Adobe's CMO Lara Balazs is advising marketing leaders that the traditional playbook has become obsolete as AI systems replace search engines for product discovery. To adapt, brands must track visibility in AI-generated responses—Adobe's own tool showed a 200% increase in brand visibility for products like Acrobat and Firefly—and CMOs must expand into orchestration roles coordinating with engineering, finance, and IT rather than managing marketing functions alone.
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Lara Balazs, Adobe's chief marketing officer, is advising peers that traditional marketing playbooks no longer apply as product discovery shifts from search engines to AI-driven interfaces. Adobe developed LLM Optimizer, a tool to track brand visibility in AI-generated responses, and saw a 200% increase in brand visibility for products such as Acrobat and Firefly after deployment.
Why it matters
As consumers increasingly begin searches in ChatGPT rather than Google, brands risk exclusion from consideration before customers reach their websites if they don't appear in AI recommendations. CMOs must now collaborate closely with finance, engineering, and IT leadership, and metrics like search engine traffic and traditional search optimization are losing relevance. Marketing organizations that succeed will be those with people eager to learn, comfortable with ambiguity, and energized by change.
What to watch
Marketing teams are restructuring into mission-focused multidisciplinary groups (marketers, engineers, product managers, data specialists) rather than traditional departments. CMOs are being redefined as chief marketing orchestrators who coordinate people, technology, data, and AI—requiring technical literacy and financial fluency alongside brand building.
The shift from search-engine-driven to AI-driven product discovery represents a fundamental break from two decades of marketing strategy anchored in search engine optimization. As the article notes, Adobe itself experienced declines in traffic tied to traditional search, prompting the company to understand how much of that change was linked to large language models. This real-world decline has forced CMOs from aspiration into action: the old instruction "spend less with more impact" has given way to the vague but urgent mandate "there's AI, do that."
Balazs's framing of the CMO as a chief marketing orchestrator reflects how this transition pulls marketing far beyond its traditional scope. Marketing insights now shape decisions about technology infrastructure, data architecture, and product development—work that once belonged to engineering and IT. This expansion means CMOs must now speak fluently with CFOs, CIOs, and CTOs; those who do not risk marginalization from enterprise-level decisions. The early phase of AI adoption—experimentation and testing—is giving way to deliberate embedding of AI into day-to-day workflows, with sustained investment tied to clear business objectives and executive sponsorship.
The challenge Balazs identifies is not technical mastery but the ability to ask the right questions without engineering training, translate technical capabilities into business outcomes, and lead organizations through sustained ambiguity. The teams best positioned to succeed are those structured around business missions rather than functional silos, bringing together diverse skills to move faster as AI capabilities advance.
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