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Today, customer service plays a defining role in how individuals perceive a brand. A single bad experience with an AI agent could mean a lost customer for good. But when done right, AI is also an opportunity for brands to deliver a satisfying customer experience. So, where’s the disconnect? It comes down to the foundation. Without high-quality content and a strong governance framework, AI agents fall short, putting both the customer experience and your brand reputation at risk. Getting it right ensures every interaction not only ends with a delighted customer, but is also safe and aligned with your brand guidelines.

Here’s what I’ve been telling leaders: customer service is no longer just a support function — it’s a brand differentiator. To truly deliver a memorable AI-powered customer experience, it starts with high-quality content. Why? Because an AI chatbot is only as good as the content it‘s trained on. This is where content governance comes in, providing a framework to ensure that AI chatbots follow brand policies, guidelines, and tone. As chatbots become the voice of brands in many customer interactions, it’s also essential to make sure they’re saying the right things.

The pace of AI development today outpaces the talk of governance. So, how are the companies using and building AI products navigating governance? They are writing their own norms to nudge AI use while protecting customer data, mitigating biases, and fostering innovation. And how does this look in practice? I spoke with leaders at Salesforce, Zendesk, Acrolinx, Sprinto, and the G2 Market Research team to find out.

As companies brave the complexities of AI governance, understanding the perspectives of key leaders like CTOs, CISOs, and AI governance executives becomes essential. Why? Because these stakeholders are pivotal in shaping an organization’s risk posture. Let’s explore what these leaders think of current tools and zoom in on their GRC priorities.

The report provides insights for marketing leaders assessing these technologies, covering key areas such as: The factors driving the adoption of generative AI solutions for content creation. The core capabilities provided by these solutions and how the AI boom impacts available offerings. The different types of providers in the market, like Acrolinx. Cost considerations for the adoption of generative AI for content creation.

Without universal policies, organizations face FOMO (fear of missing out) and are forced to navigate the wild west of AI innovation on calculated plays. Organizations are also threatened with operational inefficiencies, compliance burdens, and strategic uncertainty. “The lack of a universal AI policy definitely holds organizations back from innovation as they struggle with fragmented AI regulations,” says Matt Blumberg, Chief Executive Officer at Acrolinx.

Without solid governance, generative AI’s potential can just as easily become a source of risk. When I talk to other CEOs and business leaders, one thing keeps coming up: Regulation, or the lack thereof. This massive, complex issue is keeping a lot of us awake at night. We’re still operating in a regulatory gray area two years into the generative AI boom. But that hasn’t stopped compliance requirements from tightening across industries. The pressure is real and it’s only growing.

In my conversations with other CEOs and business leaders across industries, one of their primary concerns I hear about is risky AI-generated content. They ask, “In a world where countless AI agents and subject matter experts generate content, how can we ensure it remains compliant, on-brand, and free from potential legal and reputational risks?” The answer is simple: Businesses need to think about content very differently.