Marketing heads across Asia-Pacific are no longer asking whether AI will transform their organisations. The question now is how to integrate it without breaking their teams, how to hire for an unknowable future, and whether technology designed to accelerate work can also protect the boundaries that make sustainable performance possible in the first place.
In December 2025, an intimate gathering of senior marketing leaders assembled in Singapore for a “Conversations Over Courses” dinner co-hosted by Beyond the Boardroom and global consultancy, Maker Lab. Seated around the table were some of the region’s most influential voices-marketing heads and senior executives shaping brand narratives across beauty, fashion, technology, FMCG, entertainment and media. They convened not just to celebrate the year-end nor strategise in the conventional sense, but to engage in something increasingly rare within corporate life: an honest, unvarnished conversation framed around reflection and foresight, examining what the year had been for them, and contemplating what 2026 would demand.
The agenda was deliberately expansive. Personal life balance, the relentless pressure of content production, and the complexities of the creator economy all emerged as critical pressure points requiring attention. Yet beneath these distinct conversations, a single thread persisted with striking consistency: artificial intelligence. Not as a separate topic to be managed in isolation, but as the undercurrent connecting everything else, and the force capable of either intensifying or alleviating every other challenge on the table. What surfaced over the course of the evening proved striking not for its novelty, but for its remarkable coherence. Despite vastly different sectors and mandates, leaders spoke with a shared pragmatism that marked a decisive departure from years prior. This was not the AI conversation of 2023 or even 2024. The endless speculation had dissipated. The existential anxiety (whilst not entirely absent) had been tempered by something altogether more grounded: lived experience. These were leaders who had piloted tools, restructured workflows, confronted resistance and absorbed failures. They comprehended both AI’s promise and its profound limitations and, crucially, that the technology itself was never the central question.
As one entertainment marketing head articulated: “It’s no longer about being afraid of AI, it’s about cohesion. There’s no 100% solution, no magic bullet for applying it perfectly. But it remains a priority to see how it can fill resourcing issues strategically and drive bottom-line growth.”
This reframing-from existential threat to strategic opportunity-now defines the discourse across Asia-Pacific for 2026. But it also reveals a more complex reality. AI’s reach extends into every dimension of modern marketing practice, from how teams function to how brands create, from operational efficiency to personal sustainability. Understanding why it remains the central priority requires understanding how it intersects with the other pressures leaders face.The existential threat is diminishing precisely because AI has become omnipresent. Leaders around the table acknowledged (some with evident relief) that deployment has rendered certain aspects of their work genuinely more tractable. Whether through ChatGPT for ideation and synthesis, enterprise-level tooling for analytics and data interpretation, or automated workflows that compress what once consumed hours into mere minutes, the value proposition has moved beyond debate.
But this transition from stage one-adoption, experimentation and pilot programmes-to stage two raises far thornier questions. Having confirmed that AI delivers on its fundamental promise, leaders now confront what happens when the novelty dissipates and integration becomes the actual work?
Restructuring Teams and the Human-Machine Equilibrium
The first and most pertinent question concerns organisational architecture itself. If AI can execute certain tasks with velocity and precision that surpass human capability, how should teams be structured? Which roles remain genuinely essential, and which represent legacy thinking masquerading as necessity? And how do organisations construct a productive balance between machine efficiency and the emotional intelligence, strategic judgement and creative intuition that define genuinely differentiated work?
Leaders at the table spoke with unusual candour about the delicate recalibration underway within their organisations. One shared that AI has proven itself extraordinarily adept at pattern recognition, data synthesis, process optimisation, the analytical and procedural dimensions of marketing that consume vast amounts of human capital. Yet the capacities that genuinely differentiate brands-strategic vision, cultural fluency, the ability to discern when to shatter convention rather than optimise within it-remain stubbornly, irreducibly human.
“The conversation around AI today for leaders has shifted from fear to fluency. AI isn’t about replacing talent, but augmenting it, which means the race isn’t about tools,” shares Intan Mokhnar, Managing Director at Maker Lab, a global in-housing agency that assembles high-performing specialist teams designed to meet client KPIs in Singapore. “It’s about building teams with the judgement, emotional intelligence, and confidence to know exactly when human instinct must override the algorithm.”
Mokhnar’s insights were well reflected in the evening’s discourse, with most leaders citing that the challenge lies in constructing teams where these fundamentally different modes of intelligence co-exist productively rather than compete destructively. This demands not only hiring for technical fluency with AI tooling, but prioritising emotional intelligence, critical thinking and the judgement to discern when to trust the algorithmic recommendation and when to override it with human conviction. The most sophisticated organisations, it became apparent, are those architecting hybrid structures where humans concentrate on the questions AI cannot meaningfully address: What should we create? Why does it merit existence? How does it connect to deeper human truths that transcend optimisation metrics for marketers?
Constructing the appropriate resourcing model has therefore become a first-order strategic imperative. Brands can no longer afford to treat AI as peripheral capability, managed at arm’s length by a web of partners or isolated specialists. It must sit proximate to core decision-making, shaped by individuals who comprehend the brand’s tensions, its aspirations and its strategic imperatives with genuine intimacy. This is why embedded agency models or teams that operate inside client organisations rather than at a contractual distance, are experiencing renewed traction. Proximity enables the continuous learning loops and accumulated institutional knowledge required to transform AI from a commodity tool into a genuine competitive advantage.
The Content Dilemma: Volume Vs. Differentiation
Secondly, if AI can generate content at unprecedented scale and minimal marginal cost, the question becomes not whether it can, but whether it should. This tension provoked perhaps the most animated discussion of the evening, exposing a fault line between market incentives and strategic conviction.
The temptation proves nearly irresistible. Feeds overflow with content. Platforms algorithmically reward constant output. Competitors publish relentlessly, creating an arms race of presence. AI dangles the seductive possibility of meeting these volume demands without proportionally expanding headcount, budgets or operational complexity. Yet leaders expressed profound unease about capitulating to this logic.
Mokhnar explains, “AI makes volume easy, but quantity rarely solves the bigger business problem of differentiation. In fact, restraint is now a strategic advantage for brand guardians. Our role is to steer teams toward clarity and creative conviction, rather than producing content simply because technology allows it.”
Leaders described wrestling with this calculus on a daily basis. Do you deploy AI to maintain omnipresence across every channel, ensuring constant visibility even when you have little substantive to contribute? Or do you exercise the discipline of restraint, reserving human creative capacity for work that genuinely matters?
The emerging consensus suggested a more nuanced approach to harness AI for the operational and iterative dimensions. From format variations, to channel adaptations and performance optimisation, to the tactical choreography of distribution, whilst fiercely protecting human involvement in the conceptual and strategic. Allow machines to handle execution at scale, reserve human judgement for the infinitely harder question of what deserves to exist in the first place.
Ownership, Intellectual Property and the Data Question
As AI embeds itself within the infrastructure of marketing practice, questions of ownership and control grow increasingly existential. Who genuinely controls the data that trains these systems? Who possesses the insights they generate? And how do brands preserve proprietary advantage when the tools, platforms and even creative collaborators operate within inherently shared, increasingly surveilled ecosystems?
The creator economy substantially complicates this already uncertain terrain. Brands increasingly depend upon external creators to produce ostensibly authentic content at scale, yet managing these relationships-negotiating terms, maintaining brand consistency, preserving intellectual property amidst distributed production-creates its own operational labyrinth. When creators deploy AI tools to accelerate their output, where does authorship genuinely reside? When platforms aggregate behavioural data across countless campaigns, extracting patterns and insights at population scale, who truly owns the resulting intelligence?
“AI only becomes a competitive advantage when it sits close to the business,” says Mokhnar. “Proximity matters, because data, insight and institutional knowledge compound over time. Embedded models allow brands to retain ownership of their learning loops, rather than leaking value through disconnected partners and platforms.”
This is why many brands find themselves re-examining not just their technology stacks, but their fundamental organisational architectures. To extract authentic value from AI that compounds over time rather than dissipating with each vendor transition, organisations must assume genuine responsibility for how work gets done, not merely what gets delivered at project’s end. This means either bringing critical capabilities in-house, or embedding partners so deeply within the organisational fabric that the distinction becomes functionally immaterial. The brands that will genuinely succeed in an AI-saturated environment are those willing to own their processes, their data and their learning loops, even when the immediate costs appear daunting.
What 2026 Demands
Looking ahead, the message from those gathered that evening crystallises with unmistakable clarity. AI will continue to dominate strategic priorities, reshape budget allocations and fundamentally redefine organisational design. But success will belong to those who approach stage two with rigorous discipline rather than breathless enthusiasm alone.
For brands, this necessitates making genuinely difficult choices about what to own, what to partner and how to structure for meaningful proximity rather than convenient distance. It means investing in talent distinguished not by technical fluency alone, but by the emotional intelligence and strategic judgement required to navigate an AI-augmented landscape. It means exercising disciplined restraint in content production rather than optimising mechanically for volume metrics. And it means defending ownership of data, insights and creative intellectual property with the same vigilance traditionally reserved for physical assets and financial capital.
AI remains the central strategic priority, but the conversation has fundamentally matured. The leaders shaping its next chapter have moved decisively beyond the existential questions of will it transform us or should we fear it into something far more consequential and infinitely more complex: the operational realities of integration. In 2026, success will be defined not by who adopted AI first or most loudly, but by who deployed it most thoughtfully, with strategic clarity about organisational structure, intellectual discipline about quality versus volume, and unwavering conviction about what must remain irreducibly, strategically, competitively human.
Stay tuned for all the insights from the next Conversations Over Courses dinner with Maker Lab, a global in-housing agency that blends human creativity with AI technology to embed high-performing specialist teams within brands. With offices across Singapore, London, and New York, Maker Lab partners with the world’s most forward-thinking brands to make marketing work better.