The following responses from Art Hu and Sonu Nayyar have been edited for clarity.
Why Is Agentic AI A Timely Consideration For Today’s Enterprise IT Strategies?
Hu: Enterprise IT is being asked to deliver greater impact with fewer resources, faster timelines and tighter alignment to business strategy — all while navigating increasingly complex systems. Agentic AI refers to systems designed to act autonomously within defined parameters, observing their environment, making decisions and taking action to achieve specific outcomes, all under enterprise oversight. At Lenovo, we see this as a shift from managing workflows to managing intent. These systems help IT teams move from reactive support to proactive impact, enabling greater scale and responsiveness across the enterprise while freeing people to focus on higher value work.
Nayyar: Agentic AI represents a significant evolution, positioning IT as a central orchestrator of enterprise intelligence. Our role now includes architecting secure, scalable and compliant platforms that enable teams across the company to rapidly build, deploy and manage intelligent agents securely and responsibly. This shift places IT at the heart of a future shaped by intelligent, autonomous enterprise systems. As enterprises face growing complexity and pressure to move faster, agentic AI offers a timely catalyst for agility and scale.
How Is Agentic AI Shifting IT Toward A More Strategic, Goal-Driven Model?
Hu: It’s a meaningful change. Instead of scripting every process, you define the outcome, and the system determines how best to achieve it. That allows IT to contribute directly to strategic goals rather than getting stuck in tactical execution. At Lenovo, we’re using this model to improve how we manage infrastructure and user experience — with systems that optimize performance based on business context, not just static rules.
Nayyar: Agentic AI is shifting the primary focus of enterprise IT away from managing individual tasks and toward orchestrating intelligent, goal-driven outcomes. Unlike traditional automation, which executes fixed workflows, agentic AI enables intelligent systems to reason over intent, evaluate multiple paths and dynamically adapt to achieve strategic outcomes. For instance, rather than simply restarting a failed service, an IT agent can investigate the root cause by correlating logs, recent deployments and telemetry data — and then decide whether to roll back a change, alert a team or initiate a fix, all while adhering to service-level agreements. Similarly, an agent tasked to reduce cloud cost by 15 percent can explore options like reallocating workloads, right-sizing instances or pausing idle resources, choosing the most effective route in real time. These agents operate within enterprise-defined policies, providing autonomy while preserving governance. With this ability to independently pursue objectives, agentic AI is transforming IT from a reactive support function into a strategic driver of business value.
What Types Of Tasks Are Now Within Reach For Intelligent Agents?
Nayyar: We’re seeing agentic systems contribute meaningfully in areas far beyond routine tasks. Their capabilities now extend into deep research, strategic planning and contextual reasoning — positioning them as true brainstorming partners and problem-solving assistants. By augmenting human creativity and accelerating complex decision-making, these agents are helping teams innovate faster and more effectively.
Hu: That’s been our experience as well. For example, in our Premier Support contact centers, we’ve introduced generative AI tools that assist agents during customer interactions, translating across languages, summarizing case histories and recommending next steps. These tools are designed to support — not replace — our teams, allowing them to deliver faster, more effective service. And for enterprises looking to build similar capabilities, we’ve made a growing set of AI assets available through the Lenovo AI Library — a curated collection of models and use-cases that help teams accelerate responsible AI deployment.
How Does Agentic AI Help Enterprises Respond To Real-Time Business Challenges Like Cyberthreats Or Operational Disruptions?
Hu: Agentic AI helps us act faster and with more precision. When disruptions occur, these systems can assess what’s happening, trigger remediation workflows and escalate them when necessary — all while keeping human teams informed. It’s not about removing control, but about reducing delay. This proactive posture helps minimize impact and protect business continuity.
Nayyar: Agentic AI doesn’t just react — it enables enterprises to proactively detect, assess and respond to real-time disruptions with agility. Whether it’s identifying unusual network behavior that may indicate a cyberthreat, rerouting resources during a supply chain disruption, or helping discover and evaluate contingency plans during supply chain disruptions, agentic systems can continuously monitor signals, reason over multiple data streams and recommend actions — all within the boundaries of enterprise policies. In critical domains like cybersecurity and operational resilience, final decisions are always informed by human-defined policies and priorities. This collaborative approach augments human capabilities with critical insights, driving faster, more informed decisions — all with essential oversight that ensures resilience and adaptability.
How Can Agentic AI Serve As A Competitive Differentiator For Enterprises Looking To Innovate And Lead — And How Important Is Ethical, Responsible AI In This Evolution?
Nayyar: Agentic AI empowers enterprises to accelerate innovation, deliver more personalized experiences and optimize operational efficiency. However, this transformative power necessitates a parallel commitment to ethical and responsible AI. At NVIDIA, we prioritize explainable, auditable and enterprise-governed solutions that build trust with our customers, regulators and our workforce. This commitment is reflected in how we design, test and deploy our agentic systems across the enterprise.
Hu: Trust is key to sustainable AI adoption. At Lenovo, we’ve built responsible AI practices into our systems — from design to deployment. Our Product Diversity Office plays a role in evaluating inclusivity and accessibility, which is vital as these systems begin to touch more parts of the business. And we’re also focused on talent, helping our teams build the skills to manage and lead with AI, not just use it. As these tools evolve, so do the roles around them. Our goal is to ensure that people stay at the center of innovation, supported — not replaced — by technology.