AI That Acts, Not Just Analyzes
AI has already reshaped heavy asset industries, but its biggest shift is happening right now: AI that doesn’t just support decisions - it takes action.
For years, AI has been used in the industry to enhance efficiency, automate workflows, and improve safety. But until now, it has largely remained a decision-support tool providing insights but leaving the final action to human operators. That paradigm is shifting.
Agentic AI represents a major evolution in artificial intelligence. According to Gartner’s Top Strategic Technology Trends for 2025, agentic AI will move beyond analysis and actively plan and execute tasks with minimal human intervention.
Gartner predicts that by 2028, 33% of enterprise software applications will include agentic AI, a massive leap from today’s <1% adoption.
This shift is particularly transformative for asset-heavy industries like oil & gas, where real-time decision-making and operational efficiency are critical. At Kongsberg Digital, we are leading this evolution ensuring that AI not only provides insights but also takes intelligent, autonomous action, all while operating within clear governance frameworks.
The real challenge in the industry isn’t a lack of data - it’s turning that data into meaningful action in real time.
Learn how industrial professionals plan to maximise AI's potential over the next few years in the free report "How AI is Shaping the Future of Work Across Industrial Sectors”.
While AI has helped operators make more informed decisions, agentic AI takes this further. It doesn’t just surface insights, it executes tasks autonomously. This will redefine efficiency, reduce manual intervention, and allow engineers to focus on high-value activities.
Imagine a digital co-worker that continuously monitors asset performance, predicts maintenance needs, and automatically adjusts operational parameters - all without human intervention. This is no longer a theoretical future; it’s a reality being enabled by agentic AI.
Unlike traditional AI or robotic process automation (RPA), agentic AI doesn’t rely on predefined scripts. It learns, adapts, and makes goal-oriented decisions helping operators manage assets in dynamic environments with greater efficiency.
Gartner predicts that by 2028, at least 15% of day-to-day work decisions will be made autonomously by AI.
In heavy asset industries, this means:
• Faster incident response
• Improved safety measures
• Optimized energy usage
Many oil & gas companies are drowning in data but struggle to connect insights across business units. Agentic AI bridges these silos, ensuring real-time intelligence flows seamlessly between production, maintenance, and logistics teams.
Agentic AI can predict failures before they happen and autonomously schedule maintenance, order spare parts, and reroute workflows to ensure operations continue without disruption.
We believe trust is critical when AI moves from recommendations to action. AI-driven autonomy must operate within strict governance frameworks to ensure it aligns with business goals and regulatory standards.
That’s why we’re setting the benchmark for responsible AI—where automation is always accountable and built with clear security, compliance, and ethical guardrails.
"The future of AI in oil & gas isn’t about replacing human expertise - it’s about amplifying it. Agentic AI ensures that automation enhances decision-making, not bypasses it."
The next decade in heavy asset industries will not be about man versus machine, but rather man and machine working smarter together.
The companies that thrive will be those that embrace AI as a partner in operations. Agentic AI will fundamentally change how we manage assets, optimize resources, and drive sustainability in oil & gas.
As Gartner highlights, the companies that prepare now will gain the greatest competitive advantage. The transition from AI-assisted decision-making to fully autonomous operations is already underway.
Find out more on how you can prepare in the free industrial AI research report.
The shift to agentic AI is happening now. The question is: Will your company lead the change—or struggle to keep up?
Let’s explore how we can help your organization prepare for AI-driven autonomy.
