The Age of Intelligent Autonomy: How Agentic AI Is Transforming Enterprise Strategy

Enterprises are entering a new phase of digital transformation, and the era of automation is giving way to autonomy. The next decade will mark the most profound evolution of enterprise AI yet, as organisations move from process optimisation to systems that think, decide, and act independently. 

According to our analysis, the global Agentic AI market is projected to grow from US$7.3 billion in 2025 to nearly US$265.3 billion by 2035, representing a 25-fold increase. This trajectory signals how rapidly enterprises are operationalising autonomous intelligence as a foundation for competitive advantage. 

The momentum is not driven solely by efficiency; it reflects a larger-scale transformation. Agentic systems are redefining how enterprises operate, make decisions, and deliver outcomes across every function, from finance and manufacturing to healthcare and logistics. AI is no longer a peripheral tool; it is becoming an active collaborator, shaping strategy, efficiency, and innovation. 

Why the Momentum Is Accelerating 

Three converging dynamics are accelerating the enterprise shift from automation to autonomy: 

• Technological maturity lowers the adoption barrier  Breakthroughs in large language models (LLMs) and orchestration frameworks have enabled the development of intelligent agents without requiring deep technical expertise. Low-code and no-code development environments now allow enterprises to design self-governing workflows within existing IT ecosystems. 
  

• Seamless integration across enterprise architecture 

  Modern Agentic platforms integrate directly with ERP, CRM, and data lake systems. This interoperability enables autonomous operations without requiring the dismantling of legacy infrastructure, a key driver of scalable adoption across complex global enterprises. 
  

• Governance-first design enabling responsible autonomy 

  The newest Agentic systems embed human oversight, audit trails, and sandboxed environments. This governance-first approach ensures accountability, critical for adoption in highly regulated sectors such as finance, healthcare, and energy.  Collectively, these forces mark an inflection point: AI is transitioning from a back-office enabler to the core operational backbone of the enterprise. 
  

Industry-Specific Insights 

Agentic AI is reshaping value creation across industries, from intelligent risk management to predictive maintenance and autonomous supply chains. 

Financial Services: JPMorgan Chase 

JPMorgan Chase has been at the forefront of deploying agentic AI across its operational landscape. Its internal AI tool for threat modelling (AITMC) has achieved 20% efficiency gains and uncovered an average of nine additional unseen threats per model. In software engineering, AI-powered assistants have improved developer productivity by 10–20%. 

Strategically, the bank is transitioning from process execution to autonomous orchestration, utilising agents to manage risk, detect anomalies, and optimise workflows in real-time. This enables human expertise to focus on strategy and oversight, while AI handles precision execution at scale. 

Manufacturing and Industrial Automation: Siemens AG 

Siemens’ “Industrial Copilot” exemplifies how agentic AI redefines industrial efficiency. Integrated with its Senseye Predictive Maintenance platform, the system has achieved a 25% reduction in reactive maintenance time and a potential reduction of up to 30% in unplanned downtime. 

Engineers now utilise generative AI to generate PLC (programmable logic controller) code, enabling less experienced technicians to work at expert levels. Siemens is effectively transforming maintenance from a cost centre into a predictive, value-generating function. 

Retail and Supply Chain: Walmart Inc. 

Walmart has embedded autonomous decision agents into its global supply chain. Its AI-driven demand-sensing and inventory orchestration systems have achieved a 15–25% reduction in stockouts and a 25–40% improvement in order cycle times across key distribution hubs. 

By integrating real-time sensor data with agentic decision-making, Walmart has turned its logistics network into a self-optimising, real-time system, one that dynamically balances inventory, routes, and replenishment decisions. 

Healthcare  Agentic AI is emerging as a force multiplier in healthcare delivery and operations. Hospitals piloting agentic scheduling and diagnostics assistants report 30% lower administrative workloads and 25% faster clinical decision cycles. 

The impact extends beyond efficiency: these systems enable proactive patient flow management and resource allocation, improving both operational capacity and patient outcomes. 

Emerging Platforms Powering the Shift 

The Agentic AI revolution is being enabled by rapid advancement across complementary technology layers: 

• OpenAI o1, Google Gemini, and Anthropic Claude power early agentic pilots in finance, healthcare, and manufacturing with advanced reasoning and orchestration. 
  

• Accenture and Google Gemini Enterprise are jointly deploying more than 450 agentic agents across retail, logistics, and public services to enhance decision-making and process autonomy. 
  

• Salesforce Einstein 1 Agents are embedded within enterprise CRM workflows to deliver context-aware task automation and customer support orchestration. 
  

• Microsoft Copilot Studio, adopted by nearly 70% of Fortune 500 firms, enables enterprises to build and deploy custom AI agents for workflow automation and cross-department orchestration. 
  

• Microsoft, ServiceNow, and UiPath are integrating agentic layers into core enterprise systems, enabling automation at scale without disrupting existing infrastructure. 
  

• The blockchain backbone, projected to grow from US$7.3 billion in 2025 to US$265.3 billion by 2035, ensures secure collaboration, verifiable decisions, and auditability across multi-agent environments. 
  

• NVIDIA Omniverse, LangChain, and MetaGen enable simulation and governance of agent behaviour before live deployment, ensuring safety, control, and scalability. 
  

Together, these innovations are establishing the technical foundation for large-scale enterprise autonomy. 

Quantifying the Enterprise Opportunity 

The enterprise AI market is on a steep upward trajectory. Our analysis projects that the Agentic AI market will expand from US$7.3 billion in 2025 to US$265.3 billion by 2035, passing US$30 billion by 2029 and US$90 billion by 2032. 

This growth represents more than a technology trend; it reflects a systemic shift in enterprise value creation. As AI agents evolve from task-based automation to cross-functional orchestration, they will reshape organisational design, enabling adaptive, self-optimising operations that scale with intelligence. 

In essence, enterprises are transitioning from deploying AI as discrete tools to building autonomous networks of decision-making systems, a transformation that compounds value across every layer of the business. 

Future Vision: From Automation to Autonomy 

By the early 2030s, enterprise ecosystems will be characterised by intelligent agents capable of negotiation, collaboration, and dynamic optimisation. Key shifts on the horizon include: 

• Agent-to-Agent Commerce: Smart contracts enabling seamless, automated transactions across industries and supply chains. 
  

• Dynamic Governance: Policy-driven AI ensuring compliance, ethics, and transparency in autonomous decision-making. 
  

• Human–AI Collaboration Models: Humans as strategic supervisors and innovators, with agents handling precision execution and routine cognition. 
  

• Cross-Enterprise Interoperability: Blockchain-secured ecosystems enabling agents to collaborate safely across enterprises and borders. 
  

Enterprises that invest early in adaptive intelligence and governance frameworks will lead in defining the new operating model for autonomy. 

Conclusion: Building the Agentic Advantage 

Agentic AI represents the most significant inflection point in enterprise technology since the rise of cloud computing. Its potential lies not in replacing human intelligence but in extending it, creating organisations that think, decide, and act at digital speed. 

The next decade will reward those who move early: enterprises that align their data, governance, and AI strategies to unlock autonomy will not only gain efficiency but also shape the frontier of digital leadership. 

The age of intelligent autonomy has begun. The question is no longer when to adopt, but how to lead.