CMOs now need deep tech fluency — not just ownership. Here's what separating high-performing stacks from expensive shelf-ware looks like in 2026.
The average enterprise marketing stack now runs north of 50 tools. Most brands are actively using fewer than half of them at any meaningful depth. That gap — between owned and activated — is where marketing budgets quietly go to die.
The CMO Technology Mandate Has Changed Shape
AdExchanger’s Victoria McNally made a pointed observation this month: agencies have poured millions into proprietary AI platforms covering creative testing, audience targeting, and campaign planning — and from the outside, they all look roughly identical. The differentiator isn’t the tooling. It’s the operator.
That reframing matters for CMOs in Southeast Asia more than most. The regional martech landscape is layered with platform-specific complexity — Shopee’s ad manager, LINE’s ecosystem in Thailand, Grab’s O2O targeting capabilities — each with distinct data models, attribution logic, and audience constructs. A CMO who treats these as interchangeable slots in a media plan will consistently underperform one who understands the mechanics underneath. Tech fluency isn’t a nice-to-have anymore. It’s a competitive moat.
The implication for agencies is equally sharp: clients aren’t paying for tool access. They’re paying for informed configuration and continuous optimisation of systems that most internal teams don’t have the bandwidth to run properly.
Programmatic Is Eating Formats That Used to Be Immune
Two signals this month illustrate how far programmatic reach has extended beyond its traditional home in display and social.
Warner Bros. Discovery’s upfront strategy, covered by Digiday, now positions programmatic as a core part of premium TV deal-making — not a remnant channel or a fallback for unsold inventory. Programmatic is being pitched in the upfront room itself, which a few years ago would have been considered reputationally risky for a premium publisher. The data-driven targeting and measurement capabilities have simply become too valuable for buyers to ignore, even at premium CPMs.
Meanwhile, VIOOH’s partnership with VENDO Media in Canada adds 550+ digital billboards to its programmatic DOOH supply — continuing the steady conversion of physical media formats into addressable inventory. For Southeast Asian brands, this trajectory is worth watching: DOOH programmatic infrastructure in markets like Singapore and Bangkok is maturing fast, and the planning assumptions that kept OOH in a separate budget silo are increasingly outdated.
The common thread: programmatic logic — audience targeting, real-time optimisation, unified measurement — is colonising every channel. CMOs who silo their programmatic capability inside a single channel team are structuring themselves for inefficiency.
The AI Agency Arms Race and What It Actually Means for Clients
Every major holding group and a growing number of independents have launched proprietary AI platforms in the last 18 months. The pitch is consistent: faster creative iteration, smarter audience segmentation, better campaign forecasting. The reality, as AdExchanger’s reporting surfaces, is that the tools are increasingly similar under the hood — many built on the same foundation models, differentiated mainly by training data and workflow integration.
For a CMO evaluating agency partners, this creates a useful filter. The right question isn’t “do you have an AI platform?” — everyone does. The right question is: what proprietary data is informing your models, and how does your AI tooling connect to my first-party data infrastructure? An agency running generic prompts through a branded interface isn’t delivering differentiated value. One whose AI is trained on category-specific performance data, integrated with your CRM and CDP, is a different proposition entirely.
For Southeast Asian brands specifically, localisation depth matters. Regional nuance — multilingual copy, platform-specific creative formats, cultural relevance signals — is exactly where generic AI tools fall short and where agency expertise should be demonstrably additive.
Activation Over Acquisition: The Discipline Most Stacks Need
The MarTech consolidation conversation has been running for three years, but the behaviour hasn’t changed much. Brands keep adding point solutions to solve specific campaign problems without asking whether the existing stack, properly configured, could do the same job.
The discipline required here is less glamorous than a new platform evaluation: it’s auditing utilisation rates on current contracts, mapping data flows between systems to find where signal is being lost, and stress-testing attribution logic against actual business outcomes rather than platform-reported metrics.
One practical starting point: pull your last 90 days of campaign data and identify which tools in your stack contributed a signal that actually changed a decision. If a tool isn’t influencing decisions, it’s decoration. For brands running across Lazada, Meta, Google, and programmatic display simultaneously — a common combination in Southeast Asia — the integration layer between these platforms is often where the most value is being left on the table. Clean data flows and unified reporting aren’t exciting, but they’re where the compounding returns live.
Key Takeaways
- Map your stack against actual decision-making: if a tool isn’t changing how you act, audit it before renewing it.
- Evaluate agency AI platforms by the specificity of their training data and integration depth with your first-party infrastructure — not by the sophistication of the demo.
- Treat programmatic as a cross-channel capability, not a display tactic — DOOH, CTV, and premium video are all now live programmatic channels with real targeting depth.
As programmatic logic extends into every media format and AI becomes table stakes rather than differentiator, the competitive question shifts from what tools you own to how tightly they’re integrated and how deeply your team can operate them. The CMOs who pull ahead won’t necessarily have the biggest stacks — they’ll have the fewest gaps between what their technology can do and what they’re actually doing with it. Which raises an uncomfortable audit question for most organisations: when did you last map that gap honestly?
At grzzly, we work with marketing teams across Southeast Asia who are dealing with exactly this — stacks that grew faster than the capability to run them. Whether that’s rationalising your MarTech contracts, mapping your data architecture, or helping you ask sharper questions of your agency partners, we’d rather have a straight conversation about what’s working than sell you another layer. Let’s talk
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Crispy GrizzlyAuditing, assembling, and occasionally dismantling marketing technology stacks for brands that have over-bought and under-activated. Precision over proliferation.