Businesses are slowly adopting generative AI, such as OpenAI’s ChatGPT, but its usage is still limited. While the market value of technology companies has surged due to AI developments, their sales of AI software remain relatively small. The adoption of generative AI in businesses has been cautious, with most companies still not using it in a systematic way. However, there are some notable use cases, such as chatbots for customer service and AI tools for lower-skilled workers. The implementation of generative AI in businesses is a slow process and faces challenges such as lack of expertise, data integration, and concerns about data security and accuracy.
| Signal | Change | 10y horizon | Driving force |
|---|---|---|---|
| Businesses adopting generative AI | Adoption of generative AI tools | Increased reliance on generative AI in various industries | Desire to improve productivity and efficiency |
| AI stock market boom | Investment in AI technology | Increased investment in AI by tech firms | Potential for high financial returns |
| Slow adoption of AI software | Increase in AI software sales | More businesses using AI services | Need to generate significant revenue from AI investments |
| Changing nature of white-collar work | Shift in tasks and responsibilities | Alteration in job functions and daily work routines | Advancements in technology and automation |
| Slow pay-off for technological breakthroughs | Delayed productivity gains from new technology | Longer timeframe for realizing efficiency improvements | Time required for workers to adjust to new ways of working |
| Low adoption of generative AI in businesses | Limited use of generative AI tools | Increased adoption of generative AI by businesses | Recognition of the potential benefits and value of generative AI |
| Experimentation with AI tools in businesses | Testing and refining AI tools | Development of more effective AI applications | Desire to find practical and useful AI solutions |
| New types of white-collar work created by AI | Emergence of new job roles and responsibilities | Creation of AI-related positions in various industries | Need for specialized expertise and management of AI systems |
| AI disruption of routine administrative tasks | Automation of administrative tasks | Streamlined and more efficient administrative processes | Focus on higher-value and complex tasks |
| Generative AI as a window-dressing tool | Branding regular digital efforts as AI programs | Enhancement of customer-facing products and services | Desire to appear technologically advanced and sophisticated |
| AI tools for lower-skilled workers | Support for customer service and simple tasks | Increased efficiency in customer support and administrative work | Improved customer service and reduced handling time |
| AI tools for highly skilled workers | Assistance for complex tasks and decision-making | Augmentation of skilled workers’ productivity and performance | Enhancement of work quality and output |
| Fears of AI-induced job losses | Creation of more jobs than losses | Continued employment opportunities despite AI adoption | AI complementing and enhancing human work |
| AI adoption affecting white-collar work | Changing roles and tasks for white-collar workers | Shift in skills and responsibilities due to AI integration | Need for workers to adapt and acquire new skills |
| Benefits and challenges of AI adoption | Increased efficiency and productivity vs. concerns and limitations | Ongoing evaluation of AI’s impact and potential in the workplace | Balancing the advantages and risks of AI implementation |