- The adoption of agentic artificial intelligence (AI) is accelerating, but companies should rethink their workflows and governance models to effectively integrate and orchestrate autonomous systems.
- Physical AI is already embedded in operations and its footprint is growing rapidly, but large-scale deployment will require more innovation and investment.
- Sovereign AI is increasingly on executive agendas and shaping technology decisions amid regulatory uncertainty across regions.
Businesses cautiously integrate agentic, physical and sovereign AI
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Across industries, organizations face the paradox of speed: the pressure to quickly adopt and scale artificial intelligence at the enterprise level to remain competitive, but also proceed with caution as technology advances faster than existing operating models can support.
And while AI is already improving productivity and efficiency, only a subset of organizations are using it to truly reinvent their business rather than optimize what already exists.
Faced with this reality, business innovation is gaining momentum in three areas: agentic, physical and sovereign AI. Each opens new opportunities and requires new governance approaches and new architectural choices.
To understand how these changes are driving business innovation, Deloitte’s latest report, State of AI in the Enterprise: The Untapped Edgebased on insights gathered from more than 3,200 business and IT leaders around the world, examines how these AI trends are helping organizations move from ambition to enablement.
Agentic AI: unlocking autonomy with the right safeguards
The agentic AI market is poised to reach $45 billion by 2030up from $8.5 billion in 2026, as organizations seek to integrate agentic systems capable of planning, reasoning, and executing multi-step tasks across all business functions.
Use cases are growing rapidly across industries, with Deloitte’s survey revealing that 74% of companies plan to deploy agentic AI within two years. Early wins include customer support, while industries such as finance, aviation and manufacturing deploy agents to streamline tasks and improve decision-making.
High potential covers supply chain coordination, research and development workflows, knowledge management and cybersecurity.
As adoption grows, companies need strong governance models for risk management, accountability and transparency, as well as enforcing ethical guardrails. Yet only 21% of executives surveyed currently have a mature governance model for autonomous agents, even though these systems can initiate actions, interface with customers, or interact with key business processes.
The most successful companies start with lower-risk applications and build cross-functional governance models to connect teams across the enterprise – from legal to IT to compliance.
Physical AI: Thriving in Controlled Domains with Wider and Stealthy Adoption
Unlike software agentic AI, physical AI brings autonomy to the real world through sensors, controls, and robotics, and is quickly becoming an integral part of operations around the world.
Well over half (58%) of respondents to our State of AI in the Enterprise According to a survey, their companies are already using physical AI to some extent and its adoption is expected to reach 80% within two years.
As manufacturing, logistics and defense lead the way globally, markets in the Asia-Pacific region are leading adoption, driving widespread integration of robotics, autonomous vehicles and drones, setting the tone for the next wave of industrial automation.
The practical realities of deploying physical AI – where organizations must manage equipment investments, security regulations and ongoing maintenance – illustrate why current deployments have focused on controlled environments such as factories and warehouses.
Robotics plays an important role in these environments, with common use cases including collaborative robots on assembly lines, inspection drones with automated response capabilities, robotic picking arms, and autonomous forklifts.
Robotics ranks second (20%) among the types of physical AI that can drive business innovation. Smart security and/or intelligent surveillance systems (21%) and digital twins (19%) are also expected to have a long-term impact on businesses.
Over time, physical AI will likely become a fundamental part of business transformation, integrated not only into operations but also into the strategy that shapes how businesses interact with the world around them.
Sovereign AI: Geography shapes corporate AI strategies
As organizations increase their investments in agentic and physical AI, many are discovering that sovereign AI, where the technology is built, matters as much as what it can do and becomes a key factor in business decisions.
Sovereign AI is about technological ownership and strategic independence. Governments are accelerating investments in digital infrastructure – from AI hardware and software to advanced satellite chips and systems – to help reduce reliance on foreign suppliers for important AI capabilities.
At the same time, some governments are investing in or providing incentives for sovereign AI, while others are imposing regulatory requirements on locally owned and operated AI infrastructure. Sovereign AI varies by geography and even sector.
For example, the pressure to source AI technology from foreign suppliers varies by region: only 11% of companies in the Americas rely on foreign-sourced solutions for the majority of their AI stack, compared to 32% of companies in Europe, the Middle East and Africa, according to our study. State of AI in the Enterprise investigation.
This increased attention is prompting companies to rethink where AI is developed, how data is stored and used, what chips are used and who controls the infrastructure. More than three-quarters (77%) of executives surveyed in the report said that where AI is developed is a key factor when choosing new technologies, while nearly three in five are currently building their AI stacks with local vendors.
With almost 100 billion dollars expected To be invested in sovereign AI computing by 2026, sovereign AI has become a strategic challenge for multinational organizations, which must face complex requirements that vary by country and create customized solutions for different markets.
As this change accelerates, businesses must consider how AI architecture aligns with the principles of sovereignty to innovate with confidence and operate effectively across borders.
What awaits us
Continuing developments in agentic, physical and sovereign AI are pushing the boundaries of what is possible, but successful deployment will depend on an organization’s ability to translate experiences and potential impact into tangible business benefits and sustainable competitive advantage.
To actively pursue the shift from AI ambition to advantage, organizations can:
- Redesigning workflows for more autonomy: Empower teams to collaborate with agentic AI, balancing innovation and orchestration with strong governance and ethical guardrails.
- Invest in resilient infrastructure: Anticipate the data, compute, talent, and supply chain demands (digital and physical) that can define tomorrow’s competitive advantage.
- Align strategies with local realities: Create AI solutions that respect sovereign borders, regulatory complexity and global dependencies.
- Activate your workforce: Transform access into adoption by providing universal AI tools, rethinking roles around AI, and fostering a culture of adaptive learning that empowers your people to thrive alongside intelligent systems.
The future belongs to those who orchestrate these capabilities with vision, care and discipline. Don’t wait for the AI landscape to stabilize; help shape it.
This article was originally published on World Economic Forum Agenda Blog.