How advertising industry is rebuilding its operating system for the AI age

As AI reshapes how advertising is created, delivered and scaled, India’s market is discovering that trust engineered into systems, not speed alone, will define sustainable growth.

As artificial intelligence rapidly rewires advertising creation, targeting and optimisation, India’s advertising ecosystem is preparing for a structural reset. At the centre of this shift is the Advertising Standards Council of India, which is developing an AI-ready regulatory roadmap to help the industry adapt to machine-speed change without compromising consumer trust or ethical standards. The focus is clear. Monitoring systems are being strengthened, collaboration with digital platforms is deepening and regulation is being redesigned to keep pace with innovation rather than lag behind it.

This moment marks a departure from how advertising governance has traditionally functioned. AI has transformed advertising into an always-on system, where decisions are made and amplified at scale in real time. In this environment, trust, verification and accountability can no longer sit at the edges of the ecosystem. They must operate at system level.

When innovation moves faster than trust

The promise of AI is efficiency and scale. The risk is velocity without restraint. Misleading content today can be generated, personalised and distributed with a speed that leaves little room for human correction. The implications for brands are significant, not only in terms of compliance but also long-term equity.

Manisha Kapoor, Secretary General and CEO of ASCI, has been vocal about the need to rethink self-regulation in this context. “Self-regulation can and must evolve in an AI-driven economy, but it cannot do so in isolation,” she says. According to Kapoor, principles-based frameworks need reinforcement through technology-enabled monitoring, platform accountability and independent verification. “Building trust is the responsibility of the entire advertising ecosystem which includes advertisers, agencies and platforms.”

Her point reflects a broader recognition across the market. AI has changed how risk behaves. “Misleading or false content can spread much faster, appear more credible, and be amplified across platforms, causing damage to trust and brand value far more quickly than traditional brand safety issues,” Kapoor adds. This shift, she argues, makes proactive monitoring and shared responsibility essential rather than optional.

From episodic checks to continuous assurance

For years, brand safety was treated as a tactical concern. Ads were monitored for adjacency risks and violations were addressed after the fact. AI has exposed the limits of this approach. Risk is no longer linear. It is exponential.

Amit Relan, CEO and Co-founder of mFilterIt, an ad fraud prevention company, believes the industry is still underestimating how fundamentally AI has altered the threat landscape. “AI-generated misinformation has fundamentally changed the speed, scale, and subtlety of risk for brands,” he says. What once could be managed through keyword filters now demands a more deliberate and holistic approach to trust and accountability.

Relan points out that leading brands are shifting toward guardrails that combine contextual and sentiment intelligence with systems flexible enough to adapt to regional norms and cultural nuance. “In an always-on, AI-driven media ecosystem, trust is no longer assumed. It has to be continuously designed, monitored, and defended,” he says.

This transition signals a move away from episodic audits toward persistent verification. Trust is becoming infrastructure, measurable and enforceable in real time, much like identity or payments.

Why self-regulation alone is no longer enough

As advertising systems accelerate, the question is not whether self-regulation matters, but whether it can operate at machine speed. Vijender Yadav, CEO and Co-founder of Accops, a secure digital workspace provider, is clear about the limits of intent-based governance. “Self-regulation relies on human intent, which cannot keep pace with machine-speed execution,” he says.

Yadav argues that the industry must move toward hybrid enforcement models where regulation defines the rules, while technology ensures continuous compliance. “Compliance must shift from retrospective audits to persistent, identity-based gatekeeping,” he explains. In practical terms, this means validating the context, device health and identity behind every interaction in real time.

According to Yadav, the core issue extends beyond content to identity itself. “The real threat is a systemic identity crisis,” he says, pointing to the rise of synthetic corporate identities where AI can mimic internal brand voices or hijack credentials. “If an unauthorised actor compromises a media buy via AI, the equity damage is instantaneous.”

In this scenario, brand safety becomes an identity and access challenge. Without continuous authentication and contextual verification, Yadav warns, brand protection remains structurally vulnerable.

Platforms under pressure to balance speed and safeguards

Digital platforms sit at the centre of this transformation. They are expected to deliver speed, scale and revenue while also upholding transparency, fairness and consent. The tension between innovation and governance is becoming more visible.

Shashwat Vats, AVP at Olyv, believes the market is inevitably moving toward collaborative enforcement models. “Self-regulation has always been a vital part of responsible marketing, but with the rapid growth of AI, relying solely on self-regulation is likely not enough,” he says. Vats sees platforms, regulators and third-party auditors increasingly acting in concert rather than isolation.

He emphasises that ethical oversight must be embedded across the entire AI workflow. “Ethics and responsibility need to be a core component of platform systems, from data ingestion through model deployment,” Vats explains. When governance becomes integral to architecture rather than an external control, innovation can continue without erosion of trust.

The economics of credibility

As AI reduces the cost of content creation and optimisation, scarcity in advertising is shifting. Creativity remains vital, but credibility is emerging as the differentiator. Kapoor believes this will reshape competitive dynamics over the next five years. “The strongest advertising ecosystems will not be defined by creativity alone. They will be shaped by how well trust, transparency and accountability are built into the system,” she says.

This shift has direct business implications. Verification, fraud prevention and disclosure compliance are no longer defensive expenses. They influence visibility, platform prioritisation and consumer confidence. Brands that fail to invest in trust infrastructure risk becoming less visible or less credible in AI-mediated discovery environments.

Vats echoes this sentiment, noting that marketers will increasingly value integrity at system level, including data protection, algorithmic fairness and consistency of consumer experience. “Trust by design will become a significant advantage in the marketplace,” he says.

A new operating logic for advertising

India’s advertising industry is not stepping back from AI. It is rebuilding its operating logic around it. Regulation is becoming proactive, enforcement continuous and accountability shared across the ecosystem. The focus is shifting from policing outcomes to engineering systems that prevent violations at the point of execution.

The convergence of regulators, platforms and adtech players around trust infrastructure signals a deeper change in market thinking. Growth and governance are no longer opposing forces. They are interdependent.

As AI takes on greater creative and operational responsibility, the future of advertising will depend less on how fast systems can scale and more on how responsibly they are designed. In that equation, trust is no longer a soft value. It is the foundation on which sustainable growth will be built.