Artificial Intelligence (AI) has long been the silent engine powering countless business operations behind the scenes—optimising supply chains, analysing vast data sets, and streamlining workflows. However, the dramatic rise of generative AI tools like ChatGPT, Claude AI, Gemini, and DeepSeek has propelled AI from the background into the spotlight. AI is no longer just assisting humans; it is advising, creating, coding, and even making decisions that shape customer experiences and redefine business strategies.

According to McKinsey, 40% of companies worldwide have already adopted AI in some form, while a staggering 82% are actively exploring its potential. India, in particular, is taking a leading role with 59% of organisations integrating AI into their operations—outpacing many global counterparts. The global AI market is projected to reach an astonishing $1.85 trillion by 2030, reflecting the accelerating momentum and high stakes for businesses embracing this technology.

We are witnessing not merely a technological upgrade but a fundamental transformation in how decisions are made, who (or what) makes them, and what leadership looks like in an AI-powered era. This raises a critical question: as AI becomes more capable, creative, and autonomous, who is really in charge?

In a recent People Matters Big Questions session, this question was explored with Pragati Chakraborty, Partner – AI Strategy & Insights at Deloitte, and Namrita Mahindro, Chief Digital Officer at Aditya Birla Chemicals. From discussions on OpenAI to DeepSeek, the evolution of AI and the current leaders in the AI landscape were unpacked, shedding light on the forces driving AI adoption and the strategic considerations organisations must confront.

What is driving AI adoption — and who’s leading the pack?

Today, 91% of companies globally use AI in some capacity. Looking ahead to 2025, research shows that 31% of users worldwide are incorporating generative AI into both their personal and professional lives. Pragati Chakraborty points out several reasons for this rapid adoption.

First, the consumer landscape has shifted dramatically. Digital natives expect AI-powered experiences as part of everyday life, from personalised recommendations to smart assistants. This consumer familiarity pressures businesses to integrate AI solutions in order to remain relevant and competitive.

Second, technological advancements have accelerated innovation. Organisations now have access to powerful computing resources, cloud infrastructure, and sophisticated AI models that allow for faster testing, iteration, and deployment. The "fail fast" mindset is increasingly embraced to quickly discover what works, delivering stronger returns on investment.

Third, the consumption layer — the end users — plays a pivotal role. When employees, customers, and partners become comfortable with AI-driven tools, organisations must respond with solutions that meet these evolving expectations. Today, AI is far more accessible, experimentation is less risky, and implementation costs have dropped significantly compared to just a few years ago.

What sets AI leaders apart? According to Chakraborty, three critical factors must align:

1. Business need: Leaders clearly identify where AI can add real value, solving specific challenges or unlocking opportunities.
   
   

2. Technology maturity: They ensure their organisation’s tech infrastructure and digital capabilities can support AI adoption and scale.
   
   

3. Investment in infrastructure: Beyond software, investing in the right hardware and cloud infrastructure is crucial to innovation and sustained growth.
   
   

Success lies at the intersection of these elements. In an increasingly interconnected and complex world, the organisations that harmonise business strategy, technology readiness, and infrastructure investment will gain a decisive edge.

The role of digital maturity and AI literacy

Namrita Mahindro emphasises that the gap between AI leaders and followers often stems from differing digital transformation journeys. Over a decade ago, many businesses began by focusing on digital fundamentals, particularly building robust data foundations. As data governance, security, and analytics matured, some organisations advanced faster, while others lagged behind.

Today, the real differentiator is AI literacy — not just among technology teams, but throughout the entire organisation. Companies that embed AI understanding at every level are better positioned to lead in this new era, Mahindro adds.

This means educating employees about AI capabilities and limitations, fostering a culture of curiosity and experimentation, and integrating AI into everyday workflows. Organisations with a strong AI culture can innovate faster, manage risks more effectively, and make more informed decisions.

Mahindro also believes AI has already transformed management functions — areas involving operational efficiency, data-driven decision-making, and routine problem-solving. AI excels at mimicking human actions and can outperform in specific tasks such as forecasting, risk analysis, or optimising workflows.

However, leadership remains uniquely human. True leadership requires vision, imagination, and ethical judgment, especially during crises. It involves building trust, navigating ambiguity, and making decisions grounded in evolving human values — qualities that AI cannot replicate.

In this sense, AI should be viewed as a collaborator rather than a replacement. Humans must retain final decision-making authority, particularly in areas affecting people’s lives and well-being. Empathy, ethical reasoning, and moral responsibility remain inherently human domains.

While AI can enhance many management functions, human oversight remains critical, especially in customer service and sensitive interactions. Systems need continuous human feedback to ensure they serve human interests and uphold organisational values.

The importance of trustworthy AI and ethical governance

Pragati Chakraborty describes AI as a fundamental shift — unlike previous technologies, “AI is the first technology we are trusting to think for us.” This trust introduces new risks and challenges.

Two critical concerns emerge:

• Is the AI providing accurate and reliable insights?
  
  

• Does the AI enhance or diminish the user’s role and experience?
  
  

To address these, organisations must prioritise building trustworthy AI guided by principles such as human oversight, accountability, transparency, fairness, and societal benefit.

Trustworthy AI requires embedding ethical considerations from the very beginning — from defining use cases to evaluating outcomes. Every AI application should align with the company’s core values and regulatory frameworks to maintain credibility and avoid harm.

Additionally, governance has become a cornerstone of AI initiatives. Pragati Chakraborty highlights how governance now involves multiple stakeholders beyond traditional change boards — including CISOs, cybersecurity experts, CEOs, and dedicated risk management teams.

AI testing protocols have also expanded beyond functionality to evaluate compliance, bias, feedback integration, and the effectiveness of human oversight — especially as autonomous AI agents become more widespread.

Governance today is a continuous process, with feedback loops ensuring AI systems remain ethical, effective, and aligned with organisational goals. This shift reflects the recognition that governance cannot be an afterthought; it must be embedded throughout the AI lifecycle.

Therefore, deploying AI governance at a large, global scale presents unique challenges. Namrita Mahindro points out that a one-size-fits-all governance model is unworkable given diverse markets, regulatory landscapes, and levels of AI maturity.

Instead, companies must adopt flexible governance frameworks tailored to specific regions, sectors, and organisational structures. This requires a nuanced approach that balances consistency with adaptability.

Additionally, involving business functions early in governance is crucial. In many companies, product development and strategy now begin within business teams rather than solely in IT. Raising AI governance awareness across all functions ensures responsible innovation from the outset.

Essentials of sustainable governance

Employee actions greatly influence governance success. Without secure internal AI platforms, staff may resort to external tools like ChatGPT or Gemini, risking data leakage and compliance breaches.

To mitigate this, companies must not only implement policies but also provide secure, integrated AI tools that fit naturally within employee workflows. Educating employees on governance requirements and ethical AI use further strengthens compliance.

Lastly, the organisations that will thrive are those that embrace AI strategically, invest in digital and AI literacy, and implement robust, flexible governance frameworks. By doing so, they can harness AI’s potential responsibly — ensuring it serves people, aligns with corporate values, and supports long-term success.

As Pragati Chakraborty reminds us, AI is not just a tool; it is a trusted partner in decision-making. Balancing this partnership with human leadership is the key challenge and opportunity of our time.