Artificial intelligence is reshaping how work is done, at least in theory. In practice, many consumer brand companies are experimenting with AI intermittently, with high optimism but fragmented execution. Most leaders anticipate AI will transform roles and team structures, yet very few have taken concrete action. Drawing from our latest trend brief, How AI Is (and Isn’t) Reshaping Consumer Brand Teams, and additional industry research, we identify three core patterns and outline how growth-stage consumer brand leaders can evolve small-scale pilots into organization-wide initiatives.
Founder AI Enthusiasm Fades Without CEO Follow-Through
In many high-growth companies, founders are the first to champion AI, diving in with early experiments to make workflow more efficient. But without strong CEO and executive support, these founder-led initiatives struggle to gain traction. Our trend brief reveals a divide: 26% of founders said they’ve made AI-driven org or role changes, yet only 8% of CEOs reported the same. If top leadership isn’t actively involved, early AI wins risk fading away before they influence the wider organization.
This gap between vision and execution is reflected in broader studies as well. McKinsey research notes that executive sponsorship is a key factor for AI leadership; 44% of organizations with top AI performance have CEO or board-level support for AI initiatives, more than double the rate among lagging organizations. It’s not that CEOs are resisting AI; many are waiting for validated business cases or cross-functional alignment. Yet too much caution at the top can dampen the founder’s excitement and stall progress. AI initiatives need both bottom-up energy and top-down commitment. Leaders who move beyond experimentation and integrate AI into core strategy set the stage for real impact.
Marketing and Tech Are First Movers, But Testing Remains Isolated
Within organizations, adoption is often uneven across functions as well. Marketing and technology teams tend to be the first movers, as they’re more inclined to try generative AI for content, customer engagement, or software development. In the ForceBrands survey, one in three marketing leaders (33%) said AI is already influencing their early team planning decisions, far ahead of other functions. It’s not surprising, considering how company tech and marketing groups are often the first to engage with emerging platforms and technologies to fulfill their functions. However, these wins remain confined within those departments as operations, finance, HR, and others lag behind, “waiting for broader organizational alignment before taking action.” The result is that AI’s benefits don’t translate beyond the local level, leaving organizations static despite pockets of innovation.
Harvard Business Review highlights this risk: AI can inadvertently reinforce functional silos. Departments may optimize individually with AI, but without coordination, those gains rarely translate into meaningful progress against the company’s larger strategic vision, as company-wide improvement remains at a standstill. This “silo effect” can cause AI initiatives to lose momentum, as changes are confined to a single team or use case.
The Execution Layer Is Experimenting Without a Roadmap to Scale
Even when top leadership is on board and certain teams are making progress, another challenge emerges at the execution layer. Vice Presidents and Senior Operators, who are closest to day-to-day delivery, feel increased pressure to understand AI, leading them to implement AI tools without leadership guidance. In our survey, mid-level leaders were asked how AI is affecting their team’s work, and the responses were telling: some are running early-stage pilots, while others have been told to “prove AI can’t do the work” before they’ll get approval to hire staff.
These managers are experimenting under pressure, expected to deliver AI-driven efficiencies without clear strategic guidelines from higher-ups. It’s a recipe for frustration and fragmentation. Without guidance, AI learnings stay isolated and never form into a scalable solution set. To avoid this, companies need a pathway that connects those grassroots experiments to an organizational strategy.
For AI adoption to proliferate the organization, companies must give operational teams permission to fail and learn, while also providing structure: direct objectives, resource support, and a plan for scaling up successful pilots into cross-functional workflows. The execution layer can be a wellspring of innovation only if it’s guided by a unifying vision of where AI should take the business.
How to Go From Disjointed Efforts to Companywide Success
For growth-stage consumer brands to break out of this disjointed adoption cycle, they must start with bridging the gaps between founder vision and CEO action, between siloed department wins and enterprise strategy, and between scattered experiments and a roadmap for scale. ForceBrands, as a people strategy advisor for high-growth brands, offers an integrated toolkit to help leaders connect these dots. Our advisory solutions are designed to turn stalled pilots into empowering programs by focusing on organization-wide readiness, alignment, and guided execution. Key offerings include:
- AI Readiness Snapshot™: A benchmarking of your organization’s AI maturity and mindset; pinpointing where you stand today and surfacing blockers that could hinder adoption.
- AI Value Map™: A planning framework to translate your AI ambitions into a distinct 12–24 month roadmap.
- AI ChangeFit Toolkit™: A change management playbook to equip your team for the shifts ahead without overwhelm.
- Fractional AI Lead™: An embedded, part-time AI leader who can drive AI implementation from the inside.
With these solutions, the goal is to create cohesion by recognizing that navigating AI change is as much about people as it is about technology.
Ready to turn stalled AI initiatives into engines of growth? For a deeper dive into these trends and practical guidance tailored to consumer brand organizations, download our Trend Brief: How AI Is (And Isn’t) Reshaping Consumer Brand Teams. It’s packed with data-driven insights and self assessments to help you reflect on your own AI strategy.
