Artificial intelligence is rapidly changing how brands and customers interact. AI-powered chatbots, zero-click search results and targeted messaging are accelerating the connection between thought and outcomes, challenging traditional marketing channels and touchpoints. To capitalize on this shift, brands need a corresponding jump in both the quality and depth of their data — the indispensable fuel that turns a model's expectations into accurate recommendations and action.
“You could say data is ‘king’ or ‘queen’, but now it’s the universal force,” says Graham Wilkinson, chief innovation officer and global head of AI at Acxiom, a data and identity solutions company connecting brands with 2.6 billion people globally. “You need trusted, connected, clean data as a foundation for AI.” To drive both big-picture innovation and growth, brands must empower experts and curious minds to pair the right AI models with data curated for diverse business needs.
Ahead, explore what it takes to become an AI-driven brand, and establish a culture with the expertise and processes to maximize AI investments.
Data's Defining Moment And The Need For Curated AI Ecosystems
On the path to becoming an AI-driven enterprise, C-suite leaders are grappling with a fundamental obstacle: data quality. In Forbes Research’s 2024 AI Survey, 31% of CxOs cited data quality as a main challenge for AI adoption over the next two years. And just 33% rated their current data cleaning and reprocessing for AI initiatives as effective.
"Many organizations don't necessarily have their data in order, including having the right, curated foundation that will fuel their AI," says Jarrod Martin, global CEO of Acxiom. "Data readiness is fundamental to realizing the promise of AI."
Organizations are already taking steps to apply AI at key consumer touchpoints. For example, 72% of CMOs in the Forbes AI Survey said they use AI chatbots and virtual assistants, with 27% using them extensively to provide real-time personalized responses.
Despite this, only 9% of CEOs find AI to be very effective in achieving enhanced CX as a strategic goal, and less than a third of CxOs say their use of AI has very positively impacted CX metrics.
Making the most of generative AI agents takes more than just accelerating traditional, siloed marketing workflows. Strategists must seek insights and opportunities outside the linear model and single-tool solutions, says Wilkinson. By rethinking their marketing workflow, brands can meet the needs of thousands of different customers with dynamically created assets.
With the right tech, connected data and AI in place, brands can go from building a campaign in months to one day, he notes, adding that while execution is not perfect yet, the need for speed is here. These advancements aren’t just about efficiency—they’re about accurately building campaigns that can engage your audience across channels based on timely data.
“AI transforms marketing into a high-velocity learning lab,” says Martin. “Now brands can leverage their data and identity to test creative elements in a dynamic environment and make the most of their marketing and tech investments.”
Martin adds that this same principle applies to the AI platforms that brands use. Since different models have dramatically different strengths, it’s unlikely that any one model or tool will solve all challenges. Instead, he says organizations should pair their curated, privacy-compliant data with models best suited to specific use cases.
Overcoming AI Adoption Challenges And Building Scalable Solutions
As AI-assisted interactions and recommendations become the norm, brands must ensure they have a scalable cloud infrastructure to deliver AI insights and a steady, credible flow of data to their models. The Forbes AI Survey showed that real-time data integration is among the top five CxO strategies for AI success. On questions of AI readiness, leaders take a positive stance on operational challenges.
In Forbes Research’s CxO Growth 5.0 Survey, 66% of CxOs agreed that AI democratization has led to more innovation and informed decision-making at their organization. The Forbes AI Survey also showed just 31% of respondents see integration with existing systems and processes to be a main challenge to AI adoption, and 69% are confident their organization has a scalable cloud infrastructure suitable for AI workloads and applications.
Martin suspects leaders may be overconfident, adding that both the marketing and ad tech spaces are heavily fragmented and still dominated by legacy solutions. “Once we start to reduce the amount of complexity in that MarTech stack, we can then start to unlock the power of AI incrementally,” he says.
On the talent front, Wilkinson says the AI skills gap is less about certifications and more about mindset. He advises cultivating a systems-thinking approach, one that re-evaluates what’s possible with new technology rather than adhering to past constraints. “It’s not about just going out and acquiring new talent,” he says. “You’ve got to take your existing talent on a systems-thinking journey.”
He adds that the right strategic partner can provide the technology and expertise to smooth deployment challenges and maximize return on investment. And to ensure a unified purpose that avoids fragmentation, leadership must have a clear governance structure that welcomes all voices at the table.
Acxiom And Interact Power AI-Driven Transformation
Knowledgeable partners who work directly with multiple AI models and have a proven track record of delivering brand growth are essential to progress.
Interact, a comprehensive marketing platform, leveraged Acxiom's connected identity and data to help a major U.S. sports league overcome siloed internal teams. This allowed them to drive engagement through personalized campaign activation, powering brand growth. Within Interact’s AI platform, five distinct digital twin audience agents — AI models customized to emulate the league’s primary fan groups — were developed and interacted with to gain previously impossible insights. The outcome was undeniable: the AI-augmented personalized ads outperformed non-AI ads by 23%. High-impact display ads saw an 18% increase in tune-in conversions per thousand impressions.
As an experienced AI implementer, Acxiom helps brands tailor AI models and build specific goal-based applications, ranging from omnichannel experiences to marketing pipeline automation. “Small models, large models, adaptive models, open source models—they all have their place in different aspects of the workflow,” says Wilkinson, stressing that brands should avoid relying on generalized models and focus on tailoring their AI models to specific use cases.
Martin says that trusted partners help brands see where outdated or siloed approaches can be modernized. “There are clients with the mindset that AI will drive efficiency of the current process,” he says. “If we think differently and realize AI-powered design systems, then we unlock incremental growth rather than just efficiency.”
While the use of autonomous AI models for brand growth is in its early stages, brands have an opportunity to seize a first-mover advantage, adds Martin. “The industry at large is super-laser-focused right now on efficiency,” he says. “I believe building AI models with a growth mindset will drive the bigger opportunities.”