June, 2026.- Everyone says they have AI now. The real question, according to Gurman Hundal, is where the intelligence is actually applied—and whether it produces outcomes.
Gurman Hundal, Founder & Global CEO of MiQ, developed Sigma, the company’s AI-powered platform. He distinguishes it from the AI tools that every other programmatic company now claims to have. Sigma is not an AI wrapper layered onto existing workflows, he explains. It is an intelligence engine embedded across the entire media lifecycle, from discovery and audience planning to activation, optimization, and measurement. Most tools still require users to know exactly what to ask. Sigma is built to understand intent, recommend actions, and continuously learn from outcomes.
In this interview, Hundal debunks the biggest myth about AI in media buying: that it will “replace media planners and buyers.” Media investment is not just an optimization exercise, he argues. It requires judgment, context, brand nuance, and commercial understanding. AI will augment expertise, not eliminate it. What is under-hyped is AI’s ability to make sense of fragmented signals in a privacy-first world. By 2027, competitive advantage will come from interpreting weak signals faster and connecting disparate datasets intelligently.
Hundal also discusses bringing MiQ’s global platform to Brazil, noting that Latin America is not a smaller version of North America or Europe—it is structurally different. Brazil has unique media consumption patterns, commerce ecosystems, regulatory dynamics, and publisher landscapes. Global technology matters, he concludes, but local intelligence is what makes that technology relevant. You can scale a platform globally; you cannot scale assumptions.
1. Sigma as a Differentiator: You developed Sigma, MiQ’s AI-powered platform. How is it different from the AI tools that every other programmatic company is now claiming to have? What can Sigma do that the others cannot?
Everyone says they have AI now. The real question is: where is the intelligence actually applied, and does it produce outcomes?
Sigma isn’t an AI wrapper layered onto existing workflows. It’s an intelligence engine embedded across the entire media lifecycle, from discovery and audience planning to activation, optimization and measurement.
What makes Sigma different is that it doesn’t just automate tasks; it synthesizes fragmented data, surfaces opportunities humans wouldn’t find manually, and turns complexity into decisions marketers can act on immediately.
Most tools still require users to know exactly what to ask. Sigma is built to understand intent, recommend actions and continuously learn from outcomes. In a fragmented ecosystem, that ability to unify intelligence across channels and data environments is the real differentiator.
2. AI Hype vs. Reality: AI is transforming advertising, but also generating enormous hype. What’s one claim about AI in media buying that you believe is complete nonsense, and what’s one under-hyped capability that will actually matter in 2027?
The biggest myth is that AI will “replace media planners and buyers.” That’s a misunderstanding of both AI and advertising.
Media investment is not just an optimization exercise; it requires judgment, context, brand nuance and commercial understanding. AI will augment expertise, not eliminate it.
What’s under-hyped is AI’s ability to make sense of fragmented signals in a privacy-first world. By 2027, competitive advantage won’t come from having more data, everyone will have plenty. It will come from interpreting weak signals faster, connecting disparate datasets intelligently, and generating actionable insights in real time.
That’s where AI will create tangible business value.
3. From Global to Brazil: You’re bringing MiQ’s global platform to Brazil. What specific adaptation does Sigma require for the Latin American market, and why can’t you just replicate what works in North America or Europe?
Because Latin America is not a smaller version of North America or Europe, it’s structurally different.
Brazil alone has unique media consumption patterns, commerce ecosystems, regulatory dynamics and publisher landscapes. The same audience models, identity frameworks or activation assumptions used elsewhere don’t automatically translate.
For Sigma, adaptation means localizing intelligence: integrating regional data sources, understanding local consumer behavior, supporting market-specific inventory environments and accounting for differences in measurement maturity.
Global technology matters. But local intelligence is what makes that technology relevant. You can scale a platform globally; you can’t scale assumptions.
4. The Programmatic Trust Problem: Advertisers still worry about brand safety, ad fraud, and transparency in programmatic. What’s the single biggest misconception about programmatic today, and what’s the single biggest legitimate concern that remains unsolved?
The biggest misconception is that programmatic equals opacity.
Modern programmatic, when executed properly, can actually deliver greater control, transparency and accountability than many traditional buying models.
That said, one legitimate concern remains unresolved: supply chain complexity.
The industry still operates through a fragmented web of intermediaries, inconsistent standards and varying levels of transparency. Progress has been made, but advertisers still want clearer visibility into where money flows, how value is created and what inventory quality truly looks like.
Trust isn’t a feature you switch on. It’s an industry-wide discipline we still need to improve.
5. Advanced TV vs. Retail Media: Both Advanced TV and Retail Media are growing fast. Which one is overhyped, and which one will command the larger share of incremental ad spend in Latin America by 2028?
Retail Media is generating enormous momentum, and deservedly so, but parts of the market are overestimating how quickly every retailer can become a scaled media business.
Owning commerce data doesn’t automatically translate into having mature media capabilities, interoperable measurement or advertiser-ready infrastructure.
By 2028, I expect Retail Media to command a larger share of incremental ad spend in Latin America because of its proximity to transaction data and measurable outcomes.
But Advanced TV shouldn’t be underestimated. As streaming adoption accelerates and audience fragmentation continues, Advanced TV will become increasingly central to brand-building strategies.
The future isn’t Retail Media versus Advanced TV. The real opportunity lies in connecting them through unified intelligence, measurement and activation.
