Discover why agentic AI matters now and what CIOs and CTOs should be doing to prepare for its adoption.
Agentic AI is no longer science fiction. It’s here today, reshaping everything we know about artificial intelligence. Not just smarter chatbots or faster algorithms, but autonomous systems that can think, plan, and act with minimal or no human prompting. In 2025, we’ve entered a new phase in AI development, where machines don’t just wait for commands; they figure it out themselves.
The new world of agentic AI does bring a few questions. What exactly is agentic AI? How is it different from the AIs we’ve had before? And, finally, why should every CIO be thinking about agentic AI in 2025 and beyond?
The Rise of Agentic AI: More Than a Buzzword
Traditional AI focuses on performing pre-defined tasks based on pre-programmed rules and algorithms. On the other hand, generative AI responds to prompts, inputs, or commands to create new content based on learned patterns. Both forms of AI are smart, but they don’t take initiative. And herein lies what sets agentic AI apart.
Agentic AI systems can perceive their environment, set their own goals, make plans, and act on those plans autonomously.
- They don’t just answer your questions, but also ask their own.
- They not only suggest what should happen, but also take the steps to make it happen.
- They don’t just solve problems, but also decide which problems to solve.
In short, AI agents are goal-oriented planning systems. They break big goals into sub-goals, evaluate multiple paths, and select the best one, just like humans reason. These systems don’t just think for themselves, but also act with purpose. And this represents a massive shift in how we interact with machines, moving from AI as a tool to AI as a digital collaborator.
Over the past decade, enterprises have adopted rule-based automation, AI-powered assistants, and decision-support tools. Agentic AI is the logical next step to stitch together these capabilities into self-driving processes. And 2025 is the inflection point.
Three factors converge this year to make agentic AI enterprise-ready:
- Mature Tooling: Many technology vendors now offer frameworks and platforms (e.g., orchestration layers atop large language models or LLMs) that simplify agent development.
- Data Infrastructure: Modern data fabrics and real-time pipelines provide AI agents with the contextual intelligence they need.
- Proven Use Cases: Early pilots in IT operations, customer service, and finance have moved from pilots to production, demonstrating tangible ROI.
Simply, agentic AI now has the potential to unlock enterprise productivity at scale, which is why it should be on every CIO’s strategic radar.
Business Impact and Use Cases Worth Watching
Let’s explore some promising agentic AI use cases.
Autonomous Process Orchestration
Leveraging AI agents in IT operations and support can accelerate execution by enabling parallel processing and reducing task delays. Instead of relying on traditional workflows with sequential handoffs, AI agents can coordinate and execute multiple steps simultaneously. For example, AI agents managing cloud infrastructure can simultaneously monitor system health, provision resources, and perform disaster recovery procedures.
Internal Workflow Automation
Internal workflow automation through AI agents delivers measurable productivity gains across procurement, HR, and cybersecurity functions.
For instance, in procurement, an AI agent can select suppliers, invite them, analyze bids, check response quality, compare to historical data, and make award recommendations autonomously.
In HR, AI agents can screen resumes to find and schedule interviews with ideal candidates, and even automate payroll.
And in cybersecurity, agentic AI can automate threat prevention, detection, triage, and response. 32% of organizations now use security AI, according to IBM’s 2025 data breach report. These forward-thinkers reduce the time to identify and contain a breach by 80 days compared to their counterparts.
Embedded Intelligence in Enterprise Software Ecosystems
Embedding AI agents directly into enterprise software platforms is another strategic use case. For example, SAP Joule and Microsoft 365 Copilot integration can redefine productivity by unifying workflows across both platforms. It eliminates inefficiencies caused by constant application switching, allowing users to access and act on SAP data directly within Microsoft 365 tools like Teams, Outlook, and Planner. This results in a more seamless, intuitive work experience that empowers employees to make smarter, data-driven decisions based on real-time enterprise data.
Preparing the Organization for Adoption
Here’s how to get started with agentic AI:
1. Lay the Data and Integration Foundation
Agentic AI needs real-time access to clean, well-structured data across systems. To support this, organizations must break down data silos, standardize formats, and invest in integration through APIs or middleware. A robust data and system foundation ensures agents can operate with the context needed to act independently and effectively.
2. Establish Governance and Trust Frameworks
Autonomous agents require clear guardrails. Organizations must define what agents can do, ensure auditability of their actions, and provide human oversight where needed.
3. Manage Change Strategically
Lastly, CIOs must prepare employees to work alongside AI agents from the start. Communicating the impacts of the change and offering training in AI literacy and human-in-the-loop skills are requisite.
Next Steps for CIOs and CTOs
Agentic AI is not just a new tool. It’s a new paradigm that changes how we work, learn, create, and even how we think. And you can start leveraging it today in three steps:
- Evaluate Your Organization’s AI Readiness: What’s the current status of your IT infrastructure? Do you have real-time data integration and clean APIs? How proficient is your team with agentic AI?
- Pilot Strategically: Choose a well-defined, low-risk, high-value use case for your first phased deployment. Measure results, iterate, then expand to other areas as you see results.
- Partner to Accelerate Adoption and ROI: Engage a reliable AI solutions provider to help implement agentic AI in a strategic, secure, scalable, and cost-effective way.
NRI can deliver the technical expertise your organization needs to implement agentic AI successfully, as well as evolve capabilities once it’s integrated into business functions. Our proven frameworks, access to cutting-edge infrastructure, and partnerships with leading agentic AI players like Microsoft allow us to provide custom end-to-end solutions.
The future of AI is here. Will you embrace it?
Contact NRI to get started.
