AI-driven purchase journeys push advertisers beyond traditional reach metrics

New Delhi: WPP Media has released its Advertising Intelligence Framework, setting out a methodology to assess how major technology platforms are positioned to connect brands with consumers in an AI-driven advertising environment by 2030.

Published in February 2026, the framework establishes a structured model for evaluating which companies could emerge as primary sources of intelligence for businesses and consumers over the next five years. It identifies five core capability categories — Data Assets, AI-Technical Capability, Distribution, Transaction-Commerce Capability, and Content-Media — which together determine a platform’s readiness to deliver personalised, proactive and pervasive advertising intelligence.

The report states that as artificial intelligence increasingly mediates how consumers discover products, compare options and complete transactions, advertisers must evaluate not only reach but also the infrastructure that enables AI-driven decision-making. It adds that future purchase journeys may involve AI agents and bots acting on behalf of users to research, compare and transact, reshaping how brands secure visibility and recommendation.

The framework assigns a total weighting of 100 % across the five categories. Data Assets, AI-Technical Capability and Distribution each account for 22.2 % of the overall score, while Transaction-Commerce Capability and Content-Media carry 16.7 % each. The analysis uses companies’ current capabilities to project competitive positioning through to 2030 and is expected to be updated quarterly.

Within Data Assets, which represents 22.2 % of the framework, the report evaluates the volume, quality and diversity of proprietary data held by companies, including behavioural signals, business and commercial information, real-world mapping and location metadata, and identity systems. Scores in this category range from 37.5 % to 87.5 % of the maximum possible allocation, indicating notable capability gaps. The study finds that while many companies have achieved baseline competency in data collection, relatively few have built comprehensive, multi-dimensional datasets capable of supporting advanced intelligence systems.

Among current leaders in behavioural data are Alphabet, Meta, ByteDance and Tencent, with Amazon identified as strong in purchase signals but narrower in non-commerce behaviours. Alphabet is cited as leading in real-world data, while identity capabilities vary, with Apple highlighted for device-linked data and user trust, and Tencent and Alibaba noted for payment-based identity systems.

AI-Technical Capability, also weighted at 22.2 %, assesses model development, infrastructure scale and recommendation systems. Company performance in this category ranges from 45 % to 92.5 % of the maximum weighting. The report notes the potential commoditisation of foundation models alongside persistent infrastructure advantages for cloud hyperscalers. Frontier model development is attributed to Alphabet, OpenAI and Meta, while infrastructure scale is associated with Amazon, Alphabet and Microsoft. In recommendation systems, ByteDance, Alphabet and Meta are identified as leaders, with Amazon strong in product recommendation and Tencent in multi-domain systems.

Distribution, which also carries a 22.2 % weighting, shows the widest competitive dispersion, with scores ranging from 27.5 % to 87.5 % of the maximum. The report describes distribution as the most durable competitive advantage and the highest barrier to entry, requiring sustained ecosystem development, hardware integration and consumer trust. Google, Apple and Meta are cited as globally scaled leaders, with Apple noted as having a presence in China, the world’s second most populous market.

Transaction-Commerce Capability accounts for 16.7 % of the framework and shows performance ranging from 33.3% to 93.3% of the maximum weighting. The analysis identifies a divide between commerce-native platforms and advertising-native platforms, stating that excelling in both commerce infrastructure and advertising systems simultaneously remains uncommon. 

Amazon and Alibaba are described as having built commerce platforms before adding advertising layers, while Alphabet and Meta developed advertising systems and later expanded into commerce facilitation. No company achieves consistently high performance across all three transaction sub-segments.

Content-Media, also weighted at 16.7%, records performance ranging from 23.3% to 86.7% of the maximum allocation. While most major platforms now operate substantial content ecosystems, the report suggests that few have combined exclusive intellectual property, ecosystem lock-in and seamless shoppable advertising integration at scale.

Alphabet’s YouTube is described as having significant engagement, ByteDance’s recommendation systems are highlighted, and Amazon is identified as leading in content-commerce integration, though bundling beyond Prime remains limited.

The report categorises companies into four strategic groups. Ecosystem builders, including Alphabet and Amazon, demonstrate broad consumer reach and diversified monetisation across multiple pillars. Specialists, such as Meta, Alibaba, Tencent and Microsoft, show strength in specific capabilities but rely on partnerships to address structural gaps.

Challengers, including Apple, ByteDance and OpenAI, are characterised as fast-moving players building towards broader capability. Hardware heavyweights, such as Samsung and Xiaomi, are noted for extensive device footprints but comparatively less developed service and advertising layers.

The framework also outlines potential scenarios that could alter competitive rankings by 2030. It suggests that deeper integration between Tesla and SpaceX or its AI affiliate xAI could materially strengthen xAI’s position. A potential acquisition of Shopify by Meta is cited as a move that could address Meta’s commerce gap.

The report concludes that no single company currently demonstrates simultaneous strength across data collection, AI processing, distribution, transaction infrastructure and content engagement. It projects that by 2030, three to four companies could achieve comprehensive intelligence capabilities exceeding 75% of the total framework weighting, with a middle tier of specialised platforms operating at materially lower aggregate levels.

The publication closes with five questions for advertisers entering the AI era, including whether brands control their own customer intelligence, whether partners can demonstrate incrementality and off-platform conversion, whether targeting strategies can withstand regulatory shifts, how resilient distribution strategies are to disruption, and whether AI-driven purchasing systems will recommend their products.