Advertising

AI Turned up the Heat for your Agency at Cannes 2025? DemandScience is Here with a Refreshing Data Driven Solution

Kiko Fronda

July 24, 2025

The article you’re about to dive into takes a hard look at the evolving intersection of AI disruption and macroeconomic uncertainty, and how both are reshaping the landscape for media and advertising. From budget pressure to talent upheaval and tech whiplash, the challenges are real and growing. But it’s not all doom and digital gloom. Amid the turbulence lie real opportunities, for those agile enough to adapt, smart enough to leverage AI strategically, and bold enough to lead the transformation.

The post review of the 2025 Cannes Lions and opinions have been surfacing in droves since the end of June. No surprise, this year’s Cannes Lions felt like a group therapy session for agencies and marketers trying to make peace with their AI overlords. Yes, robots are here—and they’re generating headlines, scripts, and maybe even a few existential crises. Cannes competition categories for this year have expanded but “no doubt, every category has been affected by generative artificial intelligence “Gen AI.” As agencies and their clients face the AI threshold for implementation, some headwinds have surfaced that agency leaders should consider.

Agencies Facing Media Investment Headwinds

The June 2025 update of the MAGNA Global Advertising Forecast reveals that while global ad revenue continues to grow, projected at around 7% for the year, the pace is moderate compared to the recent post-pandemic surge. Digital advertising remains the dominant force, now commanding roughly 70% of total spend, fueled by retail media networks, AI-driven performance marketing, and the continued popularity of short-form video formats like TikTok and YouTube Shorts. Connected TV is also gaining momentum as traditional linear TV and print media continue to decline. Despite steady growth, the industry faces headwinds including economic uncertainty, regulatory tightening (especially around data privacy and cookie deprecation), and geopolitical instability. Regionally, the U.S. leads with resilience thanks to robust political and tech sector ad spend, while APAC and LATAM markets are seeing faster growth due to mobile-first consumer behavior and e-commerce expansion. Europe remains steady but is more vulnerable to economic fluctuations. Overall, the report paints a picture of an industry evolving strategically to balance innovation with accountability and performance. As the agencies aim to achieve strategic balance that no doubt AI can address, the opportunity for agencies and acceleration may involve white labeling.

Let’s look at the most common GTM channels in B2B and when to use each.

The Way We Measure Time and Productivity Is Shifting with AI

Remember when agencies billed by the hour like lawyers with cooler clothes? Those days are looking numbered. AI can now whip up thousands of ads in less time than it takes a junior copywriter to open a Figma file. Agencies built on time-based pricing models are now nervously sipping oat milk lattes while trying to convince clients that human thinking still takes time even if AI just wrote five campaign concepts during their bathroom break.

Agencies Are Absorbing the Cost of AI to Stay Competitive

Many agencies are quietly footing the AI bill themselves. Instead of charging clients for the fancy tools that make their campaigns faster, smarter, and occasionally sentient, they’re absorbing the cost like it’s a free trial that never ends. It’s like giving clients a Ferrari ride and pretending you borrowed it from a friend, all while making car payments behind the scenes.

AI Is Changing How We Work, But People Still Play a Critical Role

While AI may boost productivity, it’s also boosting HR anxiety. Will copywriters become prompt engineers? Will art directors be replaced by Midjourney? Agencies are scrambling to reskill their teams so humans can “collaborate” with AI, which is corporate speak for not getting replaced by it. Thankfully, even the robots seem to agree they can do a lot, but they still need a human touch to make things make sense (and feel something).

AI Can’t Deliver Value Without Quality Data

You’d think feeding an AI thousands of data points would make it smarter. Nope. Without context, AI just turns into a well-spoken parrot with no idea what it’s saying. Agencies are drowning in data; but much of it is a steaming pile of “meh.” Until someone figures out how to clean and contextualize that mess. It’s still garbage in, garbage out. Which, coincidentally, also describes a lot of late-stage campaign revisions.

CMOs Want Transparency in AI-Driven Marketing

While agencies cozy up to AI giants like Google, Adobe, and AWS, their clients are asking awkward questions like, “What exactly am I paying for?” and “Why does this ad sound like it was written by HAL 9000?” CMOs want transparency. If AI is involved, they want to know what it’s doing, how much it costs, and whether it’s about to unionize. Without clearer answers, client trust could start to fray like a poorly optimized banner ad.

Integrating AI Into Workflows Is Easier Said Than Done

With increasing pressure to achieve more with fewer resources, knowing where to invest budget has never been more critical. We combine advanced technology and enriched data to drive the outcomes your clients care about most. In one example, we helped a client expand their target account list by 75% by uncovering high-potential accounts that had previously gone unnoticed. These were identified through intent signals, which were accounts actively researching the problems our client’s solution could solve. We then broadened job title coverage within those accounts to improve reach and relevance. The result? A 75% increase in TAL and a 35% boost in both campaign engagement and lead volume demonstrated the power of smarter targeting and strategic data application. Whether you’re facing pressure to prove ROI, adapt to AI, or unify disconnected data, DemandScience is the partner that makes demand generation simpler, smarter, and more profitable.

Agencies Accelerate with AI White Labeling

In today’s digital jungle—where algorithms move faster than interns at coffee runs, white-label AI is the secret sauce agencies didn’t know they needed. Forget building tech from scratch (who has the time or budget for that?). With plug-and-play AI platforms you can slap your logo on, agencies are now scaling like startup unicorns and padding profit margins like pros. It’s like showing up to a potluck with a store-bought pie and still getting asked for the recipe. New revenue streams? Consider them officially unlocked.

White-labeling AI technology presents a strategic opportunity for ad and media agencies to expand their capabilities, streamline operations, and strengthen their market position.2 It enables agencies to broaden their service offerings and revenue streams by integrating advanced AI features like SEO audits, automated ad creation, and analytics under their own brand. This makes them all-in-one providers and creates new improvement and client acquisition opportunities.

Second, white-label AI drives greater efficiency and scalability. By automating repetitive tasks such as content generation, data analysis, and reporting, agencies can focus more on creative strategy. These solutions also scale easily with growing client demands and allow for faster service deployment, giving agencies a competitive edge in a fast-moving market.

Lastly, it’s a cost-effective and brand-enhancing solution. Agencies can sidestep the high costs and complexities of building AI tools from scratch while still delivering cutting-edge, personalized experiences that boost client satisfaction. With rebrand-able interfaces, agencies maintain consistent branding and showcase innovation ultimately standing out in a crowded, tech-driven marketing landscape.

DemandScience Cannes help…

DemandScience offers outcome-based services that advertising and media agencies can resell or white-label removing tech complexity and enabling teams to focus on high-value strategy. Instead of hiring or training ops resources, agencies plug into a full-service engine that includes content syndication, multi-channel advertising, web personalization, and more. No onboarding or adoption of new tools, dashboards etc.

AI disruption is real, but DemandScience turns it into an advantage vs. concern. Our proprietary Insights platform enriches data, surfaces buying signals, and proactively recommends mid-flight campaign optimizations. No more fragmented reporting, manual research, or siloed metrics. Just one view—powered by AI but guided by human strategy. As Digiday highlights, marketers now have access to more data than ever but without the right context, it quickly becomes a case of “garbage in, garbage out.” At DemandScience, we take a methodical approach to how data is collected, structured, and interpreted. We’re intentional about what goes into our AI models, how we analyze the results, and—most importantly—what insights we surface to clients. While we use AI, we train our models on small language models that accurately represent what B2B marketers care about. Large language models lead to generic outcomes, but the company’s models’ home in on what agencies care about and help break through the sea of sameness that AI tends to generate. The result is not just more data, but smarter, more actionable intelligence that drives meaningful outcomes.

Traditional reporting often captures only the data generated during a specific campaign leaving marketers with an incomplete view and insights that exist in a vacuum. While helpful to a degree, this static, after-the-fact approach falls short in today’s fast-moving market. To keep pace with evolving conditions, agencies need dynamic, real-time intelligence. DemandScience helps agencies break free from data overload and static limitations by delivering enriched, validated insights drawn from firmographics, technographics, 1st- and 3rd-party intent, and competitive signals. Our data spans geographies, personas, job functions, and even identifies key influencers and decision-makers within target accounts. We overlay our campaign reporting with changing market conditions, so campaigns are not reported on in isolation.

Case Spotlight: Forcura’s Pipeline Surge with Integrated GTM Strategy

In a world saturated with dashboards and metrics, signals often get lost in the noise. Our focus is on quality over quantity surfacing only the most relevant insights, as they happen, to support agile decision-making. And while our automation streamlines the complexity, it doesn’t replace human creativity, it amplifies it. We empower agencies to deliver hyper-targeted campaigns with strategic precision and measurable results. The goal is to reach buying committees at the right time with relevant, specific content and messaging that speaks to that persona. For example, WaveMark was running a lead-based process, the team needed to reach prospects not only earlier but deliver highly targeted content and messaging to sway their decision. With DemandScience, WaveMark revamped their GTM strategy by identifying ICP accounts earlier in the journey and tailoring content and messaging to transform marketing into an influence driver.