Over the past two years, I have had countless discussions with executives, business leaders, and AI practitioners about the future impact of artificial intelligence as part of my role for AI Strategy, Portfolio & Steering.
One question appears in almost every conversation:
Which jobs will AI replace?
While understandable, I believe this is increasingly the wrong question. A more useful question is:
Which activities within a role will no longer require human effort
because AI can perform them more effectively, consistently, and at scale?
This shift in perspective fundamentally changes how organizations should think about AI transformation.
AI is changing tasks before it changes jobs
Recent research from leading institutions such as MIT, Harvard Business School, and McKinsey points in a similar direction.
AI is not primarily replacing professions. It is progressively taking over specific tasks within professions.
Jensen Huang, CEO of NVIDIA, recently described this distinction as the difference between a person’s tasks and their purpose.
In many cases, AI can automate significant portions of information-intensive work while leaving the actual business responsibility with the human expert.
Consider an insurance underwriter. The purpose of the underwriter is not reading documents. The purpose is making sound risk decisions.
Yet a large portion of the role today still involves gathering information, reviewing reports, validating data, and preparing analyses.
These are precisely the activities that AI is becoming increasingly capable of handling.
The same applies to claims management, compliance, finance, legal, HR, and many other business functions.
The future is not AI replacing humans
In my view, the future is better described as a redistribution of work.
Historically, knowledge workers spent significant time on:
- Searching
- Reading
- Summarizing
- Documenting
- Reporting
Today, AI is rapidly taking over these activities. As a result, human work shifts towards:
- Judgment
- Prioritization
- Governance
- Stakeholder management
- Decision accountability
This is particularly relevant in highly regulated industries such as insurance, where accountability and human oversight remain essential.
The question therefore becomes:
How do we systematically understand which capabilities AI can already perform, which capabilities are emerging, and where humans will continue to play a critical role?
Understanding the evolution of AI capabilities
When viewed from a strategic perspective, AI capabilities are evolving through several distinct stages.
Predictive AI
The first wave focused on prediction.
Examples include:
- Fraud detection
- Customer churn prediction
- Risk scoring
- Pricing optimization
Generative AI
The second wave focused on content creation.
Examples include:
- Text generation
- Document summarization
- Translation
- Image generation
Reasoning AI
We are now entering a phase where AI increasingly performs structured analysis and problem solving.
Examples include:
- Complex case assessment
- Risk analysis
- Compliance reviews
- Decision support
Agentic AI
The next wave goes beyond analysis.
AI agents are beginning to execute complete workflows.
This includes:
- Gathering information
- Using software tools
- Performing actions
- Coordinating multiple systems
- Escalating exceptions
This is where AI starts moving from being an assistant towards becoming a digital workforce.
The capability question becomes a leadership question
The most important challenge is no longer technological.
It is managerial.
Leaders need to understand:
- Which activities create value?
- Which activities can be delegated to AI?
- Which decisions require human accountability?
- Which new skills become critical?
Organizations that answer these questions effectively will likely outperform those that focus solely on technology adoption.
Looking ahead
I believe we are only at the beginning of a much larger transformation.
The conversation will gradually move away from chatbots and isolated use cases.
Instead, organizations will increasingly focus on orchestrating collaboration between humans and AI systems.
Understanding this shift requires more than experimenting with new tools.
It requires a structured understanding of AI capabilities, business value, governance, and organizational readiness.
This is exactly why I have created the AI Solution Hub.
It is already being used to provide a structured view of AI capabilities, business use cases, opportunities, limitations, and governance considerations across different domains.
Why I created an AI Solution Hub
The purpose is simple.
Organizations are currently overwhelmed by thousands of AI products, copilots, agents, platforms, and use cases.
At the same time, expectations often exceed reality.
Some believe AI can already solve almost everything. Others underestimate how quickly capabilities are evolving.
The AI Solution Hub aims to create transparency.
It provides a structured overview of:
- Existing AI capabilities
- Emerging AI capabilities
- Relevant business use cases
- Opportunities
- Limitations
- Governance requirements
- Risk considerations
Most importantly, it helps separate hype from practical business value.
Its purpose is not to track technology for its own sake.
Its purpose is to help organizations better understand what AI can realistically do today, what is emerging, and where human expertise will remain indispensable. A key principle behind the platform is trust. As I discussed in my previous blog post, trustworthy AI decisions require trustworthy data. Therefore, the information and assessments within the hub are evaluated using a structured methodology inspired by NASA’s Technology Readiness Level (TRL) framework, helping organizations understand not only what is technically possible but also how mature and reliable a capability is in practice. In addition, the platform provides a market perspective by continuously monitoring AI solutions, vendors, and emerging trends, enabling leaders to make informed decisions based on both capability maturity and market developments.
If you are exploring how AI can create value in your organization and want a more structured way to navigate the rapidly evolving AI landscape, I invite you to take a closer look at the AI Solution Hub and see how it can support your AI journey.
