participate in the circular economy. Microsoft, for example, has launched three Circular Centres to repurpose cloud equipment. During the pilot of their Amsterdam centre, it achieved 83% reuse and 17% recycling of critical parts. The lifecycle of equipment in the cloud is largely hidden but environmentally conscious users will start demanding greater transparency.
Recommendations
Organisations should be aware of their cloud-derived scope 3 emissions and consider broader environmental issues around water use and recycling. Here are the steps that can be taken immediately:
- Monitor GreenOps. Cloud providers are adding GreenOps tools, such as the AWS Customer Carbon Footprint Tool, to help organisations measure the environmental impact of their cloud operations. Understanding the relationship between cloud use and emissions is the first step towards sustainable cloud operations.
- Adopt Cloud FinOps for Quick ROI. Eliminating wasted cloud resources not only cuts costs but also reduces electricity-related emissions. Tools such as CloudVerse provide visibility into cloud spend, identifies unused instances, and helps to optimise cloud operations.
- Take a Holistic View. Cloud providers are being forced to improve transparency and reduce their environmental impact by their biggest customers. Getting educated on the actions that cloud partners are taking to minimise emissions, water use, and waste to landfill is crucial. In most cases, dedicated cloud providers should reduce waste rather than offset it.
- Enable Remote Workforce. Cloud-enabled security and networking solutions, such as SASE, allow employees to work securely from remote locations and reduce their transportation emissions. With a SASE deployed in the cloud, routine management tasks can be performed by IT remotely rather than at the branch, further reducing transportation emissions.
2024 will be another crucial year for tech leaders – through the continuing economic uncertainties, they will have to embrace transformative technologies and keep an eye on market disruptors such as infrastructure providers and AI startups. Ecosystm analysts outline the key considerations for leaders shaping their organisations’ tech landscape in 2024.
Navigating Market Dynamics
Continuing Economic Uncertainties. Organisations will focus on ongoing projects and consider expanding initiatives in the latter part of the year.
Popularity of Generative AI. This will be the time to go beyond the novelty factor and assess practical business outcomes, allied costs, and change management.
Infrastructure Market Disruption. Keeping an eye out for advancements and disruptions in the market (likely to originate from the semiconductor sector) will define vendor conversations.
Need for New Tech Skills. Generative AI will influence multiple tech roles, including AIOps and IT Architecture. Retaining talent will depend on upskilling and reskilling.
Increased Focus on Governance. Tech vendors are guide tech leaders on how to implement safeguards for data usage, sharing, and cybersecurity.
5 Key Considerations for Tech Leaders
#1 Accelerate and Adapt: Streamline IT with a DevOps Culture
Over the next 12-18 months, advancements in AI, machine learning, automation, and cloud-native technologies will be vital in leveraging scalability and efficiency. Modernisation is imperative to boost responsiveness, efficiency, and competitiveness in today’s dynamic business landscape.
The continued pace of disruption demands that organisations modernise their applications portfolios with agility and purpose. Legacy systems constrained by technical debt drag down velocity, impairing the ability to deliver new innovative offerings and experiences customers have grown to expect.
Prioritising modernisation initiatives that align with key value drivers is critical. Technology leaders should empower development teams to move beyond outdated constraints and swiftly deploy enhanced applications, microservices, and platforms.
#2 Empowering Tomorrow: Spring Clean Your Tech Legacy for New Leaders
Modernising legacy systems is a strategic and inter-generational shift that goes beyond simple technical upgrades. It requires transformation through the process of decomposing and replatforming systems – developed by previous generations – into contemporary services and signifies a fundamental realignment of your business with the evolving digital landscape of the 21st century.
The essence of this modernisation effort is multifaceted. It not only facilitates the integration of advanced technologies but also significantly enhances business agility and drives innovation. It is an approach that prepares your organisation for impending skill gaps, particularly as the older workforce begins to retire over the next decade. Additionally, it provides a valuable opportunity to thoroughly document, reevaluate, and improve business processes. This ensures that operations are not only efficient but also aligned with current market demands, contemporary regulatory standards, and the changing expectations of customers.
#3 Employee Retention: Consider the Strategic Role of Skills Acquisition
The agile, resilient organisation needs to be able to respond at pace to any threat or opportunity it faces. Some of this ability to respond will be related to technology platforms and architectures, but it will be the skills of employees that will dictate the pace of reform. While employee attrition rates will continue to decline in 2024 – but it will be driven by skills acquisition, not location of work.
Organisations who offer ongoing staff training – recognising that their business needs new skills to become a 21st century organisation – are the ones who will see increasing rates of employee retention and happier employees. They will also be the ones who offer better customer experiences, driven by motivated employees who are committed to their personal success, knowing that the organisation values their performance and achievements.
#4 Next-Gen IT Operations: Explore Gen AI for Incident Avoidance and Predictive Analysis
The integration of Generative AI in IT Operations signifies a transformative shift from the automation of basic tasks, to advanced functions like incident avoidance and predictive analysis. Initially automating routine tasks, Generative AI has evolved to proactively avoiding incidents by analysing historical data and current metrics. This shift from proactive to reactive management will be crucial for maintaining uninterrupted business operations and enhancing application reliability.
Predictive analysis provides insight into system performance and user interaction patterns, empowering IT teams to optimise applications pre-emptively, enhancing efficiency and user experience. This also helps organisations meet sustainability goals through accurate capacity planning and resource allocation, also ensuring effective scaling of business applications to meet demands.
#5 Expanding Possibilities: Incorporate AI Startups into Your Portfolio
While many of the AI startups have been around for over five years, this will be the year they come into your consciousness and emerge as legitimate solutions providers to your organisation. And it comes at a difficult time for you!
Most tech leaders are looking to reduce technical debt – looking to consolidate their suppliers and simplify their tech architecture. Considering AI startups will mean a shift back to more rather than fewer tech suppliers; a different sourcing strategy; more focus on integration and ongoing management of the solutions; and a more complex tech architecture.
To meet business requirements will mean that business cases will need to be watertight – often the value will need to be delivered before a contract has been signed.
