AI to Reshape High-Skill Jobs, Says Bank CTO Bonetti

A report issued on 14 May 2026 by Paolo Bonetti, a prominent European technology analyst, outlines a significant transformation for high-skill professions driven by artificial intelligence. The analysis projects that AI could automate or augment up to 35% of core tasks in knowledge-based roles by 2030. This shift is expected to redefine job functions in sectors ranging from software development to financial analysis, placing a new premium on human judgment and strategic oversight rather than routine cognitive labor.

How Will AI Restructure Software Development?

The field of software programming, once seen as a secure and growing profession, is at the forefront of AI-driven change. Bonetti's analysis indicates that generative AI tools are becoming exceptionally proficient at writing, debugging, and optimizing code. This capability reduces the need for large teams of junior developers focused on routine coding tasks. The report forecasts a potential 20% decline in entry-level programming positions over the next five years.

However, the change is not purely one of displacement. The demand for senior-level talent is expected to surge. The report projects a 40% increase in demand for AI integration specialists and systems architects who can design, implement, and oversee complex AI-driven software systems. The role of the developer will evolve from a creator of code to a manager of AI-powered development tools, focusing on high-level logic, security, and system architecture. This creates a more specialized, and potentially more productive, engineering workforce.

Which Judgment-Based Roles Face Automation?

Beyond coding, AI is making significant inroads into professions that rely on specialized knowledge and judgment. Bonetti's report identifies fields like paralegal services, financial underwriting, and junior-level investment analysis as prime candidates for disruption. In these areas, AI models can review vast amounts of documents, identify patterns, and assess risk far faster than human counterparts. For example, AI-powered underwriting models can now process loan applications with 92% accuracy in under 60 seconds.

This does not eliminate the need for human experts but shifts their focus. A human loan officer, freed from manual data review, can spend more time on complex cases and client relationships. A lawyer can use an AI to perform initial document discovery in hours instead of weeks, allowing them to concentrate on legal strategy and argumentation. The report suggests that firms that successfully integrate AI into these workflows could see productivity gains of over 25%.

What Is the Broader Economic Forecast?

The macroeconomic implications of this shift are complex. Bonetti’s analysis points to a potential 1.5% annual boost to productivity in developed economies by 2035, driven by AI-enabled efficiencies. This could lead to significant economic growth. However, it also raises concerns about wage inequality and the productivity paradox, where technological gains do not translate into broad-based wage growth for the majority of the workforce.

The report projects that without proactive policy intervention, wages for the median worker in knowledge industries could stagnate for the next decade. These forecasts, however, depend heavily on the pace of adoption and regulatory responses. A key limitation acknowledged in the report is that historical precedent from past technological revolutions, such as the internet, suggests that initial job displacement is often followed by the creation of entirely new job categories that are difficult to predict today. The future of macroeconomic trends will depend on how society adapts to these new tools.

What Are the Proposed Solutions for the Workforce?

To mitigate the risks of job displacement and wage stagnation, Bonetti advocates for a massive, coordinated investment in workforce education and reskilling. The report's framework calls for a $100 billion investment over the next decade from a coalition of G7 nations, focused on public-private partnerships. These programs would aim to build skills in AI management, data science, and systems thinking.

The emphasis is on continuous learning as a core component of modern professional life. Bonetti suggests that corporations must move away from traditional hiring models and instead invest in upskilling their existing employees to work alongside AI systems. This approach not only helps workers adapt but also allows companies to retain valuable institutional knowledge. The future of the global technology sector hinges on this human-centric approach to AI integration.

Q: Does the analysis cover blue-collar or service jobs?

A: No, the report's scope is explicitly limited to white-collar, knowledge-based professions. Bonetti notes that automation in physical labor, driven by robotics, follows a different timeline and set of economic drivers, requiring a separate analysis.

Q: What is the single biggest barrier to AI adoption in these roles?

A: The report identifies data security and regulatory compliance as the primary hurdles. For sectors like finance and law, the challenge of using proprietary data to train AI models without violating privacy laws slows implementation, with an estimated 18-24 month lag in adoption for highly regulated industries.

Bottom Line

Bonetti's analysis concludes AI will elevate human roles toward strategic oversight, making adaptability the most valuable professional skill of the next decade.

Disclaimer: This article is for informational purposes only and does not constitute investment advice. CFD trading carries high risk of capital loss.