Social media platforms and trends have transformed public PR. From spontaneous posts to viral videos, social media has significantly changed the way brands and businesses connect with consumers. 

Social media and public relations (PR) used to operate in different spheres. PR focused on managing reputations and getting media coverage, while social media was all about direct interaction with audiences. But today, the two are inseparable. Social media marketing has become essential for PR success, helping brands amplify their message, build trust, and connect with audiences like never before.

The influence of social media on public relations

Brand presence and visibility

Social media has significantly expanded brand visibility while enabling organisations of all sizes to leverage storytelling and foster meaningful community engagement. Unlike traditional media, which often demands substantial time and financial investment to secure coverage, social platforms offer direct access to target audiences. This allows brands to deliver tailored content that resonates with their followers and extends their reach beyond conventional media channels.

Understanding how audiences engage with content across different platforms is essential for effective public relations. Social media’s cost efficiency and capacity to reach niche audiences make it a critical component of modern PR strategies. When used strategically, it enables brands to build trust and credibility while strengthening their presence, visibility, reputation, and overall influence.

Crisis management 

Social media plays a critical role in brand crisis management due to its immediacy, extensive reach, and interactive nature. During a crisis, these platforms provide direct access to large audiences, allowing brands to respond swiftly and manage situations more effectively. This real-time communication enables PR professionals to shape the narrative, limit misinformation, and preserve trust with stakeholders and communities.

Compared to traditional public relations, social media enables faster, more direct communication with a broader reach and higher engagement. While conventional PR relies on formal channels such as press releases that may take time to circulate, social media allows for immediate responses. Integrating social media into PR strategies is particularly effective during crises, supporting brand reputation management, reinforcing credibility, and strengthening trust.

Content distribution

Social media has reshaped how public relations content is distributed, enabling brands to amplify their messaging far beyond the limits of traditional media. These platforms facilitate engagement with diverse audiences while supporting multiple content distribution approaches.

Also Read: Survey: Asia Pacific entrepreneurs over 45 redefine the unicorn dream

Unlike traditional PR materials such as press releases, which audiences typically consume passively, social media encourages active participation through likes, comments, and shares. Audience engagement also varies across platforms, making channel selection essential.

For instance, Instagram is well-suited for visually driven storytelling, while TikTok’s viral potential can rapidly boost brand awareness among younger demographics. LinkedIn prioritises professional and industry-focused content, Facebook supports long-term community building and message dissemination, and X enables real-time communication and hashtag-driven campaigns, particularly during breaking news or crises.

Data insights

Social media metrics provide PR professionals and marketers with clear insights into campaign performance, audience engagement, and brand perception. Unlike traditional public relations, where measuring return on investment can be difficult, social media offers quantifiable data that reveals what is effective and what requires adjustment. These insights enable data-driven realignment of PR strategies.

Social media also allows PR specialists to extract valuable insights across owned, paid, and earned media channels:

• Owned media: Brand-controlled platforms such as websites, blogs, and social media channels play a central role in PR. These channels enable direct message distribution while offering analytics that help refine content and improve performance.
• Paid media: Social media advertising, sponsored posts, and boosted content extend reach and target specific audiences. Performance metrics from paid media support campaign optimisation through improved audience targeting and more efficient ad spend.
• Earned media: Organic engagement, including mentions, shares, user-generated content, and influencer collaborations, strengthens credibility and trust. Earned media often signals authentic audience endorsement beyond paid promotion.

By leveraging these insights, PR professionals can optimise communication strategies, strengthen audience engagement, and drive more measurable outcomes for their organisations.

Influencer partnership

Influencer partnerships have become a key component of modern public relations strategies, involving collaborations with individuals who maintain large and highly engaged social media followings. Through authentic content and personal endorsements, influencers can significantly shape audience perceptions, influence behaviour, and impact purchasing decisions. 

Collaborating with influencers whose values and audiences align with a brand’s mission enables companies to increase visibility, drive deeper engagement, and strengthen overall brand awareness.

Also Read: APAC entrepreneurs are shifting the startup narrative beyond youth–and that is a great thing

Storytelling

Storytelling on social media is a powerful tool in PR campaigns, enabling brands to establish emotional connections with their audiences. By crafting narratives that reflect their mission and values, businesses can make messaging more relatable and memorable. For instance, sharing stories of individuals who have been positively impacted by a company’s products or services can resonate strongly with consumers.

Effective storytelling also humanises organisations, fostering a sense of connection with its audiences. Through authentic and compelling narratives, brands can create lasting emotional impact, build loyalty, and enhance public perception beyond what traditional marketing can achieve.

Social media and public relations: Ethical relations

Both public relations and social media practices rely on a strong ethical foundation. Transparency in influencer collaborations and clear communication during crises are essential for establishing trust, while accurate and timely messaging helps prevent the spread of misinformation. Undisclosed paid promotions can undermine credibility, and mishandling user data can result in legal issues and damage a brand’s reputation.

Upholding these ethical standards is critical for building trust and reinforcing brand credibility. PR professionals and social media marketers must consistently adhere to these principles to maintain reliable and trustworthy relationships with their audiences.

Conclusion

Integrating social media into public relations strategies is no longer optional. It is essential for enhancing brand visibility, managing crises, distributing content, and deriving actionable insights. When combined with influencer partnerships and storytelling, social media amplifies PR efforts by driving engagement and strengthening connections with target audiences.

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When I first sold my company in 2011, I asked myself, What’s next? Start another startup, join a startup, or join an enterprise?

Instead, I invested in several startups, mentoring the Founders, helping others start their businesses, and facilitating exits.

Fast forward 14 years, and the world has changed so much that Blockchain, AR, VR, and AI have dominated businesses. So now, at 50 years old, what is next after three heart ops?

I was blessed to have the opportunity to work with some of the most brilliant people in the business world, as Mentors, Advisors, and they gave me a lot of guidance in life, too. For the past few years, I have been working with many to scale our own group of companies by scaling our clients (Startups and SMEs) business rapidly. It is fulfilling, fun, and at times difficult, but what isn’t in life?

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Generative AI is now a default ingredient in startup narratives, but the lasting shift isn’t that founders can add a chat feature or generate marketing copy. Generative AI in startups is changing three fundamentals: how quickly products are built, what kinds of products are viable, and what “defensibility” looks like when models are widely accessible. 

At the same time, the hype cycle has created noise: inflated expectations, shallow demos, and ambiguous claims of “AI-powered” differentiation. A clearer view is to ask a more operational question: what has structurally changed in the startup playbook that is unlikely to revert? 

Below are the most meaningful changes that are vendor-neutral, practical, and grounded in the realities of building companies. 

Speed has moved up the stack: From code to decisions 

Startups have always been speed machines. What’s different is where speed is now being created. 

• Product iteration: Teams can prototype UI copy, onboarding flows, help content, and even basic feature scaffolding faster than before. This compresses time from idea → test → feedback. 
• Research and synthesis: Founders and PMs can summarise customer calls, draft PRDs, and explore competitive landscapes with less overhead to free humans to validate assumptions rather than generate first drafts. 
• Support and ops loops: Early-stage teams can triage inbound, draft responses, and extract structured signals from unstructured text. 

The practical result is not “AI replaces teams,” but that small teams can run more experiments simultaneously, raising the bar for execution speed across the ecosystem. 

“Software as a workflow” is replacing “software as a screen” 

A meaningful pattern in generative AI in startups is a shift from building interfaces to building outcomes. 

Traditional SaaS often required users to configure dashboards, set rules, and learn the product. Generative systems allow startups to design products that: 

• Accept messy inputs (emails, docs, notes)
• Interpret intent
• Produce a recommended output (a draft, a classification, a plan)
• Optionally execute actions via integrations

This reframes product value around “time-to-outcome” rather than “feature depth.” It is also why many new products look like copilots or agents: users want fewer clicks, not more configurable screens. 

Also Read: How marketing will be enhanced through generative AI

Distribution advantages are shifting from feature depth to trust 

When core model capabilities are broadly available, feature-level differentiation erodes faster. Startups are learning that defensibility increasingly comes from: 

• Proprietary data loops: unique user interactions that improve outputs over time (with consent and governance). 
• Workflow integration: deep embedding into the daily tools and systems where work happens. 
• Reliability and evaluation: consistent performance in real conditions, not demo conditions. 
• Compliance and auditability: the ability to explain outputs, control access, and meet regulatory constraints. 

In short, the moat moves from “we have AI” to “we can be trusted to run AI inside your real workflow.” 

This is particularly important given the scale of investment and experimentation underway. Stanford’s AI Index reports that private investment in generative AI reached US$33.9B in 2024 and that organisational AI usage rose sharply (e.g., 78 per cent of organisations reported using AI in 2024).  

The talent model is being rewritten (smaller teams, different roles) 

Generative AI changes hiring math. Startups can sometimes achieve output previously requiring larger teams, especially in content-heavy or operations-heavy functions. But that doesn’t mean “fewer people overall” as a universal truth. It means different skill mixes: 

• More emphasis on product thinking, domain knowledge, and systems design 
• More need for data discipline (taxonomy, labelling, quality checks) 
• More demand for “evaluation thinking” (how to test AI behaviour, identify failure modes, measure drift) 

In practice, early teams that treat evaluation and quality as first-class engineering concerns tend to move from novelty to reliability faster. 

MVP barriers are lower, but the “real product” bar is higher 

Yes, it is easier to build something impressive quickly. But that cuts both ways. If everyone can ship a compelling demo, the market becomes less forgiving of products that fail under real-world complexity. 

The gap between demo and durable product often shows up in: 

• Handling edge cases and ambiguous inputs
• Controlling hallucinations and overconfident outputs
• Building proper permissioning and data governance
• Ensuring consistent performance and latency

This is why “AI MVPs” are common, but “AI products that survive procurement” are harder. Startups that win are usually the ones that invest early in reliability, not the ones that chase novelty. 

Pricing and unit economics are becoming model-aware 

Another concrete change in Generative AI in startups is that unit economics now depend on usage patterns and inference costs, not only hosting and support. 

This pushes founders to think early about: 

• Which workflows require high-quality generation vs lightweight automation
• Caching and reuse of outputs
• Controlling token or compute spend in “always-on” experiences
• Aligning pricing with the cost-to-serve curve

The market’s growth expectations amplify this pressure. Statista’s forecasts for AI market expansion are frequently cited in industry analysis and illustrate why investors and buyers expect AI-enabled efficiency gains that are often faster than organisations can operationalise them.  

Also Read: 9 ways to use generative AI for PR

Risk is no longer only “product risk,” it’s now “system and policy risk” 

Generative AI introduces new categories of startup risk that are business-critical: 

• Data exposure: accidental leakage of sensitive data through prompts, logs, or training pipelines 
• IP uncertainty: rights and provenance questions around training data and generated outputs 
• Safety and misuse: harmful content, fraud enablement, and social engineering risks 
• Regulatory change: compliance requirements evolving unevenly across regions and industries 

The biggest change: Startups can compete on “cognitive throughput” 

Stepping back, the most durable impact is that startups can increase their “cognitive throughput”, which is the amount of analysis, drafting, synthesis, and iteration they can perform per unit time. 

That doesn’t guarantee product-market fit. It doesn’t replace customer empathy or distribution. But it does compress cycles and expand what a small team can attempt, especially in domains where the work is language-heavy, document-heavy, or decision-heavy. 

Economically, this aligns with broader forecasts that generative AI could contribute material productivity gains over time, depending on adoption and how work is redesigned. 

Closing view: Past the hype, the winners will look “boring” 

In the next phase, the most successful Generative AI in startups stories will sound less like “we use GenAI” and more like: 

• “We deliver a specific outcome reliably.” 
• “We prove it with measurable business impact.” 
• “We control the risks.” 
• “We integrate so deeply that switching costs become operational, not emotional.” 

Hype fades. Operational advantage compounds!

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The narrative surrounding cryptocurrency is undergoing a fundamental transformation: a shift away from volatile speculation toward a more stable, utility-driven role within global financial infrastructure.

The 2025 Endeavour Catalyst Annual Report identifies emerging markets as the primary drivers of this change, particularly through the adoption of stablecoins and tokenised assets. Where legacy systems struggle — for payments, savings and cross-border transfers — digital assets are increasingly serving practical needs.

Solving the volatility crisis with “dollars as a service”

In many emerging markets, the appeal of stablecoins is straightforward: they preserve purchasing power and lower the friction of moving value across borders. Regions — where local currencies are volatile, or banking infrastructure is costly and slow — have shown robust adoption of dollar-pegged digital assets. Executives such as Farooq Malik of Rain describe their work as providing “dollars as a service”: enabling users to receive, hold, and send value in a stable unit relative to their everyday spending needs.

Also Read: How SMEs are using stablecoins to beat currency swings

This is not the 2021 speculative boom replay. The trend now is infrastructure-first: firms that provide rails for payments, custody, settlement and tokenisation are the companies capturing long-term value.

The Standard Chartered-cited data estimate that up to US$1 trillion could eventually move from traditional bank deposits in emerging markets into stablecoins, illustrating the scale of potential change. Infrastructure builders — from firms supporting stablecoin issuance to platforms enabling tokenised treasury and trade — are central to this transition.

From speculation to infrastructure: expert consensus

Experts in the Endeavor Catalyst report argue that crypto has shifted “from speculation to infrastructure.” This trajectory began earlier in the last decade, when companies began bridging bank-grade services and crypto rails; by 2025, the focus had shifted to embedding crypto primitives into real-world financial flows. The winners are those positioning themselves as platforms for commerce and payments, rather than venues for retail trading.

Stablecoin-powered payments, tokenised assets, and programmable money are being deployed to solve persistent frictions: remittance costs, long settlement windows for cross-border trade, limited access to dollar-denominated savings, and the challenge of onboarding small and medium enterprises into digital global markets.

Southeast Asia: why the region matters

Southeast Asia deserves special attention in this new phase. The region combines high mobile penetration, large remittance flows, substantial informal economies, and a sizeable unbanked or underbanked population — a fertile environment for stablecoin-based payments and tokenised financial services.

Key dynamics in the region include:

• Remittances and diaspora flows: Several Southeast Asian economies are materially remittance-dependent. Workers abroad sending money home require low-cost, fast, reliable transfers. Digital remittance models that use stablecoins for on-chain settlement and local rails for off-ramp can reduce fees and settlement times compared with correspondent banking.
• High mobile-first adoption: Many consumers in the region access financial services primarily through smartphones and e-wallets. That digital stack lowers the marginal cost of integrating tokenised payments or dollar-pegged digital assets for everyday transactions and merchant acceptance.
• Large informal and MSME sectors: Micro, small and medium enterprises (MSMEs) often lack access to credit and traditional FX hedging. Tokenisation and programmable payments can create new on-ramps for these businesses to participate in borderless trade, invoice financing and supply-chain finance.
• Regulatory stewardship and regional hubs: Singapore’s continued positioning as a regulated digital asset hub — with licensing, industry sandboxes and a clear engagement model between regulators and firms — makes it a nexus for institutional-grade infrastructure. Other regional regulators have been evolving their approaches to virtual assets and payments, balancing consumer protection with innovation.

Concrete regional patterns (without overstating)

Several narrative threads from the Endeavor Catalyst report map directly onto Southeast Asian realities:

• Digital remittance players as blueprints: The report highlights digital remittance companies that use stablecoins as exemplars. In Southeast Asia, local and regional remittance and e-wallet firms have already experimented with more efficient cross-border settlement models. These initiatives mirror the broader trend of moving settlement onto faster, lower-cost rails while preserving local on/off-ramps for users who still transact in local currency.

Also Read: Endeavor report shows AI is eating venture capital alive

• From retail trading to B2B payments and trade finance: Startups that pivot away from retail crypto speculation toward infrastructure for B2B payments, payroll, and trade are better aligned with investor interest. Global fintech investors looking for “real-world applications” increasingly target companies focused on payments, custody, treasury, and compliance tooling — all essential for stablecoin adoption at scale.
• Banking the unbanked with regulated rails: The “dollars as a service” model can be a pragmatic way to offer dollar-like savings and payments in countries where holding physical dollars or accessing foreign currency accounts is difficult. When paired with regulated custody, transparent reserves, and robust compliance, stablecoin solutions can coexist with national monetary frameworks rather than undermining them.

Operational hurdles and the regulatory imperative

Adoption is not automatic. Practical and regulatory challenges remain:

• On/off-ramp infrastructure: For stablecoins to be useful to everyday users, reliable fiat rails and compliant local partners are necessary. This requires banks, licensed e-money issuers and regulated exchanges to work with tokenised-asset providers.
• Compliance and AML/KYC: Regulators across Southeast Asia have increased scrutiny on virtual asset service providers. Firms must embed strong know-your-customer (KYC) and anti-money laundering (AML) controls to gain institutional partners’ trust and to operate at scale.
• Reserve transparency: The credibility of dollar-pegged tokens depends on transparent, auditable reserves and governance. Markets and regulators will reward providers that regularly demonstrate backing and sound treasury practices.

What this means for Southeast Asian fintech and policy

• Startups: Firms that build payment rails, treasury services, merchant acceptance layers, payroll and remittance integrations around stablecoins and tokenised assets are best placed to capture demand. Focusing on compliance, predictable FX handling, and partnerships with incumbent players will accelerate adoption.
• Regulators: Policymakers can support beneficial outcomes by clarifying licensing regimes, enabling compliant fiat on/off-ramps, and facilitating industry sandboxes. This approach preserves monetary stability while allowing innovative payment and settlement systems to mature.
• Investors: Venture and growth investors increasingly favour enterprise-grade infrastructure and B2B propositions over retail speculation. In Southeast Asia, that translates to funding flows toward companies solving remittances, cross-border payroll, and trade settlement problems.

Conclusion

The shift from speculative trading to infrastructure use-cases is well underway, and Southeast Asia is both a beneficiary and a testbed for this transformation. Stablecoins and tokenisation are addressing real frictions — high remittance costs, volatile local currencies, and limited cross-border payment options — by offering dollar-equivalent stability combined with the speed and programmability of digital rails.

In a world of copyable AI, founders with scars win

With measured regulatory engagement, strong transparency, and partnerships across the banking and fintech ecosystem, the region could accelerate the global move toward a crypto-enabled layer of financial infrastructure that serves everyday commerce and cross-border value flows.

The full Endeavor report can be accessed here.

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A Southeast Asian fintech founder recently counted seventeen significant regulatory changes her company had navigated in three years. That’s roughly one per quarter. When asked if she believed the mental model most founders operate under—”the regulatory landscape we launch into is stable for three to five years”—she laughed. “No founder truly believes it. We just operate as if we do, because the alternative seems too complex, too expensive, too uncertain.”

That assumption cost the industry billions in 2025. Companies treating regulatory stability as a baseline learned too late that it wasn’t. Enforcement letters arrived. Compliance gaps surfaced in third-party reviews. Single regulator reinterpretations forced multi-month platform re-architectures. By then, reactive remediation costs were 5–50 times higher than proactive design would have been.

The 2026 question isn’t whether to prepare for regulatory change. It’s whether to prepare now—in architecture and organisation—or later, in crisis mode.

Regulatory velocity has shifted

Regulatory frameworks once evolved on three- to five-year cycles. That era has ended in Asia. Regulation now moves quarterly.

India’s RBI published eight major guideline revisions in eighteen months. Vietnam reinterpreted data localisation rules twice in two years. Singapore, South Korea, and the Philippines are finalising divergent AI governance frameworks. Southeast Asia’s real-time payments platform has Q3 2025 deadlines with monthly requirement shifts.

The cross-border variance matters equally. A single data classification is “personal data requiring local storage” in Vietnam, “non-essential data allowing transfer” in Indonesia, “encrypted data acceptable elsewhere” in Thailand, and “metadata exempt from localisation” in Singapore. Founders building regional products cannot assume harmonisation—they must assume divergence.

The implication: Betting that regulatory environments will remain stable through your product roadmap has <20% odds in fintech/payments/lending/AI verticals.

Also Read: Building smart: A tech founder’s guide to the semiconductor supply chain revolution

The cost of miscalculation has exploded

Regulatory fines hit record highs in 2025. Non-compliance carries existential risk, not just financial penalties. Paytm’s RBI enforcement didn’t merely fine the company—it froze operations and demolished investor confidence. Indonesia’s startup winter exposed governance weaknesses at eFishery, Investree, and TaniHub; venture-backed growth metrics couldn’t compensate. TikTok Shop’s Philippines refund dispute fine was ₱1.6 million; the reputational damage was far steeper.

The math is stark: companies embedding regulatory resilience upfront—modular architecture, continuous monitoring, cross-functional governance—spend 5–10% of their engineering budget. Companies waiting until enforcement hits pay 5–50 times that in emergency re-architecture, fines, and churn. Proactive design overwhelmingly wins.

Yet most founders operate as if regulatory stability is the default. The question worth asking: why?

Two operating models

Static regulatory design treats compliance as periodic obligations managed by legal/finance. Requirements surface at audits, are embedded as hard constraints in product logic, and are updated when enforcement pressure arrives. This worked when regulatory cycles were long. It collapsed repeatedly in 2025.

Dynamic regulatory design embeds resilience into architecture and culture from day one. Compliance is a real-time dashboard, not an annual surprise. Regulatory functions are independent microservices—rule changes, update configuration, not core products. Product teams include regulatory engineers. Organisations scan quarterly horizons and stress-test scenarios. This assumes quarterly rule changes and designs for rapid adaptation.

The difference is architectural, not attitudinal. Static design locks compliance logic into monolithic systems; every rule change is expensive, risky re-architecture. Dynamic design compartmentalises so changes affect narrow surfaces—one microservice, API gateway rule, configuration parameter—rather than entire platforms.

Three architectural moves

• First: Modular compliance services. Separate AML screening, KYC, data localisation, and refund logic into independent microservices rather than embedding throughout the platform. India mandates T+1 auto-refunds? Update refund service configuration. Vietnam reinterprets data localisation? Adjust API gateway routing rules. Core product untouched; deployment in days, not months.

Baseella, Stripe, and leading APAC payment platforms use this pattern. Upfront cost is 15–20% higher; downstream savings are orders of magnitude.

• Second: Continuous compliance monitoring. Shift from annual audits revealing surprise gaps to real-time dashboards showing compliance status across jurisdictions. Automated systems track announcements, parse changes, and flag business impact. Gaps surface within 24 hours, not audit-time (months later).

This requires operational discipline, not novel technology.

• Third: Quarterly regulatory horizon scanning. Every quarter, the CEO, legal, product, and operations review a 6–12 month forward regulatory outlook in each market. What rules are likely to change? What constraints? What contingencies? This intelligence gathering is inexpensive but requires sustained commitment.

Also Read: Starting a business in 2026: What Founders should consider before chasing capital

The organisational piece

Dynamic design cannot live in legal silos. It requires compliance engineers embedded in product teams, regulatory risk reporting to the CEO level, and incentive structures rewarding governance alongside growth.

When legal and product don’t communicate, regulatory surprises become existential. When boards learn of regulatory risk only after enforcement, there’s only crisis management, no strategy.

The 2025 survivors had one thing in common: organising around regulatory resilience as a strategic capability, not a compliance obligation.

The self-assessment

If a major market reinterpreted one core regulatory assumption tomorrow, how long to adapt?

• Months = monolithic architecture, static organisation
• Weeks = progress, but architectural debt remains
• Days = designed for regulatory change

Which markets/products depend on regulatory assumptions plausibly shifting in twelve months? If that list is long and you’re in months-to-adapt mode, your risk surface is expanding faster than your resilience.

The paradox

Regulatory resilience appears to trade off against speed. The data shows the opposite. Companies embedding resilience upfront demonstrate faster cycles (changes affect fewer surfaces), fewer surprise fines (dashboards catch problems), higher investor confidence (seen as operationally sophisticated), and lower total compliance cost (prevention beats remediation).

The paradox is real: spending more on resilience makes you faster, not slower. It transforms compliance from a growth headwind into a competitive advantage.

For 2026

Founders thriving in Asian tech over 3–5 years won’t bet on regulatory stability. They’ll have already rebuilt assumptions. Asked “What if the rules change in six months?”, they’ll have architectures and organisations answering without panic.

That requires now: auditing whether your architecture is modular or monolithic, whether your organisation scans regulatory horizons, whether incentives reward governance, and whether your board discusses regulatory risk as intensely as product risk.

Most importantly: drop the assumption that regulatory environments are stable. In Asia in 2026, they are not. The question isn’t whether regulations change. It’s whether you’ll be prepared when they do.

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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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