At a recent roundtable dinner hosted by Empathy Lab and Adobe, a select group of senior marketing, technology and operations leaders shared candid views on one of the world’s most transformational forces: artificial intelligence.
Spanning sectors from travel and consumer goods to financial services and media, the discussion quickly moved beyond experimentation and into the realities of adoption. Specifically, which operational, cultural and ethical shifts we need to make AI work at scale. The consensus: most organizations are already using AI in some form, but few are realizing its full potential.
“This feels like a pivotal moment,” says Matthew Bradbeer, Senior Director at Empathy Lab. “We are at an inflection point moving from the theoretical to the practical application of AI. The conversation has shifted from fascination with the technology to real questions and answers about how it reshapes work, value and creativity.”
Releasing human potential, not replacing it
One theme that really stood out was the role of AI in taking on the mundane to free humans for higher-value, more inspiring work. Leaders shared how they increasingly hand repetitive production, translation and operational tasks to agents and automated workflows.
A senior travel brand leader observed that automating low-value activity has already begun to change the shape of their teams’ work, allowing them to focus on creativity and innovation rather than execution at scale. Others noted that agentic workflows are dramatically accelerating internal processes that once relied on slow, manual outsourcing models.
Yet, beneath the optimism sat a deeper organizational tension. Several leaders voiced concern that AI initiatives are still being viewed too narrowly through a workforce-optimization lens, particularly by finance functions.
“There’s a real education gap to close. AI works best when it’s designed to augment human skill, not replace it. That’s where the biggest long-term value is created.”
Nishant Pithia, Enterprise AI Architect at Adobe
Human-in-the-loop models emerged as a shared principle. These models are not just for quality control, but to ensure that AI adoption enhances, rather than diminishes, human creativity and judgement.
From tools to orchestrated workflows
If 2024 and 2025 were defined by AI pilots and copilots, the room agreed that the next phase will be shaped by orchestration. Organizations are now moving beyond disconnected tools towards structured, agent-driven workflows that redesign how work flows through the enterprise.
Examples ranged from automated translation agents trained by in-house subject matter experts to daisy-chained workflows capable of triggering multiple actions across content, experience and operations.
Alex van Gestel, VP, Consumer & Services at Empathy Lab
“We’re no longer talking about AI being deployed for isolated tasks. We’re talking about re-architecting how AI is deployed end-to-end across the entire content ecosystem.
That’s a fundamentally different level of maturity, one that allows for content workflows to connect directly into LLM's and further serve the insatiable demand for fresh creative.”
Several leaders noted that this shift places new demands on internal expertise. SMEs now play a critical role in training agents, embedding domain knowledge into systems that can then scale output far beyond human capacity alone.
Guardrails, trust and ethical design
Governance emerged as the essential foundation for progress of regulated industries, from financial services to public broadcasting. Without robust brand, data and authentication controls, innovation simply cannot advance.
“We can’t move at speed unless our risk teams truly trust the systems,” one financial services leader shared. Ethical deployment, secure access and explainability were consistently framed not as blockers, but as enablers of sustainable growth. Human oversight will be essential in maintaining trust as AI assumes a greater role in decision-making and customer engagement.
Synthetic users, personalization and the limits of simulation
Debate intensified around the growing use of synthetic users for research, testing and personalization. Some leaders see enormous potential in using synthetic audiences to pressure-test ideas, content and experiences before engaging real customers at scale.
Others were more cautious, highlighting the nuances of real consumer behavior and the risk of over-reliance on generic simulation. “Synthetic testing gives us speed, but real customers still give us truth.”
Empathy Lab challenged the scepticism with examples where early synthetic insight closely aligned with later real-world market research, suggesting a powerful complementary role for both.
The invisible barrier: skills and confidence
Perhaps the most human insight of the evening came not from technology, but from mindset. Several organizations admitted to feeling “behind” in their AI maturity, only for peers to point out that they were often further along than they realised. “The biggest constraint we’re seeing now isn’t the technology,” said one brand leader. “It’s confidence, skills and belief across teams. Education is what unlocks momentum.” As AI accelerates the pace and volume of work, people must be supported to adapt to entirely new ways of operating.
Looking ahead to 2026
As the dinner closed, attention turned to what comes next. The group agreed that AI is rapidly becoming the marketing operating system that connects content, experience, insight and activation into continuous, adaptive ecosystems.
“The winners in 2026 won’t be those with the most tools or the fanciest presentations.It will be the ones who’ve designed the best orchestration between humans and machines, with the highest AI to human augmentation value.”
Matthew Bradbeer, Senior Director at Empathy Lab
“Ultimately, the advantage in 2026 won’t come from deploying more AI, but from deploying it better. The organizations that win will be those that orchestrate humans and machines with intent. Brands need to use AI to amplify creativity, sharpen decision-making, and adapt in real time. When trust, intelligence and imagination are built into the same system, AI becomes not just a capability, but a competitive edge.”
Nishant Pithia, Enterprise AI Architect at Adobe
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