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What 2025 Revealed About AI, and What It Unlocks in 2026

What 2025 Revealed About AI, and What It Unlocks in 2026

AI AI, AI & Emerging Technology Consulting 5 min read
Profile picture for user mediamonks

Written by
Monks

A portrait of a woman in profile, facing right, with her blonde hair blurred as if in motion. She wears a black turtleneck against a dark, moody background featuring abstract magenta and purple rectangles and vertical lines. Her face is illuminated, while the rest of the image has a blurred, dreamlike quality.

2025 served as the definitive pivot point where artificial intelligence matured from a technical curiosity into a foundational organizational layer. Throughout the year, the strategic focus evolved from testing isolated tools toward architecting unified operating models that redefine the mechanics of modern work. This progression represents the shift from the "art of the possible" to the “architecture of the actual”—a transition into structured systems that deliver high-fidelity results at global scale.

The signals surfacing across 2025 have now crystallized into a strategic mandate: the industrialization of intelligence through workflow orchestration, proprietary data flywheels, and the persistent activation of brand DNA. From these signals, we can define the strategic conditions brands will navigate throughout 2026.

Marketing operations are entering the era of orchestration.

In 2025, marketing teams began moving away from isolated AI pilots to instead implement coordinated, agentic systems capable of executing work across multiple steps, continuously and at scale. These orchestrations, which redesign how collaboration is structured within the organization, connect strategy, creation, execution, and measurement within a single, connected system rather than as handoffs between silos.

This shift also presents brands with a clear exit from “pilot purgatory,” the cycle of fragmented, small-scale tests that often lack the structural weight to drive meaningful business change. By moving beyond isolated experiments and into full-scale orchestration, organizations are replacing curiosity-led pilots with a strategic architecture that connects thinking across the marketing lifecycle. This ensures that intelligence isn’t just a bolt-on tool, but a foundational component capable of dismantling legacy silos and driving high-velocity growth.

What this means for 2026: Orchestrated workflows will drive the industrialization of intelligence, serving as the bedrock for always-on marketing operations that unify creative production, commerce and optimization. Marketing teams will increasingly realign their structures, moving beyond the bottleneck of manual execution toward the strategic orchestration of agentic systems. 

Experience became the primary competitive lever.

As marketing operations became more orchestrated in 2025, experience design evolved to generate new data that could enable further personalization and consumer insights, operating as a sort of flywheel. By inviting consumers to collaborate and co-create within a generative framework, brands can capture rich, contextual signals that were previously trapped in black-box media or biased polling. This turns every interaction into a dual-purpose event: providing a meaningful consumer experience while simultaneously filling critical data gaps with owned, actionable information. When experiences are architected this way, the strategic starting point changes, leading with the fundamental question: “What data am I after?”

Under this architecture, participation is no longer just an engagement metric; it functions as a primary data-generation event, feeding high-fidelity, first-party signals directly into a brand’s agentic ecosystem.

AI serves as the connective tissue here, enabling experiences to ingest real-time data and output hyper-personalized assets without the friction of manual production. A primary example of this is our work with the Boomtown music festival, “Boomtown Unboxed,” which transformed attendee engagement into a scalable data engine and hyper-personalized creative. The platform utilized first-party event data captured throughout the festival to dynamically assemble high-fidelity recap footage unique to each individual attendee.

By treating the experience itself as a massive data-capture environment, AI became the unlock to transform attendance into insight, informing creative assembly and deepening emotional resonance. Creative automation allowed the experience to adapt to each participant at a level of granularity that legacy workflows simply cannot match.

What this means for 2026: As content saturation renders traditional engagement episodic, experience design must shift into an always-on system that continuously harvests intelligence to sustain

Authenticity emerged as a strategic asset.

In 2025, authenticity shifted from a philosophical ideal to a critical operational capability. As generative tools lowered the technical barrier to content creation, the market saw a surge in homogenized, generic outputs that lacked the distinct soul of the brands behind them. On the flip side, strategic brands sought to encode their unique visual heritage, tone of voice and proprietary audience insights into their AI systems, enabling creative at scale that is deeply authentic to the brand.

The most durable competitive advantage no longer comes from mastering off-the-shelf tools, but from training foundational models based on the brand's own history. By ingesting proprietary mascots, intellectual property, and creative principles, brands can ensure their AI-assisted work is instantly and recognizably their own. This move, from one-off prompting to a living brand brain, allows for the scaling of expression without the dilution of meaning.

Conversely, the market has seen the consequences of misalignment. When brands rely on generic public models to represent their identity, they risk falling into the uncanny valley of brand representation. You’ve likely seen a handful of high-profile missteps throughout the year, where the use of artificial, generic models felt misaligned with the brand’s core values or the diversity of its audience. Such outputs often feel like an intrusion rather than an extension, eroding the very trust the brand worked for decades to build.

What this means for 2026: As AI becomes embedded across content operations, authenticity will function as a performance driver. Governance and brand-specific foundational models will become essential components of modern marketing systems, ensuring that scale strengthens recognition rather than creating fragmentation. 

Discoverability is being redefined by AI interfaces.

As AI agents become central to everyday planning and retrieval, discoverability is no longer a matter of simple keyword ranking. Over the past year, discoverability has come to depend on branded content’s ability to be reliably retrieved, understood and cited by generative systems as a definitive source of truth.

This has birthed the era of Generative Engine Optimization (GEO). While traditional SEO optimized for visibility on a results page, GEO optimizes for inclusion within an AI-generated synthesis. This shift demands a move away from keyword density toward contextual accuracy, structured metadata, and verifiable credibility. 

Consequently, discoverability has transformed from a tactical marketing challenge into a foundational infrastructure requirement. Brands that invest in structured knowledge bases and machine-readable content ecosystems create the conditions for AI agents to reference them with confidence, reducing the risk of ambiguity or hallucination. Content must now serve two audiences simultaneously: it must remain emotionally resonant for humans while being architecturally legible for machines. Modular formats, authoritative sourcing and multimodal assets are the new table stakes for reducing inference guesswork by AI intermediaries.

What this means for 2026: Search strategy will expand beyond the logic of search result rankings. Success will be defined by citation and trust, as brands architect content ecosystems that serve as the primary nodes of recommendation within agentic interfaces. 

In 2026, intelligence maturation becomes a structural necessity.

The shift from 2025’s experimentation to 2026’s execution represents the final maturation of the AI-native enterprise. Competitive advantage now follows the industrialization of intelligence, moving past task-level gains toward a cohesive agentic architecture that unifies strategic intent, creative craft, and operational execution.

This evolution has transformed what was once a luxury of curiosity into a foundational structural necessity. Performance in this landscape is defined by the depth of system design and the purposeful activation of a brand’s proprietary DNA. By dissolving legacy silos and architecting unified flows, organizations can finally turn the complexity of orchestration into their most enduring source of compounding advantage.

2026 marks the industrialization of intelligence. Explore the shift from isolated AI pilots to orchestrated agentic systems and marketing operations. 2026 marks the industrialization of intelligence. Explore the shift from isolated AI pilots to orchestrated agentic systems and marketing operations. agentic ai Generative Engine Optimisation (GEO) brand DNA marketing operations AI & Emerging Technology Consulting AI

The Answer Engine Battles: Navigating the ChatGPT Ad Rollout

The Answer Engine Battles: Navigating the ChatGPT Ad Rollout

AEO/GEO AEO/GEO, AI, AI & Emerging Technology Consulting, Media Strategy & Planning, Paid Search, Performance Media 4 min read
Profile picture for user Tory Lariar

Written by
Tory Lariar
SVP, Paid Search

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The wait is over: OpenAI has officially announced they are moving into the testing phase for ads. As of January 16, 2026, the company confirmed it is beginning to test ads in the U.S. for logged-in adult users (18+) on the Free and the newly launched ChatGPT Go ($8/month) tiers. Here’s what brands need to know as this long-speculated move unfolds.

OpenAI confirms initial ad details.

OpenAI is proceeding with extreme caution to protect the “answer independence” that makes the platform valuable.

  • Placement & Format: Ads are contextual text ads located at the bottom of the chat response. They will be clearly labeled as "Sponsored" and physically separated.
  • Privacy & Opt-Outs: OpenAI promises not to sell user data to advertisers or make conversations accessible to them. Users who want more control over their experience and their data can turn off personalization, clear ad data, or opt for a paid, ad-free tier (as of launch, this will include Plus, Pro, Business, Enterprise, and Edu).
  • The Demographics: The ad-supported audience will likely skew young, based on OpenAI’s research study of consumer ChatGPT usage. Gen Z is dominant among demographics on the platform. The study shows 58% of adults under 30 use ChatGPT consumer plans, and their activity makes up a large volume of conversations: nearly half of all messages come from users under 26. Adoption drops to just 10% for users over age 65.
  • Pricing & Access: No public self-service advertising platform exists yet. OpenAI has not released pricing or an application process to join the tests, but early reports indicate a pay-per-impression (PPM) pricing model will be used, with up to seven-figure media commitments.

The rollout follows a strategic path.

While official details are sparse, our analysis of the rollout suggests a specific trajectory will be most likely:

  1. Vertical-Specific Testing: Initial tests will likely be an invite-only closed beta for enterprise brands focused on the D2C vertical. We expect industries like Retail and Travel to be emphasized. They have high-intent data feeds that are easily mapped to AI queries, making them a common first testing ground for other answer engines releasing new products and new experiences in the last few years.
  2. The "Perplexity" Precedent: Like early tests on Perplexity, we expect initial placements to be limited—potentially only one advertiser per answer experience—to maintain a premium feel and support their “answer independence” philosophy. ChatGPT head Nick Turley said in an interview last year that any ad experience would need to be "tasteful" to avoid disrupting the experience, fueling this likelihood.
  3. Activating via Contextual Intent: OpenAI has described the eventual ad experiences as contextual to the conversations. Given the fluidity of a "conversation" with ChatGPT and the evolutions of the search industry overall, we suspect that instead of bidding on specific keywords, advertisers will likely be bidding on specific prompts and target personas.
Image of a man in a t-shirt using an LLM engine from his cell phone.

Prepare, don't just wait.

Brands are hungry for placement in this space, but ChatGPT ads won’t be a fit for every advertiser. All brands should first consider the alignment with their target market before making a plan to invest. Per the demographics above, there is a risk of a demographic mismatch for brands in B2B, or those that target middle-aged or senior demographics. The users seeing ads (Free/Go tiers) are statistically more likely to be students or early-career professionals. Plus, while all LLM adoption tends to correlate with higher educational attainment and greater household income, the most tech-savvy users are more likely to be using the ad-free Pro/Business tiers. While ChatGPT usage has grown exponentially, that doesn’t mean your target audience is spending a notable amount of time on the platform.

Currently, we are advising brands to embrace the "duality of visibility" in their AI answer engine strategy. You cannot succeed in Paid without a solid Organic foundation, so our recommendations for brands is to prioritize the below.

Step 1: Prioritize AI Visibility (AEO/GEO)

If your brand isn’t cited in the organic response, your ad will feel like an intrusion. Increase your odds of getting cited organically by optimizing your:

  • Content Density: LLMs prefer "dense" data over marketing fluff. Focus on long-form FAQs, transparent pricing, and competitor comparisons.
  • Technical Readiness: Ensure Server-Side Rendering (SSR) and Schema markup are implemented so bots can easily digest your site.
  • Permit Crawling: Verify that your robots.txt is not blocking GPTBot or Google-Gemini.

Step 2: Define Your Persona Strategy

Determine exactly what questions and contexts you want your brand to show up for. Optimize your on-site content to answer those specific prompts. Ensure your brand has a presence on “source” sites that AI trusts, such as Wikipedia, YouTube, and high-authority community forums.

Step 3: Budget for Experimentation

As the testing expands beyond the initial invite-only phase, brands should have “test-and-learn” funds ready. Success in the conversational AI space will require a different set of KPIs than traditional search, focusing on intent alignment rather than just click volume. The right KPIs and tools will be critical to bringing AEO (answer engine optimization) and traditional search (both paid and organic) data together to make it easier to understand holistic trends for engaged consumers in your industry.

Optimize to ensure long-term visibility.

The launch of ChatGPT ads increases the available real estate for advertisers to reach engaged, intent-rich consumers. While this will only be accessible to a select set of advertisers in the near term, every brand should compare their target audience to ChatGPT’s user base to understand the growth opportunity for them on the platform. In the meantime, brands who invest in answer engine optimization (AEO) will be poised for the strongest positioning and performance once advertising opens up more broadly. Use an in-depth guide to engine optimization to begin testing your AI readiness and measure your baseline performance, and be ready to strike when the opportunity becomes available.

OpenAI begins testing ChatGPT ads. Learn what brands should prepare for ahead of rollout, including how to optimize your brand for AI answer engines (AEO/GEO). OpenAI begins testing ChatGPT ads. Learn what brands should prepare for ahead of rollout, including how to optimize your brand for AI answer engines (AEO/GEO). ChatGPT paid search Generative Engine Optimisation (GEO) Answer Engine Optimization Paid Search AI & Emerging Technology Consulting Media Strategy & Planning Performance Media AEO/GEO AI

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