Turn AI's promise into marketing execution capacity
Three documented transformations explain why the economy of marketing execution changes: the expected level rises, AI moves the cost without removing it, and the value migrates to the orchestral system.
This page is a summary of this. The two analyses that support it are available below.
Digital marketing now requires an agency sophistication at the industrial level, while current organizations, costs and processes do not deliver it.
The expected level of marketing increases faster than operational capacity
Hypercompetition, expected customisation, fragmentation of paths, multiplication of channels: these developments are not independent. Together they increase the number of decisions, content and variants needed to remain relevant.
71%
consumers expect personalized interactions; 76% say they are frustrated when they are not.
Source: McKinsey, The value of getting personalization right.
10 +
channels used by B2B customers to interact with their suppliers, compared to five in 2016
Source: McKinsey, B2B dirty: omnichannel everywhere · buyers B2B.
- What studies showThe supply, content and contact points are growing faster than the attention available, while the expected relevance of each interaction is increasing.
- What this impliesThe marketing work is multiplying in a combinatorial way: audiences × intentions × products × channels × contexts. The cost of a relevant execution increases with the number of contexts to cover, not with the number of campaigns launched.
- Our convictionCompanies must now deliver sophistication once reserved for organisations with large teams, agencies, technologies and specialized expertise.
AI brings down the cost of generation, not that of reliable execution
Producing more has become accessible. Validating, controlling, integrating into the company's data, respecting brand rules and measuring the result has not become at the same pace.
< 10%
CMOs captured value on end-to-end marketing workflows, while almost 90% experimented with AI
Source: McKinsey, Reinventing marketing workflows with agent AI · CMOs surveyed.
-19 pts
the probability of getting the correct answer out of the model's jurisdiction, out of 758 consultants from an international firm
Source: Dell'Acqua et al., Navigating the Jagged Technological Frontier · controlled experience.
80%
big brands say they're worried about how their agencies use generative AI
Source: WFA, Annual Report 2024 · WFA member advertisers.
- What studies showGeneration capacity progresses much faster than the ability to validate, govern and integrate what is generated. Models remain probabilistic and their reliability varies greatly depending on the task.
- What this impliesThe bottleneck moves from production to validation, brand compliance, system integration and measurement. Multiplying outputs without processing these steps only shifts the cost.
- Our convictionThe new problem is no longer just to produce. It is to produce acceptable, controlled, traceable and efficient results in a repeatable way.
The next layer of value is the execution system
As models become commonplace, what distinguishes an organization is no longer access to the generation, but the ability to register it in a governed chain.
CAIAC is a platform for the execution of digital marketing allowing to internalize and industrialise part of the work traditionally carried out by agencies, connecting data, content, products, audiences, rules and performance in governed workflows.
Produce and personalize on a large scale
Pages, campaigns and content are available by audience, intent, product, market or context.
Enable company data
CRM, catalogues, analytics, content and behaviours mobilized in marketing decisions.
Manage and optimize execution
Analysed performance, opportunities detected, tested actions, re-injected results.
These three capabilities are not juxtaposed; they are performed by the same transverse layer: workflows resulting from agency methods — framing, analysis, production, controls, iterations, validation, measurement — which orchestrate agents, data, tools and human interventions at each stage.
Agency quality, internal knowledge, technological speed and scalable cost
Historically, marketing sophistication was purchased — by specialists, agencies, teams, coordination. Each level of additional relevance was paid in hours and interfaces.
AI reduces part of this production cost, but shifts complexity towards integration, controls, governance and orchestration. Available work converges on this point: BCG estimates that only 10% of the value of an AI transformation comes from algorithms and 20% from technology, compared to 70% from people and organization.
Source: BCG, AI transformation is a workforce transformation.
It is on this equation that CAIAC positions itself: to make accessible a level of agency execution without re-establishing its organizational cost.
Sources and methodology
The figures cited come from works published by third parties' firms, institutions and laboratories, and we take them back to the area of origin — the population interviewed, category, year, forecast or observed result — without broadening it. The analyses and convictions that accompany them are ours and are reported as such.
- Havas, Meaningful Brands 2025 — meaningful-brands.com
- McKinsey, The value of getting personalization right — www.mckinsey.com
- McKinsey, B2B dirty: omnichannel everywhere — www.mckinsey.com
- McKinsey, Reinventing marketing workflows with agent AI — www.mckinsey.com
- Dell'Acqua et al., Navigating the Jagged Technological Frontier — doi.org
- WFA Annual Report 2024 — wfanet.org
- BCG, AI transformation is a labourforce transformation — www.bcg.com
Your marketing doesn't need one more tool. It needs an execution capability.
Identifies workflows that can be connected, governed and scaled with CAIAC.