The next frontier
For over two decades, organizations have pursued a common ambition to become “data-driven,” focusing on improving access to data, scaling analytics, and building modern platforms. With that ambition now largely within reach, data and AI leaders are facing the next frontier: how to progress from insight access to translating intelligence into consistent, high-quality decisions.
The Rise of Decision Intelligence examines how leading organizations are responding to this shift in practice.
Key findings
- 47% of data and AI initiatives are now decision-bearing, with 26% embedded directly into workflows
- Access to AI is no longer a differentiator—most organizations are using similar tools and platforms
- The highest-impact initiatives start with decisions, not data or models
- Value is created through systems, not individual models
- Workflow integration determines impact—if workflows don’t change, intelligence remains underused
- Data and AI leadership is shifting from capability delivery to outcome ownership
From insight generation to decision intelligence
Analysis of real-life data and AI initiatives from the DataIQ 100 North America, including Mars Petcare, Thermo Fisher Scientific, Amazon, Walmart, and Under Armour, shows a clear departure from traditional analytics models to intelligence that is increasingly shaping how organizations run, rather than something that sits alongside it.
“The era of the dashboard CDO is over. Over the next 12–24 months, the job shifts from arranging insights to orchestrating action. The most successful data and AI leaders will stop being passive stewards and become chief decision and value officers.”
— Sushma Punuru, Global Chief Data Officer, Global Payments
The operating structure behind the shift
This transition is not driven by a single capability or technology. The report identifies four interconnected layers through which organizations are deploying decision intelligence:
- Foundational – making data and AI usable, reliable, and scalable
- Insight access – expanding access to information and reducing friction
- Decision support – guiding decisions through shared logic and models
- Embedded intelligence – executing decisions within workflows
These are not maturity stages. They operate together, each contributing to moving intelligence closer to the point of execution.
“Data and AI leadership will shift from enablement and experimentation to scaled execution and direct value creation. GenAI, automation, and intelligent agents will drive that shift, but what matters most is integrating them into real business workflows, not just running pilots. Leaders will be expected to move fast with accountability for outcomes.”
– Manish Agarwal, Vice President, Data & Analytics, Skechers
Where advantage now lies
The findings highlight that competitive advantage is no longer determined by access to technology, with most organizations working with similar platforms and tools. Instead, the differentiator lies in how intelligence is operationalized through decision-focused design, reusable components, and workflow integration.
“Embedding data and AI into daily decision-making requires sustained cultural change, not just technical progress. Success will no longer be measured by what is built, but by the new business models, opportunities, and sources of competitive advantage that data and AI enable.”
– Meaghan Ferrigno, Senior Vice President, CFO & CDAO, Destination Canada – Number 9 in the DataIQ Top 10.
A shift in leadership, not just capability
As a result, the role of the data and AI leader is expanding. The report identifies a shift in accountability from delivering insights to owning decision outcomes, and from building platforms to designing and operating decision systems at scale.
This moves the role closer to the core of how the organization performs. As expectations shift toward execution and measurable impact, leaders are increasingly responsible for how decisions are made, how consistently they are applied, and how they translate into business outcomes.
The implication is not simply broader scope, but greater strategic importance. The role is becoming more aligned to enterprise performance, evolving into that of an enterprise operator and leader of organizational change, responsible not just for capability, but for outcomes.
“Data and AI leaders will become change agents, driving a culture of data-driven decision-making and widespread AI adoption. In essence, the role is evolving from ‘builder’ to ‘strategic conductor’”
– Rajiv Kolagani, CDAIO, Ann & Robert H. Lurie Children’s Hospital
The Rise of Decision Intelligence: How Data and AI Leaders Are Rewiring the Enterprise draws on case studies from the 2026 DataIQ 100 North America, examining how leading organizations are embedding intelligence into decisions and operational workflows.
Download the full report to explore the emerging operating structure of decision intelligence, key success factors to scaling, and the expanding mandate of data and AI leaders as they deliver the next phase of enterprise transformation.
A huge congratulations to those recognised in the 2026 DataIQ 100 North America. Their contributions provide a grounded view of how leading organizations are embedding data and AI into decisions and how the role of the data and AI leader is evolving as a result.
