78% of executives have seen high-performing agentic AI projects come from non-leaders, frontline staff, or support functions. While AI iniatives can often be top-down, "The New Face of AI Leadership," has found that these employees are building a growing bottom-up momentum to solve pain points themselves with agentic AI.
According to this report, engine of AI transformation today is increasingly the workforce, not just the IT or leadership departments.
Employees are no longer just consumers of AI. They’re the creators, initiators, and drivers powering the enterprise’s most transformative agentic AI breakthroughs. The center of gravity is shifting toward workforce-powered reinvention.
The following 15 proprietary enterprise AI adoption stats — are drawn from Moveworks study, "The New Face of AI Leadership."
This report of over 200 U.S. IT executives at billion-dollar companies — reveal the surprising ways AI is being shaped from the ground up, how you can manage and support these efforts, and what this means for your strategy in 2026 and beyond.
Stats on the decentralization of AI influence and bottom-up adoption
These data points show why your role as an AI leader is evolving, and why the most successful AI initiatives often come from the edges of the organization rather than the center.
1. Bottom-up drive
91% of executives say non-technical employees now play a larger role in driving agentic AI projects than in previous technology waves.
2. Declining central authority
Only 38% view IT as the department that will hold the most influence over AI agents in the next three years: an indicator that AI authority could be decentralizing.
3. Mandate for open innovation
78% of IT executives support allowing successful AI projects to emerge from anywhere in the company, not just from leadership or IT.
4. Frontline impact
Another 78% have already seen high-performing agentic AI projects originate from non-leaders, frontline staff, or support functions — teams closest to the workflow pain points AI is meant to fix.
Stats on ROI and the transformative payoff of adoption
These insights speak directly to enterprise leaders who are shaping their AI strategy, indicating how the impact of AI can be measurable, material, and strategically transformative.
5. Operational transformation
Nearly 80% of executives say agentic AI has already produced a significant or total transformation of their operations.
6. Utility over model hype
An overwhelming 96% would rather deploy a useful agentic AI tool than chase the latest or fastest LLM.
7. ROI accountability
Almost 57% of executives report tracking ROI primarily through increased output—the most widely used metric for proving AI’s value.
8. Transformation-based ROI metrics (process reinvention)
53% of executives say process reinvention is a top indicator of AI-driven transformation.
9. Transformation-based ROI metrics (new capabilities unlocked)
47% cite new capabilities unlocked as a key indicator of transformative ROI.
These metrics suggest that agentic AI transcends incremental efficiency gains. Its core value lies in reshaping the fundamental flow and structure of work.
Consequently, AI should be assessed not solely by reductions in operational cost, but by its capacity to multiply human and organizational capability as well.
Stats on readiness, talent, and sustaining AI adoption
Technology provides the potential for AI success, yet it's often the people, culture, and structure determine the realized value and long-term sustainability.
10. Career mobility across the workforce
Nearly 40% of executives believe agentic AI will create upward mobility for all employees, not just technical specialists.
11. New roles already emerging
Almost 70% of IT leaders have created new roles to help manage, govern, or operationalize agentic AI across the enterprise.
12. Underestimating the cultural shift
A strong 73% say their organization underestimates the cultural and structural impact of adopting agentic AI.
13. C-suite blind spot
29% report that the C-suite underestimates these cultural changes by a great deal, exposing a leadership readiness gap.
14. Change management matters (workflow integration)
65% say employees adopt AI faster when tools integrate into existing workflows rather than replace them.
15. Adoption reality
AI adoption succeeds when you design for human behavior, not idealized future-state workflows.
Download the full report: The New Face of AI Leadership
How you can use these stats to strengthen your AI strategy
These data points offer more than just a snapshot; they provide a crucial perspective on scaling AI.
They suggest that the primary bottleneck isn't technical tooling or model size. It's often an organizational challenge concerning literacy, culture, and operational enablement.
The enterprises poised for long-term success may not be those deploying the absolute most advanced models today. Rather, they will likely be the ones that effectively help their people understand, trust, and confidently integrate AI into their daily workflows.
1. Cultivate bottom-up innovation
Frontline teams possess the deepest context for the actual work being done. Build on a foundation of solid AI governance, and then provide employees with secure testing environments (sandboxes), clear governance boundaries (guardrails), and intuitive interfaces, so that they are best positioned to securely surface high-impact, agentic AI use cases.
However, genuine empowerment is contingent on comprehension. Building foundational AI literacy able with guardrails for safe experimentation is essential for employees to see clearly how these new capabilities fit into, and enhance, their existing roles.
2. Evolve the AI leadership mandate
The role of the AI leader is shifting from the sole "owner" of the technology to an enabler and platform steward. This involves setting consistent standards, clearly communicating risk and limitations, and actively modeling responsible use.
When leaders openly use AI for tasks like summarizing meetings, analyzing data, and more complex use cases, it signals that AI is an integrated tool, not a black box. This visible transparency and clear explaination is a powerful catalyst for trust and organization-wide adoption.
3. Strategically invest in new organizational capabilities
Successfully scaling AI requires augmenting teams with new, human-centered skill sets: agentic AI tools, workflow designers, operational owners focused on adoption, and dedicated governance stewards.
These roles are vital for ensuring teams can grasp the how and why of AI—specifically, how decisions are reached by a system, and how crucial issues like data privacy and fairness are practically protected—making the path to adoption both smoother and inherently safer.
4. Facilitate the cultural and operational transition
Employees adopt new technologies most readily when they are integrated into familiar, established workflows. Find ways to make the learning process practical and relevant: demystify the data that powers the tools they already use, explain the AI functionality embedded within them, and actively invite critical questions.
Simple, consistent channels for feedback—such as monthly adoption pulses, standing "Ask About AI" office hours, or quick internal explainers—help governance feel like a living, collaborative process rather than an abstract constraint.
5. Shift focus to impact and capability unlocked
Move beyond tracking mere incremental process optimization. Instead, measure output transformation, process reinvention, and the new organizational capabilities that AI enables.
Scaling AI is less about making a small part of the engine run faster, and more about transforming how work flows across the entire enterprise value chain.
constraint.
The bottom up shift
Together, these five insights offer a more nuanced roadmap for scaling AI responsibly, quickly, and in a way that generates durable, enterprise-wide impact.
Today, this bottom-up movement is reshaping company culture, creating new career paths, and redefining what innovation looks like across the enterprise.
By using these insights as a guiding principle, your can guide your organization's AI to delivers operating leverage that compounds into enduring advantage — and signals a new era of AI that gets work done– for all departments, employees, and workflows.
Download the full report: The New Face of AI Leadership
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