The Autonomy Gap: Why Only 12% of Firms Are Winning the AI Race

NEW YORK, NY – January 13, 2026 – While artificial intelligence continues to dominate boardroom discussions, a new report reveals a stark gap between ambition and reality, with only 12% of large organizations making significant strides toward becoming a true “autonomous enterprise.” The rest remain stuck in the experimental phase, struggling to scale AI beyond isolated projects.

New research released today by technology solutions firm Genpact shows that while confidence in AI is high, the foundational work required to embed it into the core of a business is lagging. The report, “Autonomy by design: Scaling AI for enterprise value,” surveyed over 500 senior executives at global companies with over $1 billion in revenue. It defines an autonomous enterprise as one where agentic AI—systems that can decide, act, and learn alongside people—is woven into the fabric of operational workflows, driving decisions in real time.

Despite the futuristic vision, the data paints a picture of widespread hesitation. A quarter of executives surveyed believe self-managing business processes with minimal human oversight could be a reality within three years. Yet, only a scant 3% are actively implementing the agentic orchestration platforms necessary to make that vision a reality.

“Our findings confirm that transformation goes well beyond technology,” said Sanjeev Vohra, Chief Technology and Innovation Officer at Genpact, in the report's release. “The leading enterprises are reimagining processes, making deliberate investments, and unlearning old ways of working, all while ensuring responsible use of data and AI.”

The Human Paradox of Automation

The chasm between the leaders and the laggards is not defined by a lack of technological tools, but by organizational and human barriers. The most frequently cited organizational constraint to AI adoption is a workforce capability gap. However, the report found that fewer than half of companies (45%) offer AI training for all employees, creating a bottleneck of talent and understanding.

This challenge is compounded by a critical deficit in oversight. Nearly all executives surveyed admitted they lack adequate governance models and structures for the very autonomous or agentic AI systems they hope to deploy. This creates a high-risk environment where companies are building powerful engines without designing the necessary guardrails or steering mechanisms.

Nelson Repenning, a professor at the MIT Sloan School of Management, highlighted this core challenge. “AI poses an interesting paradox,” he noted in the report. “On the one hand, its main benefit will come from automating the work that humans currently do. On the other hand, you can’t automate the process of implementing automation. Humans must still make the tough, messy decisions about where and how to apply AI.”

This human element—making strategic choices, designing new processes, and building a culture of trust and collaboration with AI—is where most organizations falter, preventing them from moving beyond small-scale pilots to achieve enterprise-wide transformation.

Decoding the Leaders' Playbook

So what sets the leading 12% apart? According to the research, these front-runners are not just implementing technology; they are architecting their entire organization for autonomy. The report identifies four interconnected enablers that serve as a practical blueprint for success.

First is creating a symphony of agents, which involves orchestrating multiple AI systems to work in concert across end-to-end business processes. This moves beyond deploying a single algorithm for a single task and instead focuses on creating an intelligent, interconnected web where AI can manage complex workflows, from supply chain logistics to financial closing. The underlying principle is that there can be “no artificial intelligence without process intelligence.”

Second, leaders are cultivating the universal AI practitioner. Instead of siloing AI knowledge within a small team of data scientists, they are focused on democratizing AI fluency across all roles and functions. This involves comprehensive training and creating a culture where every employee is empowered to collaborate with AI, identify opportunities for its use, and understand its implications.

Third is what the report calls enterprise architecture redux. This means undertaking the difficult but necessary work of building a modern, data-centric foundation. Leaders recognize that agentic AI cannot run on legacy systems and siloed data. They are investing in robust, scalable data architectures that ensure AI models have access to the high-quality, real-time information they need to learn and make effective decisions.

Finally, the top performers are focused on governing at the speed of AI. They are establishing agile oversight mechanisms and responsible AI frameworks that can evolve with the technology. This allows them to scale AI quickly while managing risks, ensuring ethical use, and building trust among employees, customers, and regulators.

Building the Connective Tissue of Modern Business

The journey toward an autonomous enterprise is a strategic imperative that promises significant competitive advantages, including enhanced efficiency, greater agility, and new avenues for innovation. Companies that successfully embed AI into their core operations can react to market shifts faster, anticipate customer needs more accurately, and free up their human workforce to focus on high-value, creative, and strategic tasks.

Genpact refers to this integrated approach as “Agentic Operations,” positioning AI as the essential connective tissue for modern business. “We are witnessing firsthand the transformative role of AI,” Vohra continued. “Our last mile advantage and depth of process and data knowledge enable our clients to achieve higher levels of autonomy, which drive tangible business outcomes, today.”

The findings place the company in a fiercely competitive market of global consulting and IT services firms, including giants like Accenture, TCS, and Capgemini, all racing to provide the strategic guidance and technical firepower businesses need to navigate their AI transformations. The key differentiator often lies not in the AI models themselves, but in the ability to integrate them into complex, decades-old business processes and manage the profound organizational change that follows.

The path forward is fraught with challenges that extend beyond the four enablers, including the immense complexity of integrating AI with legacy IT infrastructure and the persistent ethical dilemmas surrounding AI bias, transparency, and accountability. However, the research makes it clear that waiting for a perfect solution is not a viable strategy. The 12% of leaders are demonstrating that progress depends on a deliberate, holistic, and human-centric approach to building the autonomous enterprise, one process and one empowered employee at a time.