The agentic AI dilemma
It may come as no surprise that business executives see AI as defining the next era of business. Garter 2025 CEO study shows that 77% of CEOs believe AI will have the most significant impact on their industries over next three years. Yet they also indicate that their business and operating models are not fit for AI.
This poses a particularly sticky wicket when it comes to deploying blazing fast AI innovations like AI agents. When we asked 180 enterprise leaders in a recent study with NewtonX about how confident they were in their company's ability to strategically deploy agentic AI solutions over the next 2–3 years, only one in three said they felt fully confident.
This confidence gap isn't surprising. The tension between sky-high expectations and implementation uncertainty creates a perfect storm of hesitation. Most of these leaders (84%) report mounting pressure to deploy AI in the enterprise from their C-suite, boards, and competitors. It's the classic "hurry up, but don't mess up" dilemma that keeps executives awake at night.
AI confidence: It's more than a feeling
When it comes to implementing AI in an organization, "confidence" isn't just a feeling – it's a concrete assessment grounded in three critical pillars: strategic vision, trust and credibility, and performance and results.
This goes for AI in general, but even more so for the next generation of generative AI: intelligent agents. It is great that agents are turning LLMs from passive tools into active intelligence, but to feel confident investing in agentic AI, enterprise execs specifically need clear strategic alignment, security and compliance assurances, and transparent, predictable outcomes.
AI can't be a black box. Leaders need visibility into how decisions are made and confidence that similar inputs will produce consistent results.
Cutting through the agentic hype
To achieve business transforming value of AI agents, enterprises must navigate a fragmented market landscape to get the right balance between the power and promise of agents and the risk of inconsistency. There is a critical choice to make here: chase the hype or chart a pragmatic path forward.
A science project approach to AI agents that introduce unnecessary risk will lead to grappling with inconsistent outcomes, regulatory challenges, and frustrated users. Instead, keep agents from running amok by combining the creative power of AI with the predictability of structured workflows and processes – and gain a decisive competitive advantage.
Pega stands apart as the North Star guiding enterprises across this predictability divide – offering the only solution that harnesses the full creative potential of AI while ensuring the governance and reliability that enterprises demand. And it’s an approach that is available today.
Here’s a snapshot look at Pega’s fundamentally different approach to agentic AI that lets enterprises go beyond just having AI systems called "agents" to creating systems where:
- Agentic creativity is injected into design-time ideation: Harnessing AI's creative power during workflow design ensures innovation without sacrificing reliability. Core to this approach is Pega Blueprint™, the industry’s first agentic workflow and decisioning designer.
- Agent conversations meet prescriptive workflows: Once workflows and strategies are designed and validated, Pega Predictable AI™ leverages the semantic capabilities of AI agents at runtime to understand user requests and identify the appropriate workflow to serve them – grounding agent interactions in trusted workflows and business rules.
- An entire agent ecosystem is orchestrated: Extending beyond individual agent interactions and applications, Pega Agentic Process Fabric™ builds a directory of agents and workflows across all applications in the enterprise, both Pega and non-Pega. This allows conversational agents to find and execute any workflow, no matter where it is deployed – preventing AI agents from creating islands of automation.
- Workflow is dynamically created with human oversight: When an existing process doesn't address a specific request, Pega Blueprint design agents can be called on at runtime to dynamically create a new workflow – bridging the gap between established processes and emerging needs, all without sacrificing governance. These workflows require user approval before execution, ensuring human oversight of AI-generated processes.
Early, confident adopters will win
In the AI era, the advantage goes not to those who wait for certainty, but to those who build confidence through strategic implementation. The future belongs to the confident and hands-on – not because they have all the answers, but because they have built the frameworks, skills, and partnerships to navigate the AI landscape with purpose and clarity.
Experience the difference
The era of agentic workflows arrives June 1 at PegaWorld – where you won't just imagine the possibilities, you’ll experience them.
Discover how Pega builds agentic AI into every workflow to accelerate your autonomous enterprise transformation journey. Explore our recent research study on the next great leap leaders have not quite made yet to learn more.
And test drive Pega Agent Experience™ for your workflows to see firsthand how Pega Blueprint™ turns your trusted processes into intelligent agent workflows that deliver end-to-end results.
This post was written in partnership with Intern Iris, Pega’s highly collaborative generative AI assistant.