According to a recent Harvard Business Review study, 93% of Chief Data Officers agree data strategy is crucial for extracting value from generative AI, but a whopping 57% have made no concrete changes to their data foundations. Only 11% strongly agreed their organizations have the right data readiness for generative AI.
This should deeply concern marketing leaders. As companies invest in AI writing tools to generate customer communications such as emails, web content, ads and more, incomplete or inaccurate customer and product data will lead the AI to produce flawed, inconsistent or downright misleading content.
The hazards of this cannot be overstated. Even small data gaps or errors could spawn AI-generated marketing that promotes non-existent product features, perpetuates biases about customer segments, or spreads blatant misinformation to prospects. Such missteps would confuse customers, undermine brand trust, and actively drive away business.
The problem stems from AI's inherent limitations. Language models like ChatGPT merely reconstruct patterns from their training data. They lack common sense to detect when that data is faulty, incomplete or contradictory. The AI will simply amplify those flaws when tasked with generating any customer-facing content.
This makes vetting the data sources that feed into generative AI absolutely crucial, especially for marketers. We need to take ownership, understanding organizational data flows, ecosystems and potential gaps. Auditing and fortifying those data foundations must precede deploying generative AI for any customer communications.
While working on a particularly complex multi-system data integration project recently, it quickly became clear how duplicate contact data could lead to important messages either going to the wrong email address/phone number for that contact, or worse, sending false information to the right person.
Increasingly, digital marketing leaders will have to be the custodians managing the intersection of data, AI and the customer experience. It is part of our role to translate business goals into robust data strategies that enable trustworthy AI deployments in external communications. Otherwise, we risk undermining all our marketing efforts and customer relationships.
While generative AI's potential is immense, that potential is only as strong as the data we feed it. Prioritizing data readiness upfront is crucial to unlocking AI's value without inadvertently disseminating misinformation or alienating our audiences. Marketing leaders have a responsibility to get this right as data gatekeepers for the AI era.
