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How the we use AI in practice | AI Summit 2026 | Norges Bank Investment Management
Summary
Norges Bank Investment Management is leveraging AI technology to enhance productivity and operational efficiency. The organization emphasizes collaboration with various stakeholders to share knowledge and best practices, aiming to lift overall productivity in the sector. Ten user cases illustrate AI's potential to increase revenue, reduce costs, and improve quality across different functions.
The organization has established a modern data warehouse to enhance data quality and accessibility for AI applications. Aiming for a 20% increase in efficiency through AI integration necessitated a cultural shift and continuous employee engagement. Training programs and an ambassador network have been created to facilitate this transition.
Norges Bank Investment Management has expanded its AI team and is actively engaging employees in AI tools and projects. The organization is committed to continuous upskilling and agile project management to ensure effective AI implementation. A responsible AI framework has been developed to align with legal standards and emphasize human oversight in AI-driven decisions.
AI applications are being utilized to enhance compliance and financial analysis in investment management. This includes automating alert reviews and identifying potential financial discrepancies across a large benchmark of companies. The organization is also implementing AI to improve ESG risk monitoring, allowing for more efficient screening of companies linked to serious issues.
Perspectives
Analysis of AI integration in investment management.
Proponents of AI Integration
- Emphasizes collaboration to share knowledge and best practices
- Aims for a 20% increase in efficiency through AI integration
- Expands AI team to enhance engagement and project management
- Develops a responsible AI framework to ensure compliance and oversight
- Utilizes AI for efficient ESG risk monitoring and financial analysis
- Implements AI to improve negotiation strategies and portfolio management
Critics of AI Reliance
- Questions the uniform engagement of employees with AI tools
- Highlights potential resistance to mandatory training programs
- Raises concerns about the accuracy of AI in interpreting complex data
- Points out the risk of overlooking critical signals in AI-driven decisions
- Challenges the robustness of AI predictions in volatile market conditions
Neutral / Shared
- AI technology is rapidly evolving, presenting new opportunities
- Continuous upskilling is necessary to keep pace with AI advancements
Metrics
user_cases
ten user cases
demonstrating AI's applications
This showcases the organization's commitment to exploring diverse AI applications.
we have a lot of user cases across the firm, and we could have picked many, many different ones. We picked 10
transformations
three major steps
foundational changes for AI strategy
These steps are crucial for establishing a robust AI framework.
I want to talk about three major steps that we have done that have built the foundation for our AI strategy.
efficiency
20%
target increase in efficiency through AI integration
Achieving this target is crucial for the organization's operational success.
we should be 20 percent more efficient
team_size
ten people
size of the AI team
A larger team can enhance the capacity for AI initiatives.
We started off with just three people, and we are not going out to ten.
employee_engagement
more than half %
employees using Claude code
High engagement indicates a strong adoption of AI tools.
more than half of the employees are using Claude code to create solution.
project_count
171 projects
new projects identified
A diverse project portfolio can lead to innovative solutions.
we found 171 new projects.
manual processes
cut all our manual processes in half by the end of 2028 %
ambition to reduce manual processes
This goal indicates a significant shift towards automation and efficiency.
to cut all our manual processes in half by the end of 2028
mentions
more than 5,000 articles
media presence this year
Increased mentions indicate growing visibility and relevance in the market.
So far this year, more than 5,000.
Key entities
Timeline highlights
00:00–05:00
Norges Bank Investment Management is focusing on leveraging AI technology to enhance productivity and operational efficiency through collaboration with various stakeholders. The organization has identified ten user cases that illustrate AI's potential to increase revenue, reduce costs, and improve quality.
- AI technology is advancing rapidly, offering both opportunities and challenges that organizations must navigate to fully leverage its benefits
- Norges Bank Investment Management prioritizes transparency to build trust and gain insights from both internal and external sources, which is essential for effective technology application
- The organization seeks to work with various stakeholders to boost productivity in both the private and public sectors, viewing collaboration as key to enhancing efficiency
- Norges Bank Investment Management has pinpointed ten user cases that demonstrate AIs diverse applications, showcasing its potential to increase revenue, cut costs, and enhance operational quality
- A strategic shift involved bringing outsourced functions back in-house to improve expertise and data management, strengthening the organizations capabilities for market expansion
- Migrating to public cloud infrastructure has been crucial for addressing data limitations, allowing for improved scalability and efficiency in utilizing advanced data solutions
05:00–10:00
The organization has established a modern data warehouse to enhance data quality and accessibility for AI applications. Aiming for a 20% increase in efficiency through AI integration necessitated a cultural shift and continuous employee engagement.
- The organization has established a modern data warehouse to enhance data quality and accessibility for AI applications. This foundational step is crucial for leveraging AI effectively across the firm
- A significant push for efficiency was initiated, aiming for a 20% increase through AI integration. This ambitious target necessitated a cultural shift and continuous encouragement for employees to adopt new practices
- An ambassador network was created to identify and develop valuable AI use cases within teams. This initiative fosters collaboration and showcases the potential benefits of AI throughout the organization
- AI was integrated into all major events and activities within the organization to maintain focus on its importance. This consistent emphasis ensures that AI remains a priority in daily operations and strategic planning
- Mandatory training sessions were implemented to equip all employees with essential AI knowledge and skills. This approach addresses the challenge of engaging those who may be resistant to learning about AI
- The organization recognizes the need for ongoing support and nudging to facilitate the adoption of AI practices. This commitment to continuous improvement is vital for achieving long-term efficiency and innovation
10:00–15:00
Norges Bank Investment Management has expanded its AI team from three to ten members, emphasizing a collaborative approach to AI implementation across the organization. The organization is actively engaging employees in AI tools and projects, aiming for a 20% increase in efficiency through continuous upskilling and agile project management.
- The organization has expanded its AI team from three to ten members, emphasizing that the responsibility for AI implementation lies with the entire organization rather than just the team. This shift highlights the importance of collaboration and empowerment in driving AI initiatives
- Employees at Norges Bank Investment Management (NBIM) are actively using AI tools like Claude and Cursure, with a significant portion of the workforce engaged in coding and project development. This widespread adoption of AI tools is crucial for enhancing efficiency and fostering innovation across the organization
- The AI transformation process has unfolded in three phases, starting with providing tools and training, followed by identifying high-value projects. Although the search for a single groundbreaking AI use case yielded many smaller projects, this indicates a solid foundation for future efficiency improvements
- The organization is committed to continuous upskilling, recognizing that the rapid evolution of AI necessitates ongoing training for all employees. Recent initiatives, including a two-day hackathon, aim to keep skills current and relevant in a fast-paced technological landscape
- A shift in project management culture is underway, moving away from traditional Scrum methodologies to a more agile approach that empowers small teams to make decisions independently. This change is expected to accelerate project delivery and enhance responsiveness to AI-driven opportunities
- Ensuring quality and compliance in AI applications is a top priority, leading to the development of a framework to guide responsible AI usage. This focus on governance is essential for maintaining trust in AI systems and ensuring they align with organizational standards
15:00–20:00
Norges Bank Investment Management has established a responsible AI framework that aligns with legal standards and emphasizes human oversight in AI-driven decisions. The organization aims to enhance efficiency and decision-making while adhering to ethical standards, fostering a culture of responsible innovation.
- The organization has established a responsible AI framework to ensure ethical use of AI technologies. This framework aligns with legal standards and emphasizes the importance of human oversight in AI-driven decisions
- A risk-based approach is taken in the AI guidelines, differentiating between simple systems and those that significantly impact individuals. This ensures that the governance structure is appropriately robust for varying levels of risk
- An operating model has been created to translate AI guidelines into actionable processes, covering everything from development to deployment. This model is crucial for maintaining compliance and managing risks effectively
- The AI governance working group plays a vital role in ensuring that responsible AI practices are actively implemented. This group stays informed about regulatory changes and addresses AI-related challenges as they arise
- Training for all employees on responsible AI is a priority, fostering a culture where everyone understands AIs capabilities and limitations. This collective awareness is essential for maintaining high standards and accountability
- The organization aims to leverage AI to enhance efficiency and decision-making while adhering to legal and ethical standards. This commitment to responsible innovation is expected to drive significant business value in the long term
20:00–25:00
The organization has transitioned to a cloud-native infrastructure, utilizing tools like Snowflake for enhanced data management and analysis. This shift enables the investment team to respond swiftly to high-pressure share sale requests, optimizing financial performance through specialized AI agents.
- The organization has adopted a cloud-native infrastructure, using tools like Snowflake for efficient data management. This transition enables employees to effectively utilize advanced technology
- The investment team operates under high-pressure conditions, such as managing urgent share sale requests. Their swift and precise data analysis is crucial for optimizing the funds financial performance
- To improve decision-making, the team uses specialized AI agents that work together to collect and analyze data from multiple sources. This method provides a thorough understanding of complex transactions in significantly less time
- A prototype has been created by the investment team to streamline data collection, allowing them to concentrate on analysis. This improvement enhances decision-making and boosts profitability
- The communication department has adopted a data-driven strategy to improve transparency and effectiveness. By leveraging AI tools, they have refined their communication methods to deliver more insightful information about their operations
- In 2025, the fund was referenced in nearly 50,000 articles, underscoring the significance of effective communication. This year, they have already exceeded 5,000 mentions, reflecting an increasing media presence
25:00–30:00
The organization has developed an AI-powered sentiment analysis system to enhance media monitoring and cybersecurity risk management. This system automates data collection and analysis, allowing for quicker decision-making and risk assessment.
- The segment primarily promotes the use of AI for media monitoring and cybersecurity risk management