AI Revolution Needs Strong Leaders: Microsoft India COO Himani Agrawal Calls for Top-Down Adoption

New Delhi, September 1, 2025 – Artificial Intelligence (AI) is no longer a buzzword. It is the foundation of how businesses will compete in the future. But according to Himani Agrawal, Chief Operating Officer of Microsoft India and South Asia, the real change will only come when leaders take the first step. Speaking at the Microsoft Work Trend Index (WTI) 2025 event in Noida, she highlighted that AI adoption at the enterprise level should be driven from the top by business leaders, not left to employees alone.

Her statement comes at a time when India is positioning itself as an “AI-first” economy, with enterprises increasingly redesigning operations around human-AI collaboration.

Leaders vs Employees: A Shift in AI Mindset

The Microsoft Work Trend Index 2025 shows a surprising shift. Last year, employees were the early adopters of AI tools. They experimented with chatbots, copilots, and generative systems before companies officially adopted them.

But this year, leadership is in the driver’s seat. In India, over 80% of business leaders say they are familiar with AI agents, while only 66% of employees share that confidence. Globally, too, the trend is similar. 79% of leaders believe AI will help their careers, compared to 67% of employees.

This means that AI adoption is moving from the grassroots level to the boardroom. As Agrawal explained, “When AI projects are led by senior executives, they are seen as serious initiatives. That ensures investment, business returns, and long-term adoption.”

India’s AI-First Push: Frontier Firms Leading Change

India’s corporate sector is already witnessing a surge of what Microsoft calls Frontier Firms. These are organizations that are redesigning their workforce to include hybrid teams of humans and AI agents.

• 59% of Indian leaders are already using agentic AI to automate workflows.
• 93% of business leaders plan to scale AI adoption within the next 12–18 months.

These companies are not waiting for gradual change. They are embedding AI into the core of their business strategy—whether in operations, customer service, or supply chain management.

Himani Agrawal explained that this top-down adoption is the only way to achieve results at scale. When leaders push for AI at the enterprise level, it changes processes, roles, and performance standards.

New AI Roles Emerging Inside Enterprises

One of the most interesting findings from Microsoft’s study is the emergence of new AI-specific job roles in Indian companies.

• Agent Bosses – who oversee AI systems and ensure they align with business goals.
• AI Workflow Designers – professionals who create smart workflows where humans and AI collaborate.
• AI System Operators – who manage and monitor the technical functioning of AI agents.

Nearly 92% of leaders in India said they are considering hiring for such AI-related roles. This signals the start of a completely new job ecosystem inside corporate India.

Upskilling and Training: Building AI Confidence

AI adoption is not just about machines. It is about people learning how to use them. Leaders are now focused on upskilling their teams so that AI adoption is smooth.

• 51% of leaders listed training as their top priority for the next year.
• 63% of managers expect AI learning to become part of every employee’s core responsibilities in the next five years.

This training is not only technical. It includes AI ethics, data privacy, and collaboration skills. Enterprises are realizing that for AI to work effectively, employees must trust it and understand its limitations.

The Experimentation Era: Fail Fast, Scale Fast

Even as adoption grows, companies face a challenge—how to move from pilot projects to scaled solutions. A recent MIT study showed that 95% of US firms failed to get returns from their large AI investments because they could not scale.

But Indian leaders are learning quickly. Manpreet Singh Ahuja of PwC India compared AI adoption to venture capital. “You plant many seeds. Some fail. A few succeed. But those that succeed bring massive returns.”

Similarly, Rajesh Kumar R, CIO at LTIMindtree, explained that his company gives employees a safe space to experiment. “We allow failures in the early stage. Once an idea proves valuable, we scale it across the enterprise.”

This fail fast, scale fast method is becoming the standard for AI-driven organizations.

Breaking the Data Barrier

One of the biggest hurdles to enterprise AI adoption is data quality. AI agents need structured, accurate, and reliable data to give meaningful results.

Agrawal and other leaders agree that without strong datasets, AI will remain a fancy experiment. Once companies organize their customer, supply chain, and operations data, AI can start showing real value—whether in customer engagement, personalized services, or predictive analytics.

Costs Falling, ROI Rising

A common worry is the cost of AI adoption. New technologies are always expensive in the early years. Agrawal acknowledged this concern but explained that costs are already dropping.

For example, token pricing for Azure OpenAI and ChatGPT has declined as usage grows. These reductions are part of a larger trend where scale brings affordability. The more companies adopt AI, the more providers optimize their costs, making it easier for late adopters to join.

This is why Agrawal insists that leaders must invest early. By the time AI adoption becomes mainstream, they will already have scaled operations, trained teams, and optimized costs.

Real-World Case: L&T Slashes Planning Time

To show the practical impact of AI, Agrawal shared a success story. Engineering giant Larsen & Toubro (L&T) used AI to cut supply chain planning time drastically.

• Earlier, planning took two weeks.
• With AI systems, it now takes ten minutes.

This is not just about efficiency. It allows companies to predict disruptions and respond quickly. In volatile times, this is a game-changer for industries like construction, logistics, and manufacturing.

AI Adoption: Not Just Tech, But Culture

Agrawal’s biggest point is that AI adoption is not just a technical shift but a cultural one. Employees must trust AI. Leaders must create an environment where experimentation is welcomed. Companies must be ready to redesign jobs, retrain workers, and rethink operations.

Microsoft’s study makes it clear: companies that treat AI adoption as a strategic leadership decision will succeed. Those that treat it as an experiment at the employee level may fall behind.