Deep tech startups rarely fail because the science is uninteresting or the problem is irrelevant. Many fail in the narrow stretch between a working technology and a scalable business, when capital runs out, timelines stretch, and risk shifts faster than funding models can adapt. This gap is commonly referred to as the “Valley of Death”.

What makes this phase especially lethal is not a single missing ingredient, but a mismatch between how risk actually unfolds and how it is financed, managed, and priced.

Deep tech commercialisation is fundamentally a risk allocation problem: most models misprice where technology, capital, and time actually fail, so the “Valley of Death” keeps reopening.

The deep tech risk budget

In software, the dominant risk is market risk — most companies die because nobody cares enough to pay, not because the app can’t be built. In deep tech, the risk budget flips: technology feasibility and funding structure dominate, while market risk is often more about timing than demand.

How common models shift (or ignore) risk

• Traditional VC in deep tech: Spreads bets and accepts high failure rates, but fund timelines (5–7 years) clash with 10+ year deep-tech gestation. Technology and funding risk compound, and companies often die with working prototypes but no runway.
• Corporate venture and pilots: Corporations help with adoption, but operating and technology risk remain with under‑resourced startups. Timing risk is severe: slow procurement and internal politics can strand ventures mid‑pilot.
• University spin‑outs and TTOs: Science is validated, but scale‑up, supply chain, and regulatory risk are under‑priced. Many spin‑outs stall between lab prototype and industrial‑grade product.
• Venture studios: Studio playbooks built for software underestimate capex, regulatory timelines, and hardware complexity when applied to deep tech.

Also Read: Dow hits record high, Nasdaq tumbles 0.6 per cent, Bitcoin miners flee: Signals deeper stress than price alone

Across these models, the Valley of Death persists because risk is assumed rather than designed.

A risk‑first, “foundry” approach

There is a class of foundry‑style models that start from the risk budget and work backwards:

• Enter at high TRL, avoiding pure science discovery risk and focusing on industrialisation.
• Launch ventures with pre‑sold demand and day‑one revenue to compress market and funding risk.
• Centralise legal, finance, and supply chain as a “business‑in‑a‑box” to reduce operating risk.
• Architect each venture around a specific 2–3 year path to liquidity so capital and timelines align.

Dragonfly Ventures and its Accelerated Deep Tech Commercialisation (ADTC) model is one example: it inverts the traditional risk stack by sourcing proven assets, securing day‑one customers, and designing for near‑term exits, turning startup success from a low‑probability bet into something closer to a yield problem.

What Southeast Asia needs to decide

For Southeast Asia to unlock its deep tech potential, the ecosystem will need to make explicit choices:

• Universities: lean into technology risk and push assets to higher TRLs before spin‑out.
• Corporates: underwrite timing and market risk with real offtake and industrial partnerships, not just pilots.
• Funds and foundries: innovate on ownership, liquidity, and operating models to ensure deep tech aligns with private capital cycles.

The Valley of Death won’t close by “more funding” alone; it will close when the region treats risk as a design variable in how we build, fund, and scale frontier tech companies.

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If 2025 felt like an uphill battle for marketing agencies, the data confirms it wasn’t just in your head. It was a structural inflection point.

Across the industry, the sentiment is identical: the old agency model, built on selling hours from more cost-efficient economies, execution, and “activity reports,” is collapsing.

As noted in a recent Entrepreneur analysis, agencies are squeezed between shrinking client budgets and skyrocketing expectations. The days of justifying a retainer with “we increased engagement by 40 per cent” are over. If that engagement doesn’t map directly to revenue, pipeline velocity, or measurable business growth, clients are walking away.

But as we settle into 2026, the winners are already emerging from the wreckage. They aren’t just “surviving” the AI revolution-they are weaponising it to move upstream.

The commoditisation of “doing”

The root of the crisis is the commoditisation of execution. Basic content creation, routine analytics, and campaign optimisation services that once commanded premium fees are now being automated in-house or handled by low-cost AI agents.

According to 2026 market predictions from the World Federation of Advertisers, the industry focus has shifted entirely from “efficiency” (doing things faster with AI) to “effectiveness” (delivering better outcomes). Agencies that stick to the “we do everything” generalist model are finding themselves in a race to the bottom on price.

The era of the linear workflow is over. Successful agencies are dismantling the old ‘strategy-to-creative-to-media’ handover in favor of agile ‘pods.’ By utilising predictive modelling, these integrated teams ensure that strategy and execution happen in tandem, not sequentially.

Also Read: The era of ‘black box’ pricing is over: Why transparency is the new currency in B2B marketing

The new currency: Strategic creative planning

If execution is cheap, insight is priceless.

The agencies thriving in 2026 have pivoted to selling strategic creative planning. They don’t just “make ads”; they use AI to decode cultural nuances, competitor strategies, and audience motivations before a single dollar is spent on media.

This shifts the agency’s value proposition from “outsourced hands” to “market intelligence partner.” This is where the next generation of AI tools is bridging the gap, allowing agencies to reclaim their premium status by offering predictive certainty rather than just creative guesses.

How AI is rewiring creative strategy

To survive, agencies must integrate human intelligence with AI capabilities that go beyond surface-level metrics. We are seeing a rise in platforms specifically designed to handle this “heavy lifting” of strategic analysis.

For instance, AI creative planning solutions are allowing agencies to reduce campaign research time from weeks to minutes. By using large language models to analyse massive datasets, agencies can now predict click-through rates with significantly higher accuracy than human instinct alone, effectively modelling success before launch.

This approach aligns with the “Psychographic Profiling” methodology discussed in Plug and Play APAC’s coverage of AI in marketing. Instead of broad demographic targeting, agencies can now identify thousands of micro-attributes and behavioural preferences, allowing them to cluster audiences and generate content derivatives that resonate on a personal level.

Also Read: Recognised by Google DeepMind, SOMIN aims to redefine AI-powered marketing

Furthermore, academic research demonstrates how AI can be used to “decode” competitor strategies. By analysing high-performing content across an industry, these tools can generate data-backed creative briefs (user stories), giving agency strategists a blueprint for what is working right now in the market.

The 2026 mandate

For agency leaders, the path forward is clear but difficult. 2026 is a reset year.

You must stop fighting the old game of “billable hours for execution.” The new reality demands that you position yourself as a partner who owns the outcome.

• Double down on specialisation: Be the absolute best at understanding one vertical’s pain points.
• Invest in “pre-flight” intelligence: Use AI to validate creative strategies before production.
• Sell the roadmap, not just the car: Clients will pay for the strategy that ensures the execution works.

The “service provider” model is dead. Long live the strategic partner.

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While traditional US financial markets are closed for the Presidents’ Day holiday, the cryptocurrency market continues to operate relentlessly. Global equity futures trade with light volumes, constrained further by Lunar New Year closures across mainland China and Hong Kong. Yet crypto never pauses.

The total market capitalisation rose 0.74 per cent over twenty-four hours to reach US$2.36 trillion. This modest gain reflects a market searching for direction amid thin liquidity and conflicting signals. My view is that this movement represents not a decisive turnaround but a fragile, technical rebound driven by specific ecosystem dynamics rather than broad macroeconomic conviction.

Ethereum’s relative strength provided the primary catalyst for today’s advance. The Ethereum Ecosystem category climbed 1.16 per cent, notably outpacing the broader market’s 0.74 per cent gain. This outperformance follows recent commentary from Vitalik Buterin, emphasising Ethereum’s base-layer neutrality, and from Coinbase CEO Brian Armstrong, noting that retail investors continue to accumulate ETH with diamond hands.

After six consecutive red monthly candles and a period of historic underperformance, Ethereum appears to be executing a technical bounce from deeply oversold conditions. The narrative surrounding the protocol has shifted subtly toward constructive long-term fundamentals, which seems to have encouraged spot buyers to step in at current levels.

However, this rebound remains precarious. Ethereum must maintain a price above the psychological US$2,000 threshold to sustain momentum. A failure to hold that level could swiftly erase today’s gains and reintroduce downward pressure.

Several secondary factors contributed to the market’s upward drift. Bitcoin exchange-traded funds recorded a net outflow of US$98.86 million, indicating persistent institutional caution toward the largest cryptocurrency. In contrast, Solana ETFs attracted a modest $2.34 million in inflows, suggesting investors are selectively rotating capital toward alternative layer-one protocols. This divergence highlights a market in transition, where capital flows are becoming more discerning rather than broadly risk-on.

Meanwhile, the Fear and Greed Index inched higher from 12 to 13, a marginal improvement that nonetheless leaves sentiment firmly in the Extreme Fear zone. This slight uptick implies the current bounce is fragile, likely driven by short-term positioning adjustments rather than a fundamental shift in investor psychology. The market’s weak eight per cent correlation with Gold further confirms that today’s move is crypto-specific, not a reflection of broader safe-haven or inflationary trends.

Also Read: Crypto market bleeds US$44B as US$78M Bitcoin liquidations spark panic

The near-term trajectory of the cryptocurrency market hinges on several technical levels and external catalysts. The immediate resistance sits at the US$2.37 trillion mark, which represents the 78.6 per cent Fibonacci retracement of the recent swing high to low. A daily close above this level could open the door to a relief rally targeting US$2.53 trillion. Conversely, the market must defend the US$2.17 trillion support, which marks the yearly low established on February 6.

A break below that floor would likely renew bearish momentum and test lower liquidity zones. Beyond price action, participants should monitor commentary from Federal Reserve speakers for any shifts in interest rate expectations. Changes in liquidity sentiment could rapidly alter the risk calculus for digital assets, especially in a holiday-thinned trading environment where modest order flow can produce exaggerated price moves.

From my perspective, today’s price action warrants cautious interpretation. The advance lacks the breadth and volume conviction that typically confirms a sustainable trend reversal. Ethereum’s leadership is encouraging, particularly given its oversold technical setup and improving narrative backdrop, but the broader market remains vulnerable to renewed outflows from Bitcoin ETFs and lingering fear among retail participants.

The selective inflow into Solana ETFs suggests a maturing market in which investors differentiate among protocols based on fundamentals rather than moving in unison. This selectivity is healthy in the long term but can produce choppy, range-bound price action in the near term. I believe the current environment favours patience over aggression. Traders should watch for confirmation above the US$2.37 trillion resistance before committing to a long position, while maintaining awareness of the US$2.17 trillion support as a critical risk-management level.

The cryptocurrency market’s resilience during traditional market holidays underscores its unique, always-on nature. Yet this constant operation can also amplify volatility when liquidity is thin and catalysts are scarce. Today’s modest gain, driven by Ethereum’s technical bounce and selective altcoin demand, offers a tentative reprieve for bulls but does not resolve the underlying tensions of persistent ETF outflows and extreme fear sentiment.

Also Read: Crypto market cap drops to US$2.3T as Fed rate cut hopes fade after hot jobs report

The path forward likely depends on whether spot buyers can consistently defend the US$2.17 trillion to US$2.37 trillion range. If they succeed, a relief rally toward US$2.53 trillion becomes plausible. If they fail, residual leverage and continued institutional caution could trigger another leg lower. In my assessment, the balance of evidence points to a market in consolidation, searching for a clearer macro signal or a sustained shift in institutional flows to establish a more durable direction.

Investors should approach this environment with disciplined risk management and a focus on high-conviction narratives. Ethereum’s recent outperformance, supported by protocol-level developments and accumulation by committed holders, presents a compelling case for selective exposure. However, the broader market’s dependence on Bitcoin ETF flows and macro liquidity conditions means that any single asset’s strength can be quickly overwhelmed by systemic headwinds.

The coming days will likely test whether today’s bounce can evolve into a more robust recovery or remain a fleeting pause within a larger corrective phase. For now, the cryptocurrency market offers a lesson in patience, where waiting for confirmation at key technical levels may prove more rewarding than chasing momentum in a landscape still defined by caution and selectivity.

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In B2B services, people often expect value to appear instantly: a sudden jump in numbers, leads, partnerships, or revenue.

But the reality is simpler and less glamorous: real transformation happens through process, clarity, systems, and consistent execution.

Hype and promises of overnight results miss the point. What actually helps businesses operate better, grow faster, and avoid costly mistakes is structure. And because this kind of value builds over time, it is often misunderstood or measured incorrectly.

The illusion of instant results

Short-term metrics can be seductive. They promise clarity and control, but they often measure activity, not progress. When service providers chase quick wins, they risk optimising for the wrong outcomes — speed over substance, visibility over value.

Common pitfalls of the “instant results” mindset:

• Overpromising outcomes that can’t be sustained
• Prioritising short-term KPIs over long-term growth
• Ignoring the deeper systemic changes clients actually need
• Undermining trust when results plateau after early gains

Redefining value in B2B relationships

When a company engages a service provider, they’re not buying hours or slides. They’re buying movement — the shift from where they are to where they want to go.

Value in B2B services isn’t a transaction; it’s a transformation. It emerges from shared understanding, consistent delivery, and the ability to adapt together over time.

A campaign or strategy engagement is valuable when it brings more benefit than what the client invested. And value isn’t just financial. It includes time saved, confusion removed, manpower reduced, and opportunities created.

If you avoid months of trial-and-error, cut wasted spending, avoid bad vendors, and land in a clearer, faster path: that’s meaningful ROI.

Also Read: Why your 50s are the perfect time to start a business

True value comes from:

• Strategic alignment: Understanding the client’s real business drivers, not just their immediate pain points.
• Capability building: Helping clients grow their own capacity to sustain results.
• Iterative improvement: Using feedback loops to refine and evolve solutions.
• Partnership mindset: Treating success as mutual, not one-sided.

This is the foundation of value pricing: You pay for transformation, not just activity.

Value comes from outcomes, not optics

The real test of value is what remains after the engagement ends.

A business has grown in capability. A system now runs where there was chaos. A team gains direction instead of confusion. A market strategy becomes clear instead of abstract. A partnership pipeline lives on instead of dying after one attempt.

Real value is a trajectory shift, not a moment. It’s the difference between constantly improvising and finally having a system.

The patience of progress

Real change takes time because it involves people, systems, and culture. The most effective B2B service providers know how to balance urgency with patience — delivering early wins while laying the groundwork for lasting impact.

Ways to build sustainable results:

• Set expectations early about the timeline for meaningful outcomes.
• Combine short-term deliverables with long-term capability goals.
• Use transparent communication to show progress, even when results are still forming.
• Celebrate learning milestones, not just performance metrics.

The long game of trust

Trust compounds over time. When clients see consistent effort, honest communication, and steady improvement, they become partners in progress. That trust becomes the foundation for deeper collaboration, innovation, and shared success.

Also Read: The architecture of bad deals: Moral hazard in modern business

The intangible value: What it feels like to work with a good partner

Every great service business carries an invisible asset — its ethos.

For us, value is not only in the tangible deliverables clients receive, but in the experience of working with a partner who is honest, transparent, and aligned with their success.

We believe in clarity instead of confusion. We break down complex processes into understandable steps and ensure the client always knows what is happening, who is doing the work, and why decisions are made.

We believe in transparency instead of rent-seeking. Our pricing is clean and direct. We don’t inflate costs or hide commissions. Most of the client’s money goes directly into the work — researchers, vendors, outreach teams, content creators — not into layered markups.

We believe in fairness. Vendors are paid properly; clients receive fair value; the ecosystem grows on trust instead of exploitation.

And we believe in partnership. We don’t take work we can’t deliver. We don’t overpromise. We don’t disappear. We stay accountable from day one to the last milestone.

For many clients, these intangibles — honesty, clarity, competence — are worth more than any deliverable.

Why this matters: The B2B world is broken

Much of the B2B service ecosystem is built on opacity. Consultancies overcharge and underdeliver. Agencies outsource everything and hide their vendors. Freelancers disappear after payment. “Strategy decks” look impressive but produce nothing.

Globaloca was created as a counterpoint. The focus is not on selling time but on enabling progress. Emphasis is placed on clarity, structure, and repeatable systems rather than ad hoc decision-making or experimentation.

The platform provides transparent pricing, verified vendors, multiple quotes, milestone-linked payments, and performance tracking.

Because the B2B service industry doesn’t need more noise. It needs a trust infrastructure.

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In this interview, e27 speaks with Eric about the Asia AI Association’s work in advancing AI innovation, professional collaboration, and ethical adoption across Asia, as well as how organisations can approach AI transformation responsibly.

This conversation forms part of e27’s broader AI Pulse coverage, which examines how organisations across the region are building, deploying, and governing AI in real-world settings.

Fostering AI innovation, networking, and ethics across Asia

e27: Briefly describe what your organisation does, and where AI plays a meaningful role in your work or offering.

Eric: Fostering AI Innovation, Networking and Ethics Across Asia Promoting technological advancement in Artificial Intelligence, facilitating professional connections, and championing ethical practices in Asia

1. Professional Development – Gain access to educational resources, career advancement programs, skill development training, and expert consultancy to boost your AI career.
2. Networking and Collaboration – Connect diverse communities of AI professionals, academics, and enthusiasts for collaborative research, and events.
3. Industry and Ethical Insights – Stay updated on AI trends, technologies, and best practices while engaging in discussions about interdisciplinary applications and ethics.

Promoting AI adoption through collaboration

e27: What is one concrete way AI is currently creating value within your organisation or for your users or customers?

Eric: As a business association focused on AI, AAIA connects with corporations, individual professionals, and business networks to provide training, knowledge-exchange platforms, workshops, and hackathons—promoting how AI can benefit everyone.

The rapid advancement of Artificial Intelligence (AI) has reshaped industries, revolutionized workflows, and transformed the way we interact with technology. With AI-powered automation, machine learning, and generative models now performing tasks once reserved for human expertise, many professionals fear being replaced by intelligent systems. However, while AI significantly enhances efficiency, it lacks the deeper capabilities of Human Intelligence (HI)—such as intuition, creativity, critical thinking, and emotional intelligence.

This is where AAIA comes in: to guide innovation through deeply human collaboration with technology. AI on its own is powerful; AI guided by empathy, ethics, and human creativity is transformative. This is the role of Human Intelligence (HI) that we advocate and champion.

Navigating organisational change in AI transformation

e27: What was a key decision or trade-off you had to make when adopting, building, or scaling AI?

Eric: As a business association serving our members, the general public, business networks, and the public sector, we recognise that change is often painful—but it is also inevitable. One example is a technology member of ours who spent over 90% of the engagement working closely with a local clinic chain on its AI transformation, converting manual bookkeeping and accounting processes into automated workflows. The key hurdles for the client were:

1. Clearly understanding and accurately presenting existing processes; and
2. Adapting to new AI-assisted workflows and embracing the discomfort that comes with change.

Also read: AI Pulse Exclusive: How Explico is building AI teachers can actually rely on

Rising awareness alongside cautious adoption

e27: Looking back, what has worked better than expected, and what proved more challenging than anticipated?

Eric: Public awareness of AI is improving rapidly, and adoption is happening faster than ever before. However, most people still treat AI merely as a tool—some embrace it enthusiastically, while many remain cautious or even fearful. Few have fully considered how AI-driven transformation can fundamentally improve and reshape the way we live, work, and make decisions in our daily lives.

The underestimated effort behind AI transformation

e27: What is one lesson about applying AI in real-world settings that leaders or founders often underestimate?

Eric: Leaders and founders often underestimate the effort, time, and resources required for meaningful transformation. While many existing business processes may appear to function adequately, they are frequently ambiguous or messy beneath the surface. Converting these informal processes into structured workflows or systems requires first making the situation transparent, then introducing new ways of working—both of which take time, alignment, and patience to “clear the air” before real progress can happen.

Communication as the foundation for AI adoption

e27: Based on your experience, what is one practical recommendation you would give to organisations that are just starting to explore or scale AI?

Eric: A practical recommendation for organisations that are just beginning to explore—or looking to scale—AI adoption is to prioritise communication above all else. Effective communication must happen at every level and in every form: from strategic planning and leadership alignment, to clear documentation of existing and future processes, and down to day-to-day verbal conversations across teams.

AI transformation is not purely a technology exercise; it is a shared understanding exercise. When goals, assumptions, workflows, and expectations are communicated clearly, organisations can surface ambiguities early, reduce resistance, and align people around a common direction. This clarity makes it far easier to redesign processes, adopt AI-assisted workflows, and move toward the intended outcomes with less friction and fewer costly detours.

Also read: AI Pulse Exclusive: How CoBALT is designing AI that teams can actually trust

Continuing the AI plus human intelligence approach

e27: Over the next 12 months, how do you expect your organisation’s use of AI, or the role of AI in your industry, to evolve?

Eric: Continue to roll out the AI + HI (Human Intelligence) program to aid the industry to improve with human touch.

Invitation to engage with the AI community

e27: Anything else you want to share with the audience?

Eric: Readers are encouraged to join our events & as members.

Human intelligence in the AI era

This conversation highlights the growing importance of keeping AI development grounded in human judgment, ethics, and collaboration as adoption accelerates across industries. As organisations move from experimentation to real-world deployment, initiatives that prioritise professional education, responsible innovation, and interdisciplinary dialogue will play a key role in ensuring AI strengthens human capability rather than replacing it.

For more interviews, analysis, and real-world perspectives on how organisations across the region are applying AI in practice, subscribe to our newsletter. You can also explore more AI stories here.

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