Cannes feedback shows AI has broadly entered ad delivery, but the commercial impact is not a one-way substitution

Overview

This report summarizes Goldman Sachs' key feedback from more than 20 meetings over four days at the Cannes Lions Festival with CMOs, advertising holding groups, independent agencies, and ad tech companies. The report focuses on AI budgets, generative search, ad agency services, potential DSP changes, the substitutability of LiveRamp's data services, and the potential boost from AI and data integration to IT services growth.

Core views

The core view is that AI has moved from proof of concept into broad deployment across the advertising business and will bring incremental ad budgets in 2026, but its impact is more about reshaping the value chain than simply replacing labor. Incremental spending from AI players is changing the traditional relationship between media spending and GDP; large LLMs are poised to enter search, brand, and performance advertising budgets; and agencies still benefit from service, production, and data integration needs. However, 2027 will face a high base from sports and political events, and marketing organizational change may also progress slowly due to short CMO tenures and fragmented priorities.

Analysis framework

The report uses field research and industry interviews, synthesizing industry trends in AI, media budgets, data integration, DSPs, and IT services based on meeting feedback during the Cannes advertising festival with advertiser CMOs, agency groups, independent agencies, and ad tech participants.

Methodology notes

• Field researchCannes Lions Festival industry interviews

  Industry feedback formed through more than 20 meetings

  The report's conclusions mainly come from discussions over four days with CMOs, advertising holding groups, independent agencies, and ad tech companies, representing qualitative industry channel feedback.

• Valuation and equity analysis frameworkGS Factor Profile

  Comparison of growth, financial returns, valuation multiples, and composite percentiles

  The disclosure appendix states that Goldman Sachs uses this framework to compare key stock attributes with the covered market and industry peers, but the main body of this report does not provide specific company factor results.

• M&A analysis frameworkM&A Rank

  Scoring from 1 to 3 to assess the probability of a company becoming an acquisition target

  The disclosure appendix states that in the M&A Rank, 1 represents a high probability of 30%-50%, 2 represents a medium probability of 15%-30%, and 3 represents a low probability of 0%-15%; this report does not disclose specific M&A scores for any targets.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• LIVERAMP HOLDINGS INC / RAMP.US

  A company related to the data identity and data collaboration services mentioned in the report

  Strengths

  Industry feedback suggests LiveRamp's services are difficult to replicate, indicating that its data integration and identity resolution capabilities have certain barriers.

  Weaknesses

  Omnicom says it has replicated related capabilities, and Dentsu is also building alternatives, indicating substitution risk from competition.

  Comparison

  Compared with agency groups building in-house alternatives, LiveRamp's specialized services are still seen as harder to replicate, but large agencies may gradually reduce external dependence.

  Risks

  In-house client capabilities, agency group alternatives, changes from M&A integration, and data privacy regulation could affect the value of its services.

• Large advertising agencies and media agencies

  The main recipients of AI deployment and client budget reallocation

  Strengths

  As AI broadly enters ad campaigns, agencies may benefit from production revenue, service demand, and aggregation of LLM token procurement.

  Weaknesses

  Organizational change is slow, and it remains uncertain whether management can capture the token aggregation opportunity.

  Comparison

  Compared with pure technology platforms, agencies still have advantages in client relationships, service execution, and cross-channel budget management.

  Risks

  LLMs and agentic AI may compress the value of some interface and execution layers, creating uncertainty around long-term profit allocation.

• DSPs and ad tech platforms

  The advertising tool layer that may be reshaped by LLMs and agentic AI

  Strengths

  Existing DSPs still handle programmatic buying, budget execution, and performance optimization.

  Weaknesses

  LLMs may commoditize DSP user interfaces, and agentic AI may even reduce demand for traditional DSP interfaces.

  Comparison

  The report suggests the boundary between buying agents and DSPs may become blurred, indicating that traditional ad tech platforms need to prove their incremental value relative to AI agents.

  Risks

  User interfaces being commoditized, client workflow migration, and declining platform pricing power.

• IT services companies

  Potential beneficiaries of a recovery in growth driven by AI and data integration demand

  Strengths

  Industry participants generally believe discussions with clients around AI and data integration could help restore growth in IT services.

  Weaknesses

  The report emphasizes that progress remains slow, and near-term revenue conversion may be limited.

  Comparison

  Compared with advertising agencies, IT services are more dependent on project execution and system integration cycles, so the pace of growth recovery may lag.

  Risks

  Delayed client budget approvals, high project complexity, and long validation cycles for AI investment returns.

Key data

• Number of research meetings>20 meetingsThe report states that more than 20 meetings were held over four days with CMOs, advertising holding groups, independent agencies, and ad tech companies.
• AI deployment in ad campaignsNearly all ad campaignsThe report states that AI is now deployed in nearly all ad campaigns, and agencies are seeing growth in production revenue.
• Number of stocks covered by Goldman Sachs Global Equity Research3,074 stocksAs of April 1, 2026, Goldman Sachs Global Investment Research had investment ratings on 3,074 stocks.
• Rating distributionBuy 50%, Hold 34%, Sell 16%From the global equity coverage rating distribution table in the disclosure appendix.
• Investment banking relationship distributionBuy 65%, Hold 60%, Sell 45%The disclosure table shows the proportion of companies in each rating category that had investment banking relationships in the past twelve months.

Impact & implications

From an investment perspective, incremental AI advertising budgets benefit companies in the media and advertising ecosystem that can absorb spending from AI players, as well as data integration and service complexity; in the short term, agencies have not been clearly displaced by AI and may instead gain new revenue opportunities from production efficiency, client consulting, and token procurement aggregation. The ad tech chain faces more complex repricing: DSP interfaces may be commoditized by LLMs or agentic AI, but data identity resolution and integration capabilities still carry high barriers. In IT services, client conversations around AI and data integration are more active, but order recovery remains slow.

Risks

• The advertising market in 2027 may face pressure from a high base of sports events and political events, making growth comparisons more challenging.
• Macro and geopolitical factors such as the Middle East conflict may still disrupt advertiser budgets.
• Marketing organizational change may progress slowly due to short CMO tenures and more urgent competing priorities.
• LLMs and agentic AI may alter value allocation across DSPs and agency services, leading to repricing of some ad tech assets.
• Although LiveRamp-related capabilities are considered difficult to replicate, in-house alternatives from large agencies such as Omnicom and Dentsu may create competitive pressure.
• The conversion of AI and data integration into IT services growth remains slow, creating a risk that strong demand interest lags actual revenue realization.

What to watch

• Whether advertising spending from AI players continues to expand in 2H26 and keeps supporting upward revisions to media budgets.
• The actual monetization pace of generative search advertising revenue, and its diversion effect on traditional search, brand, and performance budgets.
• Whether major advertising agencies launch or scale LLM token procurement aggregation services.
• Whether growth in agency production revenue can offset the long-term pressure from AI automation on traditional service models.
• Whether DSP products are repackaged, replaced, or repriced by LLMs or agentic AI.
• Follow-up developments in data capabilities and transaction integration involving LiveRamp, Omnicom, Dentsu, and Publicis.
• Whether AI and data integration projects can re-accelerate IT services orders and revenue.