Use Case: Advertising for AI Agents

AI Agents
Written By Bede Feltham

Tomorrow's advertising won't persuade people. It will help AI agents make better decisions

Overview

For more than twenty years, digital advertising has relied on predicting what people might want. Cookies, browsing history, location data and behavioural profiling have all attempted to infer intent after the fact.

AI changes this model completely.

As personal AI agents increasingly search, compare, negotiate and purchase on behalf of individuals, advertising becomes less about persuasion and more about providing trusted, structured information that intelligent agents can evaluate objectively.

Instead of targeting people based on surveillance, organisations respond to explicit, permissioned intent shared by individuals under their own terms.

Advertising evolves from interruption to intelligent matching.

Context

Search transformed how people discovered information online.

AI agents will transform how they discover products and services.

Rather than browsing hundreds of websites or clicking adverts, individuals will increasingly describe their requirements once, allowing trusted AI agents to find suitable suppliers, compare offers and negotiate on their behalf.

This represents a shift from prediction to articulation.

Instead of organisations attempting to guess what customers might want, customers explicitly express what they are looking for and invite trusted organisations to respond.

DataPal provides the trusted relationship infrastructure that enables these interactions to happen safely, transparently and under individual control.

Challenge

Today's advertising ecosystem was designed for human attention. Tomorrow's customers may never see the advertisement.

Instead:

  • AI agents evaluate products

  • AI agents compare prices

  • AI agents assess trust

  • AI agents negotiate terms

  • AI agents recommend suppliers

Traditional advertising formats, behavioural targeting and emotional messaging become significantly less effective when the audience is software acting on behalf of an individual.

At the same time, organisations need confidence that declared intent is genuine, while individuals need assurance that sharing their intentions will not result in endless marketing or loss of control.

Neither today's advertising infrastructure nor current consent mechanisms were designed for this new model.

Solution

DataPal enables organisations and individuals to establish trusted, permissioned relationships before any information is exchanged.

Individuals define:

  • What they are looking for

  • What information may be shared

  • Who may respond

  • Under what conditions

  • For how long

These preferences are expressed using machine-readable Intent Signals and governed through MyTerms agreements.

Rather than collecting behavioural data, organisations receive structured, permissioned requests that their own AI systems can evaluate and respond to.

Personal AI agents can then compare offers using trusted facts rather than marketing claims, helping individuals make more informed decisions while maintaining complete control over their data.

How It Works (Flow)

Step 1

The individual tells their Personal AI Agent they are looking for a family electric SUV under £45,000 within the next six months.

Step 2

The AI agent creates a structured Intent Signal describing the individual's requirements, preferences and purchasing timeframe.

Step 3

Using DataPal, the Intent Signal is shared only with organisations that meet the individual's Privacy Signals, Trust Signals and MyTerms conditions.

Step 4

Vehicle manufacturers and dealerships receive the opportunity and submit structured offers including pricing, specifications, finance options, delivery times and incentives.

Step 5

The individual's AI agent evaluates every response using objective criteria including value, quality, trustworthiness and compatibility with the individual's stated requirements.

Step 6

The AI presents a shortlist with transparent reasoning explaining why each recommendation has been selected.

Step 7

The individual chooses whether to proceed, negotiate further or request additional offers while retaining complete control throughout the process.

Actors

The Individual (Data Owner)

Defines their requirements, controls permissions and remains in control of every interaction.

The Personal AI Agent

Acts on behalf of the individual by expressing intent, discovering suppliers, comparing structured responses, negotiating where authorised and presenting recommendations.

The Organisation (or Retailer)

Receive permissioned opportunities rather than anonymous behavioural signals and compete by providing better products, pricing, service and trust.

The DataPal Platform

Provides the trusted relationship infrastructure. Including:

  • Intent Signals

  • Privacy Signals

  • Trust Signals

  • MyTerms agreements

  • Permission management

  • Identity verification

  • Audit logging

  • Verifiable proof of requests, responses and agreements

MyTerms

Provides machine-readable permissions governing exactly how information may be used, shared, retained and acted upon.

Benefits

For Consumers (Individuals)

  • Complete control over who can contact them

  • Better matched offers

  • Less unwanted advertising

  • Transparent AI recommendations

  • Stronger privacy

  • More trusted relationships

AI Agents

  • Structured machine-readable information

  • Trusted data sources

  • Objective comparison

  • Automated evaluation

  • Clear permissions

  • Auditable interactions

For Organisations

  • Access to genuine purchase intent

  • Higher quality leads

  • Lower acquisition costs

  • Better conversion rates

  • Reduced dependence on behavioural tracking

  • Stronger customer trust

DataPal

  • Trusted relationship management

  • Portable permissions

  • Verifiable agreements

  • Human-controlled data sharing

  • AI-ready infrastructure

  • Interoperability with existing marketing and commerce platforms

Outcomes

Potential benefits include:

  • Significantly higher lead quality through explicit purchase intent.

  • Reduced reliance on cookies, behavioural tracking and third-party identifiers.

  • Higher conversion rates because suppliers respond to genuine demand rather than inferred interest.

  • Greater consumer trust through transparent, permissioned interactions.

  • Improved AI decision-making using structured, machine-readable information.

  • Reduced marketing waste by matching suppliers only with individuals who have expressed genuine interest.

  • Stronger regulatory alignment with emerging Smart Data, AI governance and privacy frameworks.

  • A shift from campaign optimisation towards long-term trusted relationship management.

Bede Feltham https://www.marketinghybrid.com/
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Use Case: Loyalty on Your Terms