admin Artificial intelligence is no longer just a support function. In 2025, it’s the central engine driving decision-making, productivity, and long-term strategy in large enterprises. From banks and cloud infrastructure providers to AI-native startups, leaders across industries are taking bold steps to integrate AI into the core of their operations. These trailblazers are not chasing hype—they’re building scalable, secure, and intelligent systems that are changing how business works.
Jane Fraser: Bringing Agentic AI into Banking at Scale
At Citigroup, CEO Jane Fraser is leading one of the boldest AI transformations in global finance. The bank has launched an ambitious rollout of agentic AI tools—systems that don’t just assist but act on behalf of users. Working closely with Google Cloud and leveraging Vertex AI, Citi is embedding generative and decision-making AI across departments. From trade confirmations to fraud detection and internal customer support, these tools are being scaled to support Citi’s entire workforce. Fraser’s approach isn’t about experimenting with AI—it’s about embedding it deeply in the bank’s daily operations to reduce delays, cut manual effort, and improve accuracy across global markets.
Arvind Krishna: Making Specialised AI Work for Real Business
IBM’s CEO Arvind Krishna is doubling down on specialised AI models. Unlike general-purpose large language models that require vast data and compute, IBM’s models are lightweight and tailored for specific use cases. These include financial document analysis, IT automation, and supply chain insights. Krishna’s strategy is built on the belief that enterprises need focused, reliable, and secure tools rather than massive, generalised ones. This approach has also helped IBM deliver faster results for clients while managing energy costs and data governance. It reflects a shift from AI hype to AI usability—where smaller, smarter models drive measurable outcomes.
Michael Dell: Building the Infrastructure Behind AI Ambitions
AI performance depends not just on algorithms but also on infrastructure. Michael Dell has positioned Dell Technologies as a key supplier of enterprise-grade AI hardware. In partnership with Nvidia, Dell is providing high-performance servers that support large-scale AI deployments across industries. These systems are being used by cloud-native firms, telecom operators, and even governments for national-scale AI initiatives. In 2025, Dell’s AI server business is on track to grow by over 50 percent. By focusing on compute and scalability, Dell is helping enterprises deploy AI not just quickly—but at a scale and speed that meets real-time demands.
Teresa Heitsenrether: Leading Enterprise LLM Deployment at JPMorgan
At JPMorgan Chase, Vice Chair Teresa Heitsenrether is overseeing the rollout of large language models (LLMs) across core banking operations. The models are being used to improve internal workflows, automate document review, and support client reporting. Unlike surface-level AI integrations, these tools are woven into day-to-day systems. Heitsenrether is also driving a strong focus on compliance and risk controls, ensuring that LLMs follow internal guidelines and regulatory frameworks. JPMorgan’s early results show faster turnaround on tasks and improved consistency, highlighting how enterprise LLMs can support—not replace—human expertise in financial decision-making.
Rama Akkiraju: Applying AI to Keep IT Systems Running Smoothly
Rama Akkiraju, Vice President of AI/ML for IT at Nvidia, is helping reshape how enterprises manage their infrastructure. Her work focuses on AIOps—applying machine learning to monitor, detect, and respond to problems in IT environments. Using real-time data, Nvidia’s AI tools can detect anomalies, predict outages, and even trigger self-healing actions. This allows IT teams to avoid downtime and reduce firefighting. Akkiraju’s approach reflects a broader shift in enterprise AI—from customer-facing tools to behind-the-scenes intelligence that keeps critical systems running without disruption.
Mira Murati: Launching Next-Gen Generalist AI
After leaving her role as CTO at OpenAI, Mira Murati founded Thinking Machines Lab, a startup focused on building generalist AI systems with spatial awareness. These models are designed to learn from fewer examples and adapt across multiple environments—similar to how humans learn and respond to change. Her work is especially relevant in fields like robotics, industrial automation, and augmented reality. Backed by billions in venture capital, Murati’s new company aims to push AI beyond software and into the real world, where systems interact with people and spaces in meaningful ways.
Daniela Rus: Connecting AI with the Physical World
Daniela Rus, director of MIT’s Computer Science and Artificial Intelligence Lab (CSAIL), is pioneering work at the intersection of AI and robotics. Her team is developing systems that combine machine learning with real-world sensors to support human collaboration. Applications include wearable devices for accessibility, flexible robots for factories, and autonomous navigation systems. Rus’s vision is practical and human-centered—designing AI that works with people rather than around them. In industrial settings, this approach is making automation more adaptable, safer, and easier to deploy at scale.
The Common Thread: AI Designed for Impact, Not Just Innovation
What connects these leaders is not just their use of AI, but their focus on making it usable, measurable, and grounded in the realities of business. Jane Fraser is embedding AI into the core of a global bank’s daily functions. Arvind Krishna is tailoring AI for specific use cases, not headlines. Michael Dell is ensuring that enterprises have the computing muscle to run modern models. Mira Murati and Daniela Rus are shaping the future by bridging AI with physical systems and human behavior.
Across industries, the message is clear: the future of enterprise intelligence depends on strong leadership, thoughtful application, and the right mix of scale, specialisation, and responsibility. These trailblazers are not simply following the AI trend—they are defining how AI becomes a foundational part of how business gets done in 2025 and beyond.
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