Agentic AI, one of Gartner’s top technology trends for 2025, represents a shift from task-based automation to autonomous goal-driven systems. Unlike task-based AI, agentic AI dynamically adjusts to changing conditions and autonomously makes decisions to complete complex processes. This innovation promises to redefine productivity across industries, enabling CIOs to build virtual workforces that complement human teams.

Gartner predicts that by 2028, agentic AI will make 15% of daily work decisions, introducing opportunities as well as governance challenges for IT leaders.

What Is Agentic AI?

Agentic AI represents a major leap in automation. Unlike traditional AI, agentic systems understand and pursue objectives autonomously. These agents can reason, plan, and make real-time adjustments to achieve desired outcomes. For example, in a customer service setting, an agentic AI system might independently manage inquiries, follow up with clients, and escalate cases without human intervention.

The technology can operate across a variety of enterprise functions, from financial services to IT operations. It acts as a virtual co-worker, handling multiple tasks simultaneously while learning from past interactions to improve over time.

This ability to adapt makes agentic AI especially valuable for organizations seeking to reduce operational complexity and scale efficiently.

Transforming the Enterprise

Companies in attendance at the Gartner event like MyWave.ai are leading in the innovation curve and has integrated agentic AI across ERP platforms like SAP and Salesforce to automate business processes end-to-end. Their Wave Process Model allows companies to design workflows using a no-code platform, enabling non-technical users to deploy AI-driven processes quickly.

This use case streamlines operations by embedding AI agents directly into ERP systems, managing tasks such as purchase order processing, service call creation, and data updates. This integration eliminates repetitive work, improves accuracy, and ensures compliance with industry regulations through built-in audit trails.

For example, in regulated sectors like banking and aviation, MyWave.ai’s agents enforce compliance by dynamically adapting workflows to meet changing regulations. This level of adaptability provides businesses with a significant advantage, as it reduces the time spent on manual interventions and ensures consistent performance.

One of the key benefits reported is up to a 75% reduction in deployment time for new processes and 85% lower manual effort, demonstrating how agentic AI accelerates digital transformation while maintaining operational control.

Governance and Challenges

While the benefits of agentic AI are significant, CIOs must address governance challenges to ensure these systems operate ethically and effectively. Autonomous AI systems introduce risks, such as unanticipated decisions or compliance violations, especially in regulated industries.

Gartner emphasizes the importance of AI governance platforms to monitor and control agent behavior, predicting that companies with robust governance will experience 40% fewer ethical incidents by 2028.

Key governance considerations include:

• Transparency: Ensuring stakeholders understand how AI agents make decisions.
• Compliance: Embedding regulatory guardrails within AI workflows to prevent violations.
• Accountability: Establishing clear frameworks for monitoring outcomes and assigning responsibility for AI-driven decisions.

MyWave.ai addresses these challenges by incorporating compliance controls directly into its agentic AI models. Their systems provide real-time audit trails, ensuring that every action taken by an AI agent can be tracked and verified. This transparency builds trust and reduces the likelihood of operational errors.

How CIOs Can Prepare for Agentic AI

CIOs should begin by identifying low-risk processes that can benefit from automation. Functions like financial reporting, customer service, and IT support offer ideal pilot opportunities.

CIOs should also consider scalability from the outset. No-code solutions allows businesses to deploy modular AI processes quickly, making it easier to scale agentic AI across multiple departments. This adaptability ensures organizations can respond to new challenges and market opportunities efficiently.

“The rise of Agentic AI co-workers is unlocking unprecedented levels of productivity. The magic happens, when you can not only enable massive gains in efficiency but also address key challenges like AI governance and compliance.”

Geraldine McBride, CEO – MyWave.ai

Additionally, cross-functional collaboration will be critical. Business units must align their objectives with the capabilities of agentic AI systems, ensuring smooth integration into existing workflows. Training employees to work alongside AI co-workers is another essential step, as it shifts their roles from task execution to strategy and supervision.

The Wrap

Agentic AI is transforming the way businesses operate by enabling autonomous decision-making and streamlining complex processes. Early-adopters are demonstrating the real-world potential of this technology, achieving significant gains in productivity, accuracy, and customer satisfaction. From financial services to IT operations, agentic AI offers a scalable solution for modern enterprises seeking to enhance efficiency while reducing costs.

However, the successful deployment of agentic AI requires robust governance frameworks to mitigate risks and ensure compliance. CIOs must take proactive steps to integrate these systems thoughtfully, align them with business objectives, and foster a culture of collaboration between humans and AI agents.

As Gartner’s forecast suggests, the enterprises that adopt agentic AI today will be better positioned to navigate future disruptions and drive sustainable growth. With the right strategy and governance in place, agentic AI offers an exciting opportunity to truly redefine the future of work.