The New Skills in Finance Report 2022
In a digital-transforming era, there is a widening skills gap for those who cannot adapt to the new digital world in finance.
CFTE and Elevandi published the report with the discussion with leading experts to help governments, organisations and individuals address the current skills gap in finance and build a digital-resilient workforce in the industry.
Key takeaways from "Reshaping Business With Artificial Intelligence" report published by MIT Sloan management review
CFTE summarised “Reshaping Business With Artificial Intelligence” report by MIT Sloan management review. The report highlights the high expectations for AI in business, but also notes the significant gap between ambition and execution in AI implementation across companies.
Key Aspects
- The report is based on a global survey of over 3000 executives, managers, and analysts, as well as in-depth interviews with technology experts and executives.
- The report delves into the challenges and opportunities associated with AI, highlighting the disparity in adoption and understanding of AI across different organizations.
- It emphasises the need for data training and algorithm development, and addresses various management challenges associated with integrating AI into business practices
Table of Contents
1. Executive Summary
2. About the Research
3. AI at Work
4. High Expectations Amid Diverse Applications
5. Disparity in Adoption and Understanding
6. The Need for Data Training and Algorithms
7. Beyond Technology: Management Challenges
8. What to Do Next
9. The Way Forward: Implications for the Future
Key Findings and Insights
This report will give you an insight into:
- High Expectations: There is a high level of expectation for AI across various industries, with 63% of respondents expecting significant effects from AI within five years.
- Gap in Adoption: Despite these expectations, only about 20% of companies have incorporated AI in some offerings or processes, indicating a large gap between expectation and action.
- Organisational Maturity Clusters: Four maturity clusters were identified - Pioneers, Investigators, Experimenters, and Passives - each with different levels of understanding and adoption of AI.
- Data Training and Algorithms: The need for training AI algorithms on data is critical, with many organizations lacking a clear understanding of this requirement.
- Management Challenges: Successfully integrating AI into businesses requires more than just technological capabilities; it involves overcoming significant management and leadership challenges
Key infographics
