Agentic AI Is Gaining Enterprise Cred—But Scaling It Is Still a Slog
Automation Anywhere, long a heavyweight in Robotic Process Automation (RPA), has released new research showing that AI agents are no longer just hype—they’re on the brink of enterprise mainstream. But the path forward isn’t exactly frictionless.
Developed in collaboration with Forrester Consulting, the study surveyed global decision-makers managing enterprise AI strategies. The verdict: AI agents are hot, but hurdles like data privacy, talent shortages, and system integration still block widespread adoption.
In other words, the future might be autonomous—but it still needs better wiring.
Purpose-Built Platforms vs. General AI Tools
Here’s the standout stat: 60% of leaders favor RPA-native automation platforms like Automation Anywhere over more general-purpose AI systems from OpenAI or Anthropic. Even broader enterprise platforms like Salesforce and Microsoft lag behind in the AI-agent race.
Why? Enterprises need automation platforms designed from the ground up to handle complex, long-running business processes—not just chat-based interactions or narrow use cases. That’s a vote of confidence for companies that built their reputation automating workflows long before LLMs made AI sexy.
Mihir Shukla, CEO of Automation Anywhere, sees this as a major inflection point. “The industry is shifting toward AI-augmented workflows,” he noted, emphasizing that Agentic Process Automation (APA) is the foundation for building scalable, secure, and effective AI agents.
The Promise (and Pain Points) of AI Agents
There’s strong belief in what AI agents could deliver:
- 74% of enterprise leaders believe agents can surface hidden insights from massive data sets.
- 71% think automation should enhance—not replace—human work.
But enthusiasm doesn’t equal execution. Data privacy (66%), skills gaps (63%), and integration complexity (61%) are the main barriers holding back full deployment.
Automation Anywhere argues its APA framework is built to tackle exactly these issues—with governance, human oversight, and enterprise-grade security baked in.
Real Use Cases, Not Just Pilots
According to the report, many organizations have already started piloting AI agents for internal support (53%) and customer service (48%). But over the next two years, they’re planning to expand those efforts into compliance, sales automation, and even enterprise-wide process management.
The kicker? Across all use cases, decision-makers rate the potential value of AI agents at over 8 out of 10—a clear signal that companies see transformative payoff if they can overcome implementation friction.
Automation Anywhere’s new Agentic Solutions suite is designed to move companies past endless pilots. With pre-built, enterprise-grade agents for common functions—think customer support, finance, and compliance—the company hopes to lower the adoption barrier and start delivering business impact now, not five quarters from now.
Enterprise-Grade or Bust
There’s a clear trend in platform preference: 60% of respondents say they need intelligent automation platforms built for long-running, enterprise workflows. That means tightly integrated, highly secure systems that don’t just run single tasks, but orchestrate end-to-end processes at scale.
With its APA system, Automation Anywhere is positioning itself as the go-to vendor for those needs. Unlike generalist AI providers, its solutions emphasize:
- Cross-platform integration
- Secure data governance
- Multi-layered automation workflows
- Human oversight in every loop
In a crowded field of AI startups and toolkits, that mature infrastructure gives it a unique edge.
The Road to Scalable Agentic AI
The takeaway? Enterprise adoption of AI agents is no longer an “if”—it’s a “when” and a “how fast.” Leaders see the potential. They’re running pilots. And with platforms like Automation Anywhere offering lower-friction, ready-to-go solutions, the race to scaled deployment is officially on.
Of course, not every company will make it through the maze of security concerns, talent constraints, and legacy system challenges. But those that move decisively now—backed by automation-native platforms—stand to lead in the era of the autonomous enterprise.
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