The rise of deepfakes has evolved from a fringe technological curiosity to one of the most pressing cybersecurity concerns heading into 2026, according to new predictions from Kaspersky. As AI adoption accelerates across the Asia Pacific (APAC), the region is becoming both a proving ground for innovation and a testing arena for increasingly sophisticated cyber threats.

With 78 per cent of professionals in APAC using AI at least weekly, compared with 72 per cent globally, the scale and speed of adoption are amplifying the risks associated with synthetic content, forcing businesses and governments to rethink digital trust and resilience strategies now. For business owners and policymakers, this means prioritising AI risk assessments and embedding deepfake awareness into national and corporate cybersecurity roadmaps.

Deepfakes are no longer limited to manipulated videos of public figures; they are becoming a mainstream technology encountered by employees, consumers and organisations alike. Kaspersky notes that awareness of deepfake risks is growing, with companies increasingly training staff to recognise synthetic content and reduce the likelihood of fraud.

As deepfakes appear in more formats—video, images, voice and text—they are becoming a “stable element of the security agenda,” requiring structured policies rather than ad hoc responses. Leaders should respond by formalising internal training programmes, updating incident response plans and mandating verification processes for sensitive communications.

The threat is compounded by rapid improvements in deepfake quality and accessibility. While visual deepfakes are already highly convincing, Kaspersky predicts major advances in realistic audio, a key enabler of voice-based scams and impersonation fraud. At the same time, the barrier to entry is falling sharply, with non-experts now able to generate mid-quality deepfakes in just a few clicks.

Also Read: AI’s biggest bottleneck isn’t intelligence but fragmentation: i10X co-founder

This democratisation of creation tools means cybercriminals no longer need advanced skills to launch convincing attacks at scale. To counter this, organisations should invest in multi-factor authentication, out-of-band verification, and stricter approval workflows for financial and executive-level requests.

Efforts to label AI-generated content are expected to intensify in 2026, but progress remains uneven. There is still no unified or reliable system for identifying synthetic content, and existing labels can be easily removed or bypassed, particularly in open-source environments. As a result, Kaspersky anticipates new technical and regulatory initiatives aimed at addressing the challenge, though enforcement will lag behind innovation. Policymakers should collaborate across borders to establish minimum standards for AI content labelling, while businesses should not rely solely on labels and instead adopt layered detection and verification controls.

More advanced forms of deepfakes, such as real-time face and voice swapping, will continue to evolve, even if they remain tools for technically skilled attackers. While widespread use is unlikely in the near term, Kaspersky warns that risks will grow in targeted scenarios, including executive fraud, espionage and political manipulation. Increasing realism and the use of virtual cameras will make these attacks harder to detect and more persuasive. High-risk organisations should conduct threat modelling for targeted deepfake attacks and limit the public exposure of executive audio and video data wherever possible.

The growing use of open-weight AI models is also blurring the line between legitimate and malicious applications. As these models approach the capabilities of closed systems in cybersecurity-related tasks, they offer more opportunities for misuse due to weaker safeguards. At the same time, AI-generated phishing emails, fake websites, and synthetic brand assets are becoming increasingly indistinguishable from legitimate content, especially as companies themselves adopt AI in their marketing and communications. Businesses must strengthen brand protection, monitor for impersonation and educate customers on official communication channels to reduce fraud risks.

“Attackers are using it to automate attacks, exploit vulnerabilities, and create highly convincing fake content,” said Vladislav Tushkanov, research development group manager at Kaspersky. “At the same time, defenders are applying AI to scan systems, detect threats, and make faster, smarter decisions.”

Also Read: The ASEAN AI rush: Why “move fast and break things” is a dangerous strategy for risk

For the APAC region, the stakes are particularly high. “Asia Pacific is setting the global pace for AI adoption,” said Adrian Hia, managing director for Asia Pacific at Kaspersky. “This momentum is creating tremendous opportunity, but also redefining how cyber threats emerge and scale.”

As deepfakes cement their place as a top cybersecurity concern of 2026, resilience will depend on preparation rather than reaction.

Kaspersky recommends regular data backups, isolated from networks, and the use of advanced security platforms to detect and neutralise complex threats. These steps, which policymakers and business leaders alike must champion, are crucial to safeguarding trust in an AI-driven economy.

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The lead image in this article is AI-generated.

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The Southeast Asian startup ecosystem is currently experiencing a “Great Divide” in its capital allocation strategy.

While total regional funding saw a modest 7 per cent rise to US$5.2 billion in 2025, this growth was entirely top-heavy. As detailed in the “SEA Tech Annual Funding Report 2025” by Tracxn, late-stage funding witnessed a meteoric 194 per cent rise, reaching US$3.9 billion. This surge in the upper echelons of the market suggests that investors are doubling down on proven winners rather than betting on new ideas.

Also Read: Jakarta trails as Singapore tightens its grip on tech capital

Conversely, the environment for fledgling startups has become increasingly hostile. Seed-stage funding plummeted by 57 per cent to just US$214 million, while early-stage funding (Series A and B) dropped by 64 per cent to US$1.1 billion. This creates a precarious situation for the region’s innovation pipeline, as the foundation of the ecosystem is shrinking even as the top becomes more robust.

The data regarding “first-time funded” companies is particularly alarming for those hoping for a new wave of entrepreneurs. The number of companies receiving their first round of capital fell 62 per cent, from 283 in 2024 to just 107 in 2025. Investors are clearly operating with a “flight to quality” mindset, favouring companies with clear paths to profitability and established market presence.

This shift is further evidenced by the return of the mega-round. 2025 witnessed nine funding rounds of US$100 million or more, a slight increase from the seven seen in 2024. High-profile deals for firms like Airwallex, which raised US$330 million in a Series G round, and MiniMax, which secured US$300 million, have become the primary drivers of the region’s capital totals.

Also Read: From US$107M lows to a US$491M finish: SEA’s volatile 2025

The Southeast Asian funding landscape has evolved into a high-stakes arena where only those who have already breached the walls can find shelter, while the gates remain firmly shut for newcomers outside.

The post Southeast Asia’s startup boom is becoming a closed club appeared first on e27.

Thailand has formally entered Southeast Asia’s high-stakes semiconductor race, unveiling its first national roadmap aimed at transforming the country from a backend electronics hub into a strategic producer of high-value chips over the next 25 years.

The roadmap, approved on Wednesday by the newly constituted National Semiconductor Board, chaired by Deputy Prime Minister and Finance Minister Ekniti Nitithanprapas, sets phased milestones for 2030, 2040, and 2050. At its core is an ambition to reposition the country as a critical node in the regional and global chip supply chain, moving decisively beyond basic assembly into design-led and upstream manufacturing.

Also Read: Spectral is breaking Nvidia’s monopoly — one line of CUDA code at a time

Competing and complementing Singapore and Malaysia

Thailand’s strategy places it in a complementary rather than confrontational position against regional leaders Singapore and Malaysia, both of which already occupy entrenched roles in the global semiconductor ecosystem.

Singapore commands roughly 10 per cent of global wafer fabrication and chip design, underpinned by world-class R&D infrastructure and deep integration with multinational firms. Malaysia, meanwhile, dominates the outsourced semiconductor assembly and testing (OSAT) segment, accounting for 13-15 per cent of global market share.

Thailand is charting a different course. Rather than directly competing in advanced front-end fabs or cutting-edge R&D, it is targeting power electronics, automotive semiconductors, sensors, analog, photonics and discrete chips. These segments are closely aligned with its existing industrial strengths in electric vehicles, medical devices, AI data centres and smart manufacturing.

Lower operating costs, aggressive incentives and specialised industrial clusters are expected to give Thailand an edge in mid-tier, high-growth segments.

The roadmap: From assembly to fabrication

The National Semiconductor Strategy is structured around five strategic pillars:

1. High-potential products: Prioritising power, sensor, photonics, analog and discrete chips critical to Thailand’s industrial base.
2. Short-term strengthening: Consolidating Thailand’s existing leadership in OSAT and integrated circuit (IC) design over the next five years.
3. Long-term upstream ambition: Gradually entering wafer fabrication, the most complex and capital-intensive stage of chipmaking, while nurturing “local champions” to reduce reliance on foreign technology.

Also Read: Asia rises in the AI chip race: China to outgrow US by 30 per cent by 2030

1. Talent development: Allocating billions of baht to workforce training, with targets ranging from 17,500 to over 200,000 engineers by 2030 through partnerships with global universities and industry.
2. Ecosystem building: Developing specialised semiconductor clusters in regions such as Lamphun and Lampang, backed by guaranteed clean energy, water security, streamlined regulations and semiconductor-specific trade agreements with the US, UK and EU.

The Board of Investment (BOI) is offering 15-year tax holidays, long-term low-interest financing, fast-track visas, land incentives within the Eastern Economic Corridor (EEC) and green-energy access via direct power purchase agreements. Around 70 semiconductor projects worth nearly THB 300 billion are already awaiting approval.

Why semiconductors matter to Thailand

Semiconductors are foundational to the country’s broader technology ambitions. Electronics already account for over 25 per cent of Thai exports, generating more than US$50 billion annually. As global supply chains realign– accelerated by US-China decoupling — Thailand sees chips as essential to sustaining growth and avoiding stagnation in traditional manufacturing.

Without deeper participation in semiconductors, Thailand risks being locked into low-margin assembly work while demand for chips surges across EVs, AI, IoT, data centres and advanced automation. The roadmap is also central to the government’s “Thailand 4.0” vision, which seeks to shift the economy toward innovation-led, high-value manufacturing and boost GDP growth to 2 per cent in 2026.

A sector on the rise

Thailand’s semiconductor and electronics sector has expanded rapidly over the past decade. The market grew from US$4.88 billion in 2023 to US$8.46 billion in 2025, and is projected to reach US$11.79 billion by 2030, with annual growth ranging between 7.6 and 20 per cent.

Also Read: Semiconductors at risk: The invisible threats that could break global supply chains

Between 2018 and late 2025, the country recorded 1,748 electronics investment applications worth THB 1.17 trillion (US$34.4 billion). Global heavyweights such as Infineon, NXP, Murata, Foxconn (Fiti) and others have expanded or established significant operations, reinforcing Thailand’s status as a key OSAT and automotive semiconductor hub.

The long game

While figures around US$73.5 billion in investment likely reflect broader multi-decade ambitions rather than near-term commitments, the intent is unmistakable. As BOI secretary general Narit Therdsteerasukdi noted, the semiconductor industry is on track to become a US$1 trillion global market by 2030, and Thailand intends to be more than a passive consumer.

Thailand’s journey is less about overtaking Singapore or Malaysia, and more about filling strategic gaps in Southeast Asia’s chip ecosystem. Like a master craftsman moving from assembly to design, the country is laying the groundwork to own more of the semiconductor value chain—patiently, pragmatically, and with an eye on long-term competitiveness.

The post Thailand enters the chip race, without challenging Singapore head-on appeared first on e27.

Rather than treating cloud spend as a back-office responsibility, leading organisations are starting to manage it as an operational discipline. This aligns teams around shared data, enabling clearer decisions on infrastructure, scaling, and performance and making cloud investments easier to forecast and optimise as the business grows.

Drawing from its work with enterprises across the region, Elite Cloud observes that multi-cloud adoption is accelerating faster than visibility and cost governance. As workloads spread across providers to support resilience, compliance, and performance, leadership often loses clarity on actual usage, cost drivers, and emerging inefficiencies.

While Elite Cloud’s cloud savings report is currently AWS-first, Elite Cloud already delivers end-to-end multi-cloud consulting, optimisation, and cloud operations across AWS, Google Cloud, Azure, Alibaba Cloud, and Tencent Cloud. This regional, provider-agnostic perspective reflects how ASEAN enterprises actually operate today.

In fast-growing markets, cloud visibility is central to resilience, forecasting, and operational control — but it is only the starting point. The real advantage comes when insight is translated into continuous optimisation. As a result, organisations can expand without cloud complexity becoming a drag on growth.

The new risks created by unseen cloud waste

The cloud computing market is predicted to surpass $1 trillion by 2028. (Source: Precedence Research). As ASEAN enterprises scale across multiple cloud platforms, inefficiencies often accumulate unnoticed, frequently driven by well-intentioned teams adopting tools and services in pursuit of productivity.

According to Flexera 2025 State of the Cloud Report, up to 30% of cloud spending is wasted each year. This includes money paid for idle or under-utilised resources that rarely deliver business value. This silent leakage quietly erodes margins. Meanwhile, cloud bills continue to grow, especially as organisations chase innovation and expansion.

Unpredictable billing compounds the problem. Without clear visibility into usage and cost drivers, engineering, finance, and leadership struggle to forecast budgets or align roadmaps. Leadership tightens controls, while teams lack the data needed to justify decisions, slowing progress on both sides.

Also read: Is the future of AI decentralised? Cloud computing holds the key

Why visibility is quickly becoming the backbone of cloud governance

For enterprises looking to expand across ASEAN markets, this is more than a back-office issue — it’s a strategic risk. When leaders can’t see what they’re spending or why, cloud waste becomes a barrier to disciplined growth.

Elite Cloud’s specialists see visibility as the practical starting point for disciplined cloud governance. True cloud cost visibility means a clear, shared view of cloud usage signals and corresponding costs across cloud environments. This eliminates blind spots created by fragmented dashboards and siloed teams. Rather than relying on retrospective billing reports, organisations need continuous insight to catch inefficiencies as they emerge. In short, enterprises need real-time awareness rather than annual reviews or manual audits that cost more time and resources to accomplish.

Elite Cloud applies AI-driven precision analysis to examine workload patterns across environments. It identifies idle or oversized resources and prioritising the highest-impact optimisation opportunities. Beyond cost optimisation, Elite Cloud also supports security posture checks with hundreds of checks. Thus, it helps teams prioritise high-risk and critical issues alongside efficiency improvements.

To help teams understand how optimisation translates into real outcomes, Elite Cloud surfaces a prioritised list of opportunities, with each recommendation tied to a specific action teams can implement.  But visibility alone isn’t enough. Real value comes from turning data into action so that engineering and finance can operate from the same data foundation with alignment. In practice, visibility becomes most useful when it clearly shows what can change. 

In a typical cloud diagnostic (results vary by environment and scope), Elite Cloud identifies an estimated 28.3% cost savings potential, or roughly US$24,800 in monthly savings, with clear attribution between pricing leverage and AI-driven optimisation. Drawing on insights from more than 2,000 client engagements, the company tailors savings reports that, in some cases, surface opportunities of up to 40%. Tracking these changes over time allows teams to see how cost structures evolve as inefficiencies are removed.

Also read: Coded in your DNA: How Singapore can help avert a global data storage crisis

How transparency strengthens competitiveness for fast-growing ASEAN enterprises

For fast-growing ASEAN enterprises, transparency becomes a competitive advantage when it translates directly into better decisions. Rather than applying blanket cost-cutting measures, Elite Cloud focuses on service-level optimisation. Each cloud service is reviewed individually to identify configuration or usage inefficiencies — whether that means rightsizing instances, changing instance families, applying scheduling policies, or tuning storage lifecycles — all without compromising performance.

Elite Cloud enables this by maintaining a detailed, time-stamped record of historical data and cloud activity across connected environments. This allows teams to analyse historical usage patterns and identify cost drivers with precision. This continuous logging and instant access to insights help organisations move beyond reactive cost reviews toward proactive optimisation.

Centralised visibility further reduces operational friction, especially for teams operating across markets. With shared insights and prioritised recommendations, teams can align on what to change first and implement improvements efficiently, lowering overhead and accelerating response times.

In fast-changing markets, disciplined cloud cost control becomes a form of strategic resilience. This is especially true when optimisation is embedded into day-to-day operations. Teams that operate from shared data can detect waste earlier and optimise without compromising performance.

Where Elite Cloud believes visibility-led cloud operations are heading next

In many organisations, leaders report that a significant portion of cloud spend feels wasted due to limited visibility and weak cost control. Addressing this requires solutions that surface usage patterns, cost drivers, anomalies, and optimisation opportunities in one place.

Elite Cloud’s specialised and contextual insights are designed to help organisations strengthen their cloud posture while reducing waste at the same time. The future of FinOps in ASEAN will rely on solutions that support continuous optimisation across both financial and operational risk, not just one-off cost-cutting.

At its core, Elite Cloud’s approach to smart cloud cost optimisation is about making every dollar work harder. By combining data-driven analysis with intelligent allocation and expert validation, organisations can reduce cloud spend while maximising return on infrastructure investments — without trading off performance, reliability, or security. To get started with understanding your cloud strategy, message Elite Cloud’s expert team and get your free cloud savings report.

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Southeast Asia and the Pacific region are at a critical juncture, facing unique challenges and immense innovation potential. For startups looking to build impactful and profitable ventures, focusing on problem-based solutions aligned with the UN Sustainable Development Goals (SDGs) offers a clear roadmap.

In 2026, the following 10 sectors present the most compelling opportunities.

The power of problem-based innovation

Instead of chasing fleeting trends, successful startups identify acute problems and build solutions. The SDGs provide a globally recognised framework for these problems, making them excellent targets for entrepreneurial ventures. This is not just a dry, academic-based assessment.

I live this experience daily, as I’ve spent 35 years in the region, starting, growing and exiting from 10 companies, before investing in 77 startups myself.

Top 10 SDG problem-based sector opportunities (Southeast Asia and Pacific – 2026)

• Sustainable aquaculture and ocean health (SDG 14: Life below water):

  • Problem: Overfishing, marine pollution, and unsustainable farming practices.

  • Opportunity: AI-driven precision aquaculture, sustainable feed alternatives, ocean plastics recycling tech, and mangrove restoration monitoring.

  • Actionable insight: Focus on scalable, low-cost monitoring solutions for small-scale fishers or developing alternative protein sources from sustainable marine resources.

• Resilient agri-food supply chains (SDG 2: Zero hunger and SDG 12: Responsible consumption):

  • Problem: Post-harvest loss, inefficient distribution, food waste, and climate vulnerability.

  • Opportunities: Cold chain logistics optimisation, farm-to-consumer digital platforms, food waste valorisation (upcycling), climate-resilient crop tech.

  • Actionable insight: Develop localised digital marketplaces connecting smallholder farmers directly to urban consumers, reducing intermediaries and waste.

• Decentralised renewable energy access (SDG 7: Affordable and clean energy):

  • Problem: Energy poverty in remote areas, grid instability, reliance on fossil fuels.

  • Opportunity: Microgrid solutions, pay-as-you-go solar for rural households, smart battery storage, ocean/hydrokinetic energy innovations.

  • Actionable insight: Focus on modular, easily deployable renewable energy kits for islands and remote villages, paired with innovative financing models.

Also Read: As the demand for energy soars, climate tech is here to save the day

• Circular economy for plastics and waste (SDG 12: Responsible consumption):

  • Problem: Massive plastic pollution, inadequate waste management infrastructure.

  • Opportunity: Advanced recycling technologies, alternative packaging materials (biodegradable/compostable), waste-to-energy solutions, and informal sector integration for waste collection.

  • Actionable insight: Create platforms that connect waste generators with recyclers, or develop localised micro-factories for upcycling plastic waste into valuable products.

• Nature-based climate adaptation (SDG 13: Climate action and SDG 15: Life on land):

  • Problem: Rising sea levels, extreme weather events, deforestation, and biodiversity loss.

  • Opportunity: Ecosystem restoration tech (e.g., coral, mangrove), early warning systems for natural disasters, sustainable land use planning, carbon sequestration solutions.

  • Actionable insight: Leverage satellite imagery and AI to monitor ecosystem health and identify critical areas for restoration or protection, offering this as a service to governments or NGOs.

• Inclusive digital healthcare (SDG 3: Good health and well-being):

  • Problem: Limited access to healthcare in rural areas, shortage of medical professionals, and high costs.

  • Opportunity: Telemedicine platforms, AI diagnostics for primary care, remote patient monitoring devices, and health literacy tools.

  • Actionable insight: Develop culturally sensitive mobile health applications that provide preventative care advice and connect patients in remote areas to medical consultations.

• Water security and sanitation (SDG 6: Clean water and sanitation):

  • Problem: Water scarcity, contaminated sources, inadequate sanitation infrastructure.

  • Opportunity: Smart water management systems, affordable water purification tech, decentralised sanitation solutions, wastewater treatment innovations.

  • Actionable insight: Focus on low-cost, decentralised water purification systems adaptable for community use in areas with poor water quality.

• Future of education and skills (SDG 4: Quality education):

  • Problem: Skill gaps, unequal access to quality education, and outdated curricula.

  • Opportunity: Personalised learning platforms, vocational training for green jobs, AR/VR for experiential learning, digital literacy tools for underserved communities.

  • Actionable insight: Create engaging, gamified learning modules focused on essential 21st-century skills and sustainability topics, accessible via low-bandwidth connections.

Also Read: How to tackle climate change by choosing a career in cleantech

• Sustainable urban mobility (SDG 11: Sustainable cities and communities):

  • Problem: Traffic congestion, air pollution, inefficient public transport.

  • Opportunity: Electric vehicle charging infrastructure, micro-mobility solutions (e-bikes, scooters), intelligent traffic management, last-mile delivery optimisation.

  • Actionable insight: Develop smart routing and demand-response platforms for public transport in rapidly growing secondary cities, reducing congestion and emissions.

• Financial inclusion and digital economy (SDG 8: Decent work and economic growth):

  • Problem: Lack of access to banking, credit, and digital payment systems for informal workers and rural populations.

  • Opportunity: Blockchain-based microfinance, digital wallets, identity verification for financial services, e-commerce platforms for local artisans.

  • Actionable insight: Build simple, secure digital payment solutions tailored for informal vendors and small businesses, enabling them to participate more fully in the digital economy.

Call to action

The problems are clear, and the opportunities for impactful innovation in SE Asia and the Pacific are immense. If you’re building a solution in any of these critical SDG-aligned sectors, let’s connect.

DM me to arrange a call to discuss how your startup can capitalise on these opportunities.

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Most founders start the day the same way: clearing emails in the morning, moving through back-to-back meetings by midday, and making dozens of small decisions in between. By the end of the day, the calendar is full and the inbox is quieter and yet, progress feels harder to point to. Time is spent coordinating, catching up, and reprocessing information rather than doing the work that actually moves the business forward.

For solo founders, project managers, marketing teams, and small business owners who spend most of their day inside Google Workspace, this pattern is familiar. The tools are there, but the work often feels heavier than it should.

AI is often positioned as the answer, yet many tools feel disconnected from how work actually happens. They sit outside existing workflows or require teams to adopt new platforms just to get started. What’s missing is context. This is where Gemini takes a different approach, bringing AI directly into the tools teams already rely on.

Google Workspace supports everyone from solo founders to 50-person teams who run their businesses inside Gmail, Docs, Sheets, and Meet every day. This article looks at how those teams are using Gemini within their existing Workspace tools to reduce everyday friction with practical examples that show how work can become clearer, faster, and more focused without changing how teams operate.

Context-based operations support with Gemini

Rather than introducing a new tool to learn, Gemini is built directly into Google Workspace, working inside the same Gmail, Docs, Sheets, Meet (and more) environments teams already use every day. The interface stays familiar, as do file access, permissions, and sharing rules. What changes is how quickly teams can move through information.

Within each Workspace app, Gemini appears in a side panel that provides quick summaries, drafts, and contextual help without pulling users out of their task. It can surface key points from long email threads, suggest first drafts in documents, or help organise information in spreadsheets—all while staying anchored to the work already in progress.

For questions that span multiple tools, the Gemini app adds a broader layer of context. It allows teams to connect information across Drive, Gmail, and Docs—such as locating a specific proposal and summarising related conversations—without manually searching through files or inboxes.

For deeper work, tools like NotebookLM and Google Vids extend this support further. NotebookLM helps teams synthesise research and internal documents into source-backed insights, while Google Vids makes it easier to turn ideas and presentations into simple video content. Together, these tools position Gemini as an integrated layer across Workspace, supporting day-to-day execution as well as moments that require deeper focus.

Also read: AI for SMEs: Indonesia and Google partner on Gemini Academy

Case study #1: Addressing email overwhelm and the endless inbox battle

For most teams, this shift becomes most visible in the place where work begins and ends each day: the inbox. You step out of a meeting to dozens of unread emails—clients waiting on updates, internal threads needing replies. Half an hour goes into catching up, another into drafting responses, and by lunch, little of the work that actually moves the business forward has started. For many founders and small teams, email has become a daily bottleneck.

Gmail with Gemini reduces that friction. Instead of scanning long threads, teams can use smart summaries to surface key decisions, action items, and open questions in seconds. A prompt like “Catch me up on the Project Atlas emails” highlights what matters, with links back to the source for quick verification.

When replies are needed, Gemini supports context-aware drafts that draw from past emails, Drive files, and recent meeting notes. Responses reflect existing communication styles and are grounded in the latest information, saving time without sacrificing clarity or tone. Priority emails are easier to manage as well, with intelligent labeling, reminders, and follow-ups helping important messages rise to the top.

The impact is practical. Customer-facing teams may reduce drafting time while staying responsive. For most teams, it starts small. They begin the day by asking Gemini to summarise emails by project, let it adapt response templates for client replies, and use the Gmail side panel to quickly check context from Drive and earlier conversations. 

Ready to conquer your inbox? Explore what Google Workspace with Gemini can do for you.

Case study # 2: This meeting should have been an email (or document)

However, much of what fills the inbox starts earlier during meetings.

The morning inbox often reflects what happened the day before. Many of the follow-up emails waiting for attention are the result of meetings where decisions weren’t clearly captured. What felt like a productive call at midday shows up the next morning as more work to untangle.

Back-to-back meetings are often the source of a good problem; high productivity means meeting targets in the long run. However, as modern work requires coordination between cross-border teams, there is a need for reduced friction in communicating. Teams need to be more effective in multi tasking notes, tracking action items, and capturing decisions in real time. This reduces the need for follow-ups, and ensures that everyone is on the same page with next steps.

Google Meet with Gemini helps to reduce this friction at the source. With “Take notes for me” enabled, Gemini automatically captures key discussion points as the meeting unfolds, highlights decisions, and identifies action items. Instead of raw transcripts, teams receive structured summaries that reflect what mattered without relying on one person’s notes.

These summaries are saved directly to Drive and easy to share. For remote teams, real-time translated captions, available across more than 60 languages, help ensure everyone has access to the same information, regardless of location or language.

Where Gemini’s value compounds is often seen after the meeting. Summaries can be referenced when drafting follow-up emails in Gmail or pulled into project updates in Docs, reducing repetition and preserving context across tools. The same information no longer needs to be retyped, re-explained, or reinterpreted. 

As a result, teams spend less time documenting and more time listening. Participants stay present in conversations, knowing decisions and next steps are being captured accurately. More importantly, fewer meetings are needed to revisit or clarify decisions.

Make every meeting count. Try Google Workspace with Gemini features today.

Case study # 3: Streamlining expansion without the learning curve

To stay ahead, founders often need to expand their client base to unknown territories. Researching a new market or vendor often turns into a pile of industry reports, docs, and links. It often slows teams down because relevant information is scattered across too many sources.

NotebookLM functions as a personal research workspace built around your own materials. It helps by understanding dense material and synthesising data into actionable insights. Teams can upload PDFs, Google Docs, Slides, and web links—bringing together internal strategy documents, market research, competitor information, and customer feedback in one place. Each source can handle large volumes of text, allowing teams to work with full reports rather than summaries or excerpts.

What sets NotebookLM apart is that it stays grounded in source material. Every response is generated strictly from the documents uploaded and includes citations that link back to the original source. This makes it easier to verify insights, trace decisions to evidence, and avoid “hallucinated” conclusions. 

Multiple sources (with the processing power of up to 500,000 words per source) can be referenced together, allowing teams to synthesize insights across documents without manually cross-checking. When reading isn’t practical, NotebookLM can take its findings and convert it into an audio overview which offers a way to absorb complex material on the move.

In practice, teams use NotebookLM to speed up decision-making. During strategic planning, financial reports and market analyses are distilled into clear summaries backed by data. For vendor evaluations, RFPs, pricing, and compliance documents can be compared side by side. Sales teams turn product documentation and competitor materials into clear positioning points tailored to specific customer segments. 

The shift is subtle but meaningful. Instead of spending days moving between documents, teams move more quickly from research to interpretation. Research moves faster and decisions are made with clearer reference to evidence without adding a new workflow or learning curve.

Also read: Architecting AI Factories to solve the enterprise data paradox

Addressing the invisible tax on modern work with real results

Small implementation efforts can compound into tangible real results down the line. The progress becomes tangible as AI is integrated over time to real workflows. 

This is where Gemini operates quietly within Google Workspace. It supports the repetitive parts of work—summarising threads, drafting first passes, organising notes, and carrying context across email, meetings, and documents—while leaving judgment, creativity, and decision-making firmly with the team. Everything remains reviewable and adjustable, functioning as a faster starting point rather than a final answer.

In practice, this approach has supported organisations operating at very different scales. In the Philippines, Google Workspace helped a regional convenience store chain expand rapidly during the pandemic, enabling remote training for over 1,000 workers, supporting far-flung communities, and improving operational efficiency.

Further, a large logistics and last-mile delivery provider uses Workspace to coordinate a 24/7 network across tens of thousands of employees, maintaining security while improving daily efficiency.

Finally, an agricultural technology and irrigation equipment manufacturer connected teams across rural regions, allowing faster coordination between field staff and leadership and enabling more timely support for farmers.

Across sectors, the pattern is consistent: when work is clearer and better connected, teams move faster with less friction.

Start tomorrow with a small step

Adopting AI does not require a big shift or a new way of working. It can start with something small and immediately useful.

Three Gemini prompts to try today

• In Gmail: “Summarise the emails from [client name] this week and highlight any action items.”
• In Docs: “Write a one-paragraph blog post introduction about the importance of productivity for small teams.”
• In Meet: During a meeting, turn on Take notes for me to automatically capture key points, decisions, and next steps.

Pay attention to what changes when you recover even 30 minutes of your day.

Over time, the teams that benefit most will be the ones that integrate AI thoughtfully, using it to support how they already operate rather than replace it. With Gemini built into Google Workspace, the work remains yours—only with less friction, clearer context, and more time to focus on what matters most.

Ready to supercharge your Workspace? Gemini is available to Google Workspace customers on the Starter, Standard, and Plus plans. For teams looking to experience Gemini fully integrated across Gmail, Docs, Sheets, Meet, Drive, and more, the Standard plan offers the most complete balance of features. Visit their website to upgrade or learn more.

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When Malaysian edutech startup Pandai first launched in 2020, its ambition was modest but clear: help students learn better outside the classroom through personalised digital support aligned with the national curriculum. Five years on, that focus on product depth rather than aggressive marketing has helped Pandai scale to more than one million users — and earn a place in the London School of Economics’ (LSE) prestigious 100x Impact cohort.

Pandai is one of four Southeast Asian ventures selected for the latest 100x Impact programme, an LSE initiative that identifies high-impact organisations with the potential to improve the lives of one billion people. Chosen from more than 800 global applicants, the cohort spans sectors including education, health, and income inequality, and features both for-profit and nonprofit models that are already delivering measurable results at scale.

For Pandai, participation in 100x Impact represents validation of a strategy that has always prioritised educational outcomes alongside sustainable growth. “Since Pandai started, the focus has always been on personalising the offering,” says Khairul Anwar, CEO and co-founder of Pandai, in an interview with e27. “Everything in Pandai — quizzes, tests, flashcards and gamified activities — is tailored to each student’s progress and performance.”

Unlike one-size-fits-all learning platforms, Pandai dynamically adapts its content. Even students from the same class using the app will have different learning journeys, depending on their strengths and weaknesses. The platform covers the full school curriculum for primary and secondary students aged seven to 17, combining curriculum-aligned content, AI, and gamification to drive engagement and retention.

That emphasis on product quality has played a critical role in Pandai’s user acquisition strategy. In its first year, the edutech startup invested nothing in paid marketing, instead relying on organic growth driven by word of mouth and social sharing. Even today, paid advertising plays a minimal role. “Our customer acquisition cost is very, very low,” Khairul says.

Also Read: Why Southeast Asia’s edutech must go beyond chatbots to truly transform learning

Most new users discover Pandai organically through recommendations from friends, social media or search, a key factor behind its strong SEO performance as an edutech startup. Affiliate programmes, where existing students invite peers, and a network of “Pandai consultants”—typically teachers and parents—further support growth. Over the past two years, Pandai has also expanded into B2B partnerships, working with schools, corporates and foundations to subsidise access for underserved communities.

This multi-channel approach has helped Pandai reach scale without compromising its social mission. About 30 per cent of its users come from rural or underprivileged backgrounds, a figure the company is particularly proud of. To support learners with limited connectivity, Pandai has developed an offline mode that allows students to preload content and continue studying even with intermittent or no internet access.

Pandai’s business model reflects this balance between impact and growth. The platform operates on a freemium basis, offering a free version that is available indefinitely. Paid subscriptions unlock features such as deeper performance analytics, interactive content and live classes. “The small portion of students who are paying are essentially subsidising the rest,” Khairul explains. “That’s how we stay true to our mission while remaining sustainable.”

The result is a rare combination in the edutech startup space: rapid scale paired with strong retention. Pandai’s monthly retention rate has improved from 60 per cent in its early days to an average of 94 per cent today, driven by continuous improvements in content, technology and user experience.

Behind the product is a founding team deeply shaped by education. The founders were schoolmates who benefited from scholarships and supportive learning environments, experiences that informed their decision to build an education-focused company. “We saw firsthand how education can transform lives,” Khairul says. “That’s why education felt like our calling.”

Also Read: TikTok and the future of education: How Generation Alpha actually learns

Support from external organisations has also been crucial. Programmes such as LSE’s 100x Impact provide frameworks and mentorship to help Pandai refine its long-term “impact endgame” — how it can scale responsibly while deepening outcomes for learners. For Pandai, being part of the 100x Impact cohort is less about prestige and more about amplification. “We cannot take credit for everything ourselves,” Khairul adds. “A lot of organisations around us have supported us to reach more students.”

As Southeast Asia emerges as a hub for social innovation, Pandai’s journey highlights how an edutech startup can grow by staying anchored to its mission. By focusing on personalised learning, low-cost user acquisition and inclusive access, Pandai is positioning itself not just as a fast-growing platform, but as a scalable solution to education inequality — one student at a time.

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Image Credit: Pandai

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The first wave of freelancing in Asia was about independence — choosing your clients, your hours, and your projects. The second wave, accelerated by the pandemic, brought a surge of creators, solopreneurs, and portfolio careers.

Now, a third wave is coming. And this time, it is shaped by AI.

For creative freelancers, the question is no longer “Will AI take my job?” but “What will my job become?” As someone who has spent over a decade championing the freelance space through CreativesAtWork and now building GenAI production workflows at Dear.AI, we are confident that we are heading towards a future where the definition of freelance work is being rewritten. We are no longer just “gig workers.” We are becoming architects of ideas.

From gig work to intelligent work

Freelancing has always been about independence. Yet, too often, that independence comes at the cost of stability. Freelancers traded security for flexibility, managing fluctuating income, burnout, and a constant chase for the next gig.

AI is changing that equation. It is giving independent professionals especially the creatives, the ability to operate with the efficiency and capability of a small agency — but without the overheads.

Instead of competing on price or speed, freelancers can now truly compete on value — by combining human insight with AI-driven execution. We are seeing the rise of “intelligent freelancers” (ie. professionals who use AI not just to do more, but to think differently).

Freelancers must rethink revenue models

AI compresses production time dramatically. If you are still billing by the hour, it will be a bad news! Your income will shrink as projects become faster to produce. New revenue models are not optional — they are essential. The new revenue models could be a combination of the following:

• Value-based pricing: Charging for business outcomes rather than hours.
• Licensing instead of one-offs: Designers, videographers, and writers across Asia are experimenting with licensing templates, story frameworks, and reusable assets.
• Monthly creative subscriptions: Clients access a creator’s brain and capabilities, not individual tasks.
• Revenue-share partnerships: More creators are co-developing campaigns, original IP, or brand content with profit-sharing models — especially in the creator and media economy.

Insight, originality, and taste will remain premium. Freelancers need to rethink their revenue models.

Also Read: Singapore’s workforce is facing its biggest reset yet and AI is forcing the shift

The new skillsets for freelancers

Technical literacy is now the baseline. To thrive in the new freelance economy, you need to level up in areas AI cannot touch:

• Creative direction: AI generates a thousand options; you are the one who decides what has meaning.
• Cultural curation: Asia is a mosaic of nuance. AI can remix culture, but it cannot originate the “soul” of a local story. Your cultural intuition is your greatest asset.
• Workflow orchestration: Knowing which AI tools to chain together is the new “mastery of the craft.”

The human advantage in an automated Asia

Asia’s freelance economy will not be shaped by AI tools alone. It will be shaped by:

• Cultural intuition
• Lived experiences
• Empathy
• Community roots
• Multilingual storytelling
• Emotional intelligence
  

AI can replicate style, but not soul. It can remix culture, but not originate it. As AI reduces the burden of technical labour, the value of human perspective increases — especially in a region as culturally rich and diverse as Asia.

A future where freelancers lead, not follow

Asia is uniquely positioned to lead this 2.0 freelance economy. We have a young, digitally native population and a booming creator economy hungry for storytelling. But remember: AI can replicate style, but it cannot replicate soul. It lacks lived experience, empathy, and community roots. As the burden of “technical labour” decreases, the value of our unique human perspective increases.

Conclusion

The freelancers who thrive, in the future, will be those who embrace hybrid identities — blending creativity, strategy, technology, and empathy. The future does not belong to the fastest adapter of tools. It will belong to the one who uses AI to become more creative, more human, and more original. Because in the age of AI, the most powerful work does not come from automation. It comes from amplified imagination.

The post The freelance economy 2.0: In the age of AI appeared first on e27.

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When I run workshops for older adults, I see the same moment every time. A trembling hand hovers over the keyboard. Someone looks up and whispers, “Teacher, if I press this key, will it spoil the computer?”

They do not dare to touch the screen. They worry that one wrong click will destroy everything. And when I tell them gently, “You can just delete it,” they still hesitate.

It is not the machine they fear. It is embarrassment.

Many midlife and senior learners are not afraid of technology itself. They are afraid of looking foolish, of doing it wrong, of being judged by others who “know better.” They do not want to risk fun for judgment. Or as one of my learners said with a laugh, “Jude who? Why risk fun for judgment?”

That small sentence says everything. Underneath every hesitation lies the fear of being laughed at instead of supported.

Where the fear begins

For those of us who grew up in a world of pens and paper, technology feels like a foreign language. Every update changes the grammar. Every new app comes with a new accent.

When you are not fluent in that language, silence feels safer than speaking. That is why many older adults say, “I cannot learn.” They simply do not want to feel small again.

The problem is not ability. It is confidence.

Learning needs safety, not speed

When seniors enter an AI class, what they need most is not information. They need a space where it is safe to try, fail and laugh.

One of my students once said, “I did not know I was allowed to make mistakes here.” After that, she started experimenting with voice-to-text, image generation and storytelling. Her progress was not because of the tool but because of the environment.

When we remove judgment, curiosity returns. And when curiosity returns, learning becomes natural.

Also Read: The second act: How midlifers are reinventing themselves with AI

Reframing what learning means

In school, mistakes are punished. But in creativity, mistakes are how discovery begins.

Adults need to unlearn the belief that knowledge only comes from perfection. AI actually rewards trial and error. It invites us to ask, test and adjust.

You cannot break AI by asking questions. But you can break your own confidence by not trying at all.

Building bridges between generations

Younger people often forget that older learners want to participate. They just need someone patient enough to walk with them.

When a teenager teaches a parent how to use AI, both grow. The younger learns empathy and patience. The older learns courage and self-trust.

It is not about who knows more. It is about discovering together.

Creating confidence through small wins

Confidence is built through small successes. Each time an older learner writes a story, generates a picture or records their voice, they prove they can still learn.

The key is to start small. Ask one question. Try one feature. Share one post. Every attempt removes fear and builds trust, not only in AI but in their own ability to grow again.

The gentle reminder

Technology will always evolve, but our curiosity can evolve with it. If we treat AI as a bridge rather than a barrier, it can reconnect generations and rebuild confidence.

The fear of breaking something is real, but the greater loss is never pressing the button at all. It is not about perfection. It is about participation.

So go ahead. Press the key. Delete. Retry. Post. Because courage begins with a single click.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.

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