Some thoughts on the deployment of AI by senior leadership teams in 2026, from Quartz Labs;
After two years of experimentation, pilots and hype, businesses are entering 2026 with a more sober view of AI. The technology itself is no longer the constraint. The real challenge now lies in how organisations adapt their structures, decision-making models and ways of working to make AI genuinely useful.
Drawing on work with product, innovation and insight teams across sectors, the founders of Quartz Labs, Jonathan Kahan and Danielle Jaffit, outline three shifts they expect to define the next phase of AI adoption.
These predictions point to a move away from isolated tools and short-term efficiency gains, towards AI as a shared, strategic capability embedded across the enterprise.
Jonathan believes the next phase of AI adoption will be defined less by technical capability and more by whether organisations are willing to change how they operate:
“With 95% of AI pilots failing, the C-suite is entering 2026 with growing AI fatigue. But the issue is not the technology. It is organisational. Outdated habits, slow approvals and legacy decision-making models are blocking what AI now makes possible.
“So far, most AI use has defaulted to a chat interface. But is chat the right medium for complex decisions, collaboration or creative work? Should AI behave as a tool, a co-worker, an assistant that moves across applications or something embedded directly into every workflow? And once you answer that, a second question emerges: how should teams work with AI together?
“Do organisations let every employee use AI as they see fit? Do they augment existing workflows? Or do they redesign the operating model entirely?
“Next year will not be about buying more AI, but about building a business that can actually use it.”
SIMULATION NOT AUTOMATION?
Meanwhile, Danielle predicts that simulation, rather than automation, will become the most practical way for leaders to use AI in high-stakes decision-making:
“Digital twins will become one of the most valuable executive tools in 2026.
“Improvements in AI modelling mean teams can now simulate how customers might respond to new ideas, features or creative work, using the insight they already have. This turns research from a static archive into a working system inside the marketing and innovation workflow, allowing teams to test, learn and iterate before costly decisions are made.
“For a C-suite facing rising pressure on speed, spend and certainty, simulation will become a key strategic capability over the next twelve months.”
Jonathan concludes by saying he expects AI to shift from a personal productivity tool to a form of shared organisational intelligence that shapes how decisions are made:
“In 2026, AI stops acting as a collection of isolated assistants and begins operating as a shared intelligence across the enterprise. Most employees will use AI to extend their thinking, but the real breakthrough comes when these individual interactions feed a collective decision layer that benefits the whole organisation.
“As AI supports research, models behaviour, generates ideas or challenges assumptions, businesses will need systems that retain the evidence, logic and constraints behind those interactions. Without this shared context, knowledge becomes fragmented, and thousands of personal AI helpers pull the company in different directions.
“This is why AI will increasingly function as core infrastructure. It will hold customer understanding, organisational memory and decision standards in one place, reducing rework, uncovering risks earlier and speeding up alignment across teams.”
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