How AI Will Reshape the Future Role of Marketers

Industry & Competitive Context

The global marketing and advertising industry entered a period of structural change between 2023 and 2026, driven by the commercial availability of generative artificial intelligence tools. This shift touched every layer of the industry: holding companies that run creative and media agencies, the brand-side marketing organizations of large consumer companies, and the technology vendors supplying the underlying AI models.

The scale of this shift is visible in the consolidation among advertising holding companies. In 2025, Omnicom Group Inc. and Interpublic Group (IPG) completed a merger valued at approximately $13.5 billion, creating the world’s largest advertising holding company by combined revenue. Philippe Krakowski, IPG’s CEO at the time of the deal, stated publicly that the combined company’s increased capacity to invest in a “leadership position in the tech and AI space” was central to the merger’s rationale, and he cited IPG’s proprietary AI platform, Interact, as a “key driver” of the company’s performance, noting that it was used by more than half of IPG’s employees and processed over a million prompts annually. Separately, WPP, one of the industry’s other major holding companies, reported a reduction in headcount from 111,000 to approximately 104,000 employees in the first half of 2025 a decline of roughly 7,000 roles alongside a drop in pre-tax profit from £338 million to £98 million over the same period. WPP’s outgoing CEO, Mark Read, attributed this primarily to pressure on client spending and a slower new-business environment, while the company’s incoming CEO, Cindy Rose (formerly Microsoft UK’s chief executive and, most recently, Microsoft’s chief operating officer for global enterprise), was brought in with a public mandate to sharpen WPP’s focus on AI and digital transformation.

On the technology-partnership side, WPP announced a collaboration with NVIDIA in May 2023 to build a generative AI content engine on NVIDIA Omniverse Cloud, incorporating tools from Adobe (Firefly) and Getty Images, alongside NVIDIA’s own Picasso platform for custom generative models. NVIDIA’s founder and CEO, Jensen Huang, framed the opportunity by referencing the digital advertising industry’s roughly $700 billion size as a market “racing to adopt AI,” while Mark Read described the partnership as giving WPP a differentiator unavailable elsewhere in the market.

On the brand side, consumer companies have begun disclosing how AI is changing their internal marketing operations. On a fiscal Q2 2026 earnings call, Procter & Gamble’s President and CEO, Shailesh Jejurikar, told analysts that AI and generative AI tools help the company’s teams “discover consumer-relevant insights” at each stage of the purchase path, drawing on sources that include traditional shopper research as well as social media and brand fan websites, and that these insights are converted into a “unifying brand idea” activated across connected TV, online video, social media, e-commerce, and in-store channels. P&G reported fiscal Q2 2026 net sales of $22.2 billion, up 1% year over year, and maintained full-year guidance of 1% to 5% sales growth.

Toy manufacturer Mattel also moved into this space, announcing a strategic collaboration with OpenAI in June 2025 to explore AI-powered products and experiences across its brand portfolio, including Barbie and Hot Wheels, with Mattel’s first OpenAI-powered product expected to be unveiled later that year. In October 2025, reporting indicated Mattel had also partnered with OpenAI around the Sora 2 AI video model.

Together, these developments show an industry moving on three fronts simultaneously: holding-company consolidation and cost restructuring tied explicitly to AI investment capacity, infrastructure partnerships between agencies and AI/technology vendors, and brand-side adoption of AI tools for insight generation, content production, and campaign activation.

Organizational Situation Prior to AI Adoption

Before this period of AI-driven restructuring, large marketing organizations both agency-side and brand-side operated on a model built around specialized human labor at each stage of the marketing value chain: strategy and insight generation, creative concepting, content production (photography, video, copywriting, localization), media planning and buying, and performance measurement. This model, as IPG’s Krakowski and WPP’s Mark Read both referenced in their public remarks, depended on manually producing large volumes of content through largely disconnected tools and teams a process NVIDIA and WPP jointly described, in announcing their partnership, as requiring creative teams to “manually produce hundreds of thousands of content pieces” from systems that did not talk to one another.

This labor- and tool-intensive model coexisted with growing fragmentation of media and retail channels. Jejurikar’s framing of the “new media reality” in which, in his words, “retailers are becoming media platforms and media platforms are becoming retailers” describes a landscape where the number of channels a marketing organization must plan, produce for, and measure across had expanded substantially, without a commensurate increase in the specialized headcount required to service each one at the same unit cost.

Strategic Objective

Across the organizations examined in this case, the stated strategic objective was consistent: to use AI to compress the cost and time required to produce marketing content and generate consumer insight at scale, while preserving or strengthening brand consistency and client differentiation. For WPP and NVIDIA, the explicit goal stated at announcement was an engine that could “outperform current methods” of content production and let clients reach consumers “in more personalized ways while preserving brand identity, products, and logos.” For IPG, the objective tied to its Interact platform was framed by Krakowski as a driver of company “success” and a basis for differentiating service offerings post-merger. For P&G, Jejurikar’s framing positioned AI-derived insight as a tool for sharpening the “unifying brand idea” that anchors a campaign before it is activated across a fragmented channel set. None of the companies in this case disclosed internal financial targets, return-on-investment thresholds, or efficiency ratios tied specifically to these AI initiatives in the sources reviewed;

AI Integration Architecture & Execution

The architecture of AI adoption documented publicly falls into two categories: infrastructure-level platforms built or licensed by agencies, and consumer-facing or insight-generation applications built or commissioned by brands.

At the infrastructure level, the WPP–NVIDIA content engine connects three-dimensional design, manufacturing, and creative supply-chain tools. WPP designers can use Adobe Firefly and Getty Images visual content generated with NVIDIA Picasso, a platform for building custom generative AI models. The stated outputs include two-dimensional images and videos for advertising campaigns, as well as interactive three-dimensional product configurators that can be streamed to consumers on web devices via NVIDIA’s Graphics Delivery Network. At the time of announcement, the companies stated the engine would be made available exclusively to WPP’s clients worldwide. Separately, in June 2024, WPP announced an AI-powered Production Studio, co-developed with its in-house production company Hogarth, intended to support content creation for marketing campaigns at scale; in July 2024, WPP and NVIDIA also announced work on generative 3D worlds. IPG’s Interact platform, described by Krakowski as processing over a million prompts a year with more than half the company’s employees using it, represents a second, independently built infrastructure layer within the now-merged Omnicom-IPG organization.

At the brand level, P&G’s approach as described by Jejurikar is insight-first rather than production-first: AI tools are used to mine consumer and shopper data including social media posts and brand fan websites, alongside traditional research to surface insights that inform both product innovation and the “unifying brand idea” behind a campaign, which is then activated through claims, demonstrations, and visuals distributed across connected and broadcast television, online video, social media, e-commerce platforms, and physical retail.

Mattel’s execution path, by contrast, centers on product rather than marketing process: its collaboration with OpenAI is aimed at embedding AI capability directly into toys and the experiences built around them described in coverage as exploring “AI-powered interactive toys” with the first OpenAI-powered Mattel product slated for unveiling later in 2025, and a subsequent reported partnership involving OpenAI’s Sora 2 video-generation model in October 2025.

Coca-Cola’s execution offers the most publicly documented case of AI used directly in finished advertising content. For its 2024 holiday campaign, Coca-Cola commissioned new, AI-generated versions of its 1995 advertisement “Holidays Are Coming,” described in coverage as the company’s largest push into AI advertising to date. One of the firms involved, Silverside AI, stated publicly that a project of this scope would typically take over twelve months to produce using conventional methods, but that its team of 40 completed it in two months using proprietary and market-available AI tools. The resulting ads featuring AI-rendered lighted Coca-Cola trucks, snowy roads, and townspeople aired on television that holiday season. This built on Coca-Cola’s earlier generative AI work: in 2023, the company had already launched a tool partly built with OpenAI that generated artwork from the company’s archived imagery, and later that year allowed consumers to generate personalized holiday cards using the same underlying capability.

Positioning & Consumer Insight

The organizations in this case positioned AI adoption differently depending on their role in the value chain. Agencies and holding companies (WPP, IPG, and by extension the merged Omnicom-IPG) positioned AI capability as a basis for competitive differentiation with clients a claim made explicitly by both Mark Read and Jensen Huang in describing the WPP-NVIDIA partnership, and by Krakowski in describing IPG’s Interact platform as a differentiator post-merger. Brand owners such as P&G positioned AI primarily as an instrument for sharpening consumer understanding in a more fragmented, retail-media-driven environment, rather than as a consumer-facing innovation story. Mattel positioned its AI partnership as a product and experience innovation aimed at children and families engaging directly with its toy brands, rather than as a marketing-production efficiency story.

Coca-Cola’s case is the most instructive on the question of consumer insight, because it is the only one in this case with documented public reaction data. A Yahoo/Publicis Media study cited in coverage of the ad found that approximately 77% of surveyed advertisers held a positive view of AI, compared with only 38% of surveyed consumers a substantial gap between industry sentiment and consumer sentiment that the Coca-Cola campaign appeared to surface directly. Reaction to the ad itself was publicly split: some commentary praised it as bold visual innovation, while critics, including Tim Halloran, a Georgia Tech professor with a decade of prior experience in Coca-Cola’s own brand management division, argued the AI-generated imagery undercut the brand’s long-standing “Real Thing” positioning and that it visually resembled a “poorly done imitation” of the 2004 film The Polar Express, with the broader criticism being that AI could not replicate authentic human emotion in a brand built on authenticity.

Media & Channel Strategy

Only limited, specific, verifiable detail on channel strategy is available from the sources reviewed. Coca-Cola’s AI-generated holiday ads aired on television as part of a seasonal campaign. P&G’s Jejurikar described insight-driven creative being activated across connected and broadcast television, online video, social media, e-commerce platforms, and in-store channels, with growing emphasis on retail media specifically, framed around the convergence of retailers and media platforms. No verified public information is available on the specific media budgets, channel mix percentages, or paid-media spend levels tied to any of the AI-enabled campaigns or platforms described in this case.

Business & Brand Outcomes

Documented, disclosed outcomes in this case are limited chiefly to financial and operational metrics rather than AI-attributable marketing performance metrics, and the case notes that distinction carefully rather than inferring causality that the source material does not support.

WPP’s reported financial results for the six months ended June 30, 2025, showed revenue down 7.8% (2.4% on a like-for-like basis, with the decline accelerating to 5.8% in the second quarter), pre-tax profit falling from £338 million to £98 million, and the interim dividend halved to 7 pence per share. The company’s own public statements attributed this primarily to client spending pressure and a slower new-business environment, not to AI adoption specifically; no verified public information is available linking WPP’s headcount reduction directly and causally to AI deployment, and the case does not assume such a link.

P&G reported fiscal Q2 2026 net sales of $22.2 billion, a 1% year-over-year increase, with the company citing continued softness in the U.S. market, and it maintained full-year sales growth guidance of 1% to 5%. The earnings call did not disclose specific, measurable outcomes attributable to AI-driven marketing insight generation; Jejurikar’s comments described the capability and its intended use rather than quantified results.

Silverside AI’s own public statement about the Coca-Cola holiday campaign claimed a compressed production timeline two months versus a typical twelve-plus months for a project of that scope representing the clearest documented efficiency claim in this case, though it is a vendor’s self-reported claim rather than an independently audited figure, and no verified public information is available on the campaign’s downstream sales or brand-metric performance.

On workforce and skills, the Microsoft-LinkedIn 2024 Work Trend Index, based on a survey of 31,000 people across 31 countries, found that 75% of knowledge workers reported using AI at work, that generative AI use at work had nearly doubled in the preceding six months, and that 78% of AI users were bringing their own AI tools into the workplace rather than waiting for employer-provided tools. On hiring, the same report found that 66% of business leaders said they would not hire someone without AI skills, that LinkedIn members adding AI-related skills such as Copilot and ChatGPT to their profiles had risen 142-fold year over year, and that job postings mentioning AI were associated with a 17% increase in application growth. These figures describe the broader knowledge-worker population surveyed by Microsoft and LinkedIn and are not specific to the marketing function; no verified public information is available breaking these figures out specifically by marketing job titles or marketing-department outcomes.

Strategic Implications

Four implications can be drawn directly from the documented record in this case, without extending into inference beyond what the sources support.

First, AI investment is becoming an explicit factor in industry consolidation and capital allocation decisions at the holding-company level. The Omnicom-IPG merger rationale, as stated publicly by IPG’s own CEO, cited increased AI investment capacity as a strategic driver, indicating that scale itself is being positioned by at least one major industry participant as a prerequisite for competing on AI capability.

Second, agencies are building AI not as a single tool but as infrastructure a content engine, a production studio, a proprietary prompt-processing platform used organization-wide suggesting that the locus of competitive advantage is shifting from individual campaign execution toward the underlying technology stack an agency can offer across all of its client relationships.

Third, brand-side disclosures to date, such as P&G’s, describe AI’s role in marketing primarily as augmenting insight generation and accelerating the path from consumer data to a unifying creative idea, rather than as replacing creative judgment. This is a narrower and more conservative framing than the content-generation-at-scale framing used by agencies and technology vendors, suggesting that brand owners and their agency partners may currently be emphasizing different parts of the AI value proposition.

Fourth, the Coca-Cola case demonstrates that the gap between industry sentiment toward AI (77% positive among advertisers, per the Yahoo/Publicis Media study) and consumer sentiment (38% positive) is a real, publicly documented, and reputation-relevant risk factor, not a hypothetical one. A marketing organization’s internal confidence in AI-generated content does not automatically transfer to audience acceptance, particularly for brands whose positioning rests on claims of authenticity.