JK's Diary

Prepare for the next wave: Consent Engineering

For years, Consent Management Platforms (CMPs) like OneTrust, TrustArc, and Osano served as the digital privacy gatekeepers of the web. They helped companies display those now-ubiquitous cookie popups and ensure that users gave (or didn’t give) permission for tracking. But while technically necessary for GDPR, CCPA, and similar regulations, CMPs have become more of a compliance checkbox than a meaningful privacy safeguard. We, as users, feel the frustrations of this broken process. Thanks to the evolution of AI and digital experiences, this model is changing.

The Problem: Consent Management Is Fragmented, Fatiguing, and Fading

With AI-first browsers like Comet (to be launched by Perplexity) explicitly designed to “track everything users do online” for hyper-personalized experiences, the locus of control is moving away from individual websites to the browser layer, where consent could be set once and respected everywhere.

In short, Browsers — not websites — are becoming the central actors in user data collection. This shift renders traditional CMPs increasingly irrelevant — unless they evolve.

AI Browsers Don’t Just Observe — They Act!

The implication: CMPs must become smarter or “agent-aware”. They’ll need to integrate directly with browsers and their APIs to:

• Interpret global consent settings issued by users.
• Detect when AI agents are scraping or collecting data.
• Ensure downstream systems (like adtech or analytics platforms) respect those browser-level preferences.

This isn’t hypothetical. OneTrust and BigID are already deploying AI-driven privacy agents and compliance automation tools, which could evolve to interface directly with browser AI.

Programmable & Portable Consent

Imagine a future where users set privacy preferences once — during browser setup — and those settings follow across every site, platform, and digital touchpoint. That’s programmable consent.

In this model:

• CMPs don’t just ask for consent; they interpret and enforce it.
• Consent signals become machine-readable, portable, and actionable across systems/devices.
• Privacy becomes not a moment in time, but a persistent layer of the digital experience.

This requires a fundamental re-architecture of CMPs — from UI overlays to backend orchestration engines.

The existing setup is not going to go away anytime soon. They will co-exist for a while, but the additional layer to address the emergence of AI browsers is inevitable in the near term.

The initial rollout of consent management at the browser level might be rigid or with limited options, but with subsequent rollouts, this could change. For example, browsers could provide options to set consent at website level, website category level, bookmarked/favorite sites level, or as simple as allowing websites to push their ubiquitous popups when a site is opened for the first time on the AI-browser and store the user preference for future visits on the browser.

Blueprint for CMP 2.0: Consent Engineering in Action

CMPs face an urgent need to redefine their value. Instead of focusing solely on front-end banners, they must shift toward being Consent Orchestration Engines or Consent Engineering Platforms —interpreting, enforcing, and governing consent across platforms, applications, and back-end data systems.

Few key opportunities and imperatives for CMPs:

§ Agent-aware and API-first with AI-Browsers

Consent signals will originate from browsers and autonomous agents. CMPs must build real-time API hooks to sync with browser preferences and ensure websites respect those choices.

§ Orchestration Across Platforms

CMPs must manage (and synchronize) machine-readable consent across all digital touchpoints (e.g., website, mobile app, SaaS tools), not just the web layer. Encoding consent in standardized formats (e.g., Global Privacy Control (GPC)) that downstream systems can interpret and enforce automatically is critical.

§ Consent-as-a-Service

Offer “consent-as-a-service” embedded at the edge (e.g., browser extensions, SDKs) to enforce rules downstream—in data warehouses, CDPs, marketing clouds.

§ Downstream Data Governance

It’s not just about capture—it’s about ensuring consent follows the data. I.e., data flow control, compliance logging, and privacy auditing for server-side and AI-powered data operations. CMPs must enforce usage restrictions in analytics, personalization, and advertising systems.

§ Consent Auditing & Logging (PrivacyOps)

Regulators want proof. CMPs can provide the audit layer for browser-generated preferences, creating reconciliations between user intent and system behavior. Deploy AI to detect tracking violations, scan for third-party risks, and auto-generate regulatory reports. Where applicable, collaborate with cloud providers or AI agents to enforce preferences.

Who’s Leading the Way?

Leading CMPs are taking steps to adapt to this new future. For example, there is a lot of investment in AI governance and automation by OneTrust. Use of AI/ML for consent management by BigID and so on.

These companies aren’t just reacting—they’re re-architecting.

What This Means for Privacy Leaders and Digital Teams

We’re at the beginning of a major shift. AI browsers will rewrite the rules of data privacy, and businesses that rely on outdated CMPs risk being caught flat-footed. Hence, the implications of this browser-centric future are profound:

• Chief Privacy Officers must start redefining what compliance looks like when consent is programmable and portable.
• Marketing and data teams need to reconfigure how they ingest and process user data—browser signals might override what your CRM thinks it knows.
• Engineering teams must build consent-aware architectures that support API-driven orchestration and server-side governance.

In short, the cookie banner era is ending. The age of dynamic, portable, agent-aware consent is here. It is time for you to:

• Audit your current CMP for readiness in an AI-agent web environment.
• Evaluate browser-level consent initiatives and their implications for your data strategy.
• Explore integration paths between your privacy stack and AI/automation tools.

Are these thoughts in your mind?

• How to evaluate your consent architecture for the AI browser era?
• Is your CMP strategy AI-agent ready?
• Should your next privacy investment be in compliance… or consent engineering?

Don’t get left behind. Reach out, and let’s collaborate on building a forward-thinking approach to consent that aligns with the browser-level revolution.