The transition to the autonomous enterprise
AI’s trajectory has accelerated dramatically. As companies integrate AI into the core of their operations, they’re becoming autonomous enterprises, using AI that decides, acts, and learns alongside people to make strategic decisions in real time.
Most companies are just starting this journey, but our study finds that those out in front have lessons that everyone can learn from. Read on for a summary of our findings.
Decoding AI maturity
In Autonomy by design: Scaling AI for enterprise value, more than 500 senior executives from enterprises with revenues of between $1 billion to >$50 billion across industries and functions, share their experiences and expectations from AI.
They reveal four levels of AI maturity and four enabling themes that are critical to the creation of an autonomous enterprise.
Benchmarking AI maturity identifies four clear levels
The AI of now
New technology doesn’t eliminate the need to overcome old challenges. Companies must still breakdown familiar barriers before they can build on AI’s full potential.
Value deficit: AI plays a significant role in decision-making, but judgment-driven decisions are still people-led. Until companies fundamentally reimagine how they operate in an AI-enabled world, true financial impact will remain out of reach.
Organizational inertia: When companies don’t close capability gaps, realign structures, or manage change thoughtfully, the results they get from AI suffers.
Technological complexity: With greater AI adoption comes greater technological complexity. Both leaders and non-leaders face challenges integrating the technology into existing workflows.
The rise of the autonomous enterprise
Our research reveals the four enabling themes that bring the autonomous enterprise to life.
1. A symphony of agents
Companies need a conductor to coordinate their AI agents and prevent them from working at cross-purposes. But only 3% of respondents’ organizations are actively implementing agentic orchestration.
Only with AI integrated across workflows, systems, and decision loops will it succeed, because there’s no artificial intelligence without process intelligence.
2. The universal AI practitioner
Empowering and training every employee to become AI practitioners is central to scaling AI. As roles and ways of working evolve, leaders are helping their people understand how humans and AI will collaborate.
3. Enterprise architecture redux
Most companies struggle with the complexity of their technologies. To scale autonomous AI, they need a strong data-centric foundation, but this architectural backbone has yet to fully emerge for many.
Findings from a poll at Microsoft Ignite
4. Governing at the speed of AI
Governance sets the pace – and limits – of AI innovation. But almost all respondents indicate that they don’t have adequate governance models and structures in place for autonomous or agentic AI systems.
The leaders’ playbook
No matter where you are on your AI journey, use the leaders' playbook for practical actions your organization can follow across the four enabling themes.
Access the full report for more insights, case studies, and the next steps that will accelerate your transition to an autonomous enterprise.
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