AI is here, alignment is not
AI adoption is accelerating, and coordination is the next opportunity
AI is now a standard part of operations. Nearly all organizations surveyed (97%) report using at least one form of AI today, and leaders overwhelmingly view AI as a positive force for productivity, customer experience, and operational efficiency.
AI has moved beyond experimentation and into daily use across business functions, suppporting content generation, forecasting, customer interactions, and workflow automation. At the same time, the way AI is deployed today reflects the pace of adoption. AI is often implemented within individual tools or teams, delivering targeted benefits where it is applied. The opportunity ahead is connecting those capabilities so AI can support work end-to-end.
Antonio Nucci PhD, Chief AI Officer, RingCentral
Where organizations stand on AI
0%
use at least one form of AI
0%
hold a positive view of AI
0%
have an AI strategy in place
Speed, practicality, and immediate value are top priorities during AI adoption
The most commonly deployed AI capabilities today are those that integrate easily into existing workflows and deliver fast, tangible benefits. Generative AI (77%), predictive analytics (54%), and process automation (53%) are widely used across industries.
AI agents (digital workers) are also gaining traction (45% report using them today), reflecting growing interest in systems that can move beyond single tasks to support coordinated work across steps and functions.
Speed, practicality, and immediate value are top priorities during AI adoption
0%
use generative AI
0%
use predictive analytics
0%
use process automation
0%
use AI agents (digital workers)
These patterns indicate that early AI initiatives tend to be fast-moving and highly targeted.
Early momentum is real, and returns come quickly
Across industries, organizations are moving quickly from experimentation to execution. Most leaders report that their first AI initiatives were rolled out within a year, and a similar share saw measurable returns in that same timeframe. Satisfaction levels are high, reinforcing confidence that AI is contributing real value.
Targeted, tool-level deployments often drive these early wins, making it easier to demonstrate value before broader coordination challenges emerge.
Where organizations stand on AI
0%
rolled out their first AI initiative within one year
0%
saw ROI within the first year
0%
are satisfied with their AI initiatives overall
Scaling AI introduces new coordination needs
The operational payoff of AI remains tactical. More than half of organizations (52%) have implemented AI initiatives to improve productivity, and 90% say it's best used to automate specific workflows.
These benefits often appear early, even before systems fully mature: organizations using or testing digital workers report increased productivity (61%) and faster workflows (58%). However, as AI expands beyond isolated use cases, execution challenges emerge, with 40% of organizations reporting they have paused or cancelled at least one AI initiative.
These adjustments are not signs of diminished confidence in AI. Instead, they reflect a natural recalibration as teams move beyond early, isolated successes and confront the practical realities of scaling across systems, data, and teams. In many cases, organizations pause because early wins reveal the need for stronger integration, governance, and coordination to sustain value at scale.
Of respondents who have paused or cancelled an AI project or initiative, one or more of the following reasons were cited
Integration complexity
Internal resistance or misalignment
Unclear or inconsistent ROI
Poor user experience for employees
Businesses are no longer questioning whether to adopt AI. They’re focused instead on how to connect, govern, and scale its capabilities across the organization.
The data shows that organizational readiness, not technology, is the primary challenge to scaling AI. Integration complexity, inconsistent ROI measurement, and internal alignment slow progress. AI can deliver value quickly, but sustaining that value at scale requires stronger coordination and clearer connective frameworks.
Jon Arnold Principal Analyst, J Arnold & Associates