From Idea to Impact: How Enterprise Brands Are Actually Using GenAI to Drive Growth

When generative AI entered the enterprise conversation, most leaders were caught between two forces: FOMO and fear. For Ajay Dhaul, former SVP at Kenvue, the key was finding a responsible way to experiment early without compromising privacy, brand integrity, or business value.

In a focused fireside chat at CommerceNext, Dhaul joined Writer’s VP of CPG, Kushala Silva, to share how billion-dollar brands are moving from experimentation to execution with GenAI now embedded across content creation, personalization, knowledge management, and go-to-market workflows.

Back in early 2023, the promise of GenAI was obvious but so were the risks. Dhaul described that moment as a balancing act between innovation and governance. Large enterprises like Kenvue (then still part of Johnson & Johnson) had to figure out how to test GenAI tools without risking IP leakage, brand inconsistency, or regulatory exposure.

That meant looking for enterprise-ready partners and building guardrails from day one. The result was a structured collaboration with Writer that began not with models, but with trust ensuring brand voice, privacy, and data use were fully aligned before scaling.

For Dhaul’s team, the entry point was clear: follow the money. Growth was coming from eCommerce and social commerce. The goal was to accelerate new product introductions and win on emerging channels, faster and with more agility.

The first big question? Whether GenAI could create brand-safe marketing content at scale. Skepticism quickly gave way to results: the team was able to train Writer’s model on iconic brands like Listerine and Johnson’s Baby in days, not months. From there, use cases moved up the value chain from content creation to enterprise-level knowledge search.

Why search? Because enterprise knowledge is scattered across R&D labs, clinical studies, packaging specs, and regional files. Centralizing that data then unlocking it with GenAI gave marketers and innovation teams access to insights that previously took weeks to surface.

As Silva noted, the early phase of GenAI adoption was driven by experimentation. But the shift now underway is more strategic. Enterprises are no longer asking, “What can GenAI do?” Instead, they’re asking, “Where should we deploy it for the highest ROI?”

That reframing changes everything. When companies only chase low-risk use cases, executive engagement stays low. But when use cases deliver fast, visible returns, leadership interest grows and so does investment.

Dhaul emphasized the importance of tying AI initiatives directly to strategic growth priorities. He described how his team embedded GenAI across the commercial “score”, the full GTM cycle from market insight to campaign execution. Use cases ranged from category analysis to media asset generation, all tied to clear performance outcomes.

Looking ahead, the next evolution is already underway: AI agents. But Dhaul was careful to temper the buzz.

Many companies, he said, are still in the middle of defining their core processes, much less automating them. Agent-based AI only works when workflows are well understood and intentionally reimagined. Otherwise, brands risk automating broken systems.

Instead, he advocated for a more disciplined approach: value stream mapping, business-led design, and partnership between tech and commercial teams. Once that foundation is set, AI agents can begin handling sub-processes, accelerating execution and reducing time to market.

Dhaul shared a few takeaways for leaders navigating GenAI inside complex organizations:

He closed by noting that the most exciting shift is cultural: “Business users are becoming builders.” With the right tools and training, they no longer need to wait months for IT to deliver capabilities. They can prototype, test, and scale workflows themselves.

ClickZ is a ClickZ Media publication