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We’re two years into marketing’s AI era, and while just about every agency, brand, and publisher is actively experimenting with AI, far fewer are actually deploying it at scale and achieving the sort of gains that have captured the imaginations of C-suites everywhere.
For advertising leaders, the challenge now lies in not just adopting AI, but in integrating it strategically to deliver measurable business value.
This year’s Advertising Week New York offered insights into how industry leaders are leveraging AI and automation to make the most of their data, identify new opportunities to optimize campaigns, and transform their organizations.
The promise of AI is vast, with 87.9% of marketing and advertising professionals believing the technology will radically transform digital advertising within the next 3-5 years. But to unlock its potential and derive true value, organizational infrastructures must evolve.
It's not enough to adopt the latest tools—success will depend on an organization’s ability to enhance the speed and efficiency of the teams and processes that interact with AI. This requires careful vetting of prospective AI tools/partners, real budgetary commitments, involvement and buy-in from CTOs and CIOs, and a clear roadmap for change management. AI is a powerful tool, but without the right investment in people and systems, its potential will remain untapped.
Of course, in order to do this, leaders will first need to determine what, exactly, they hope AI can help them solve.
As with any new technology solution, AI should serve a specific purpose and be embraced as a strategic investment. Yet too often, AI is pursued as a novelty rather than a solution—another toy to toss onto the tech stack.
Some of this is the FOMO factor (“fear of missing out” on the emerging trend), but another is the technology’s sheer newness and complexity, which can leave many organizations overwhelmed. Due to no fault of their own, they often lack the internal expertise to distinguish between genuinely impactful AI initiatives and those that will drain time and budget without delivering real value. This is where agencies and other strategic partners can play a crucial role, guiding clients through this process and helping businesses unlock the potential of AI while ensuring it delivers measurable, responsible result.
The key to success is aligning AI initiatives with well-defined business problems. Deriving transcendent value from AI and automation will come from integrating it into everyday business processes, particularly in areas like data analytics, consumer insights, and strategic planning. Off-the-shelf models will rarely meet all of an organization’s needs— AI tools must ultimately be tailored to that organization’s specific goals and context. Think of it like onboarding a new team member: You’ll want to give these tools the time, training, and customization they’ll need to become effective. The payoff, however, is substantial, and once properly integrated, AI can deliver efficiencies, streamline operations, and provide a deeper understanding of what drives business outcomes.
In order to properly identify the right AI and automation tools for your organizations, it’s essential to start with a clear objective: What are your key performance indicators (KPIs)? What outcomes are you targeting? What’s your budget, and how much risk are you willing to take on? How much effort and resources will the project demand? How will you measure success (or failure)? Without clarity, even the most advanced technology will struggle to deliver value. Once these and any other essential parameters are established, clients can draft a brief and proceed with issuing a request for proposal (RFP) to identify the best-suited vendors for their AI initiatives.
Collaboration with trustworthy partners who can help troubleshoot and refine AI implementations is also critical. This requires transparency, not to expose intellectual property, but to ensure that both parties can maximize the value of the data and models in use.
Lastly, as with all things marketing, it’s crucial to have robust measurement framework in place. AI can help advertisers do some remarkable things, but without clear, reliable metrics that quantify its impact, even the most well-intentioned of organizations can miss out on potential benefits. Decision-makers must ensure they have the right systems in place to track and assess AI's contribution—otherwise, they risk investing in innovation without truly understanding its return on investment.
Taking a solution-agnostic approach and testing different models against one another in can help organizations identify the solutions that best fit their needs. Transparency and governance must also be central to any AI strategy, ensuring that teams are continuously evaluating performance and holding systems accountable. This not only builds trust, but ensures that the tech delivers consistent, meaningful value to your business.
In the last few years, AI-generated creative has earned quite a few headlines...for good reasons, and bad. And research indicates that most marketing and advertising professionals think of AI as primarily a resource for content creation: A 2024 Basis report found 57.4% of marketers believe content creation is the aspect of digital marketing process that will be most impacted by AI (despite the fact that 70.2% feel AI-generated content is worse than their organization’s human-generated content.)
But advertising leaders are starting to realize that the technology is likely to make its greatest impact on the media side.
This will, of course, require a change of mindset: When asked how their organization is currently using AI, more than 67.4% of industry professionals said they were leveraging it for drafting content/creative, just 10.6% said they were using it to develop their media buying strategy. Furthermore, only 8.4% named media buying as the part of the digital marketing process they expect to be most impacted by AI, and even fewer (6.4%) pointed to strategic decision-making. Yet AI’s greatest power lies not as a creative consultant, but as a sophisticated and turbo-charged engine for data-driven insights.
Large language models (LLMs) are particularly adept at uncovering patterns across complex datasets, helping marketers refine their media spend, optimize partner combinations, and even outsmart competitors with smarter bids. With AI, advertisers can consolidate disparate data assets across numerous platforms and touchpoints to get a more comprehensive view of media performance across all channels and platforms. Then, through data clean rooms and other trusted partners, they can subsequently layer third-party data onto those first-party assets to enable the kind of deterministic matching advertisers crave—providing more accurate targeting and measurement while maintaining the data’s privacy, integrity and structure.
With this approach, AI becomes less of a creative tool and more of a strategic asset—a way to make informed, data-driven decisions that elevate campaigns and sharpen competitive edges. And these benefits can extend well beyond traditional data engineering teams.
The chat capabilities of LLMs can empower non-data scientists to access and make use of complex datasets, “democratizing” the data and empowering teams across the organization. In this way, AI bridges the gap between specialists and generalists, enabling anyone to interrogate data and uncover insights without requiring advanced technical skills. As these tools become more intuitive and accessible, they will enable broader teams to contribute to data-driven decision-making. The goal, as with all things AI, is not to replace human expertise, but to augment it—giving marketers the tools to ask better questions and get more insightful answers.
AI has the potential to revolutionize how marketers use data to inform strategy and execution. But achieving this potential requires more than just adoption—it demands a disciplined, strategic approach. From optimizing media spend to enhancing consumer insights, AI and automation can elevate marketing effectiveness if implemented with care and purpose.
Scaling AI requires careful planning, agile testing, and thoughtful governance. Leaders must resist the temptation to adopt one-size-fits-all solutions. Instead, focus on model diversity and continual refinement. AI is a tool that can catalyze smarter, more impactful decision-making across an organization, but its value depends on how well it is integrated into that organization's core functions. By building transparent, adaptable systems and fostering cross-functional collaboration, leaders can ensure that AI not only enhances marketing efforts, but transforms them.
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Want to learn more about how advertisers are approaching AI, as well as how they’re thinking and feeling about an AI-driven future? Get all the latest insights in our report, AI and the Future of Marketing.