By Greg Woolf, AI RegRisk Think Tank
Everyone wants to know how AI is being used in the real world—across industries and job roles. Understanding its applications provides us with two key perspectives: first, it reveals where to start deploying AI today so we don’t fall behind; and second, it helps identify which job roles are most likely to be impacted in the future.
Anthropic, a leading AI research organization and suite of large language models, recently set out to provide a factual, data-driven analysis of AI usage by industry and job role. Anthropic’s Claude AI system is currently the best-rated frontier model for coding. This strength in coding skews the reported data in favor of developers. However, when we strip out this developer-centric usage, a more balanced picture emerges—one that shows robust AI adoption across a broad spectrum of industries.
Meanwhile, visionary leaders like Sam Altman, CEO of OpenAI, have argued that AI will drastically lower the cost of knowledge work and augment human capabilities to levels once thought impossible. Altman envisions a future where AI acts as a virtual coworker, exponentially boosting productivity across fields.
Job Roles: Who’s Leading in AI Usage
When we exclude developers using the models, the picture becomes more nuanced. Research-intensive sectors—such as those in scientific, business, and financial services, and academic research—are leading the way in AI usage. Professionals in these areas are leveraging AI to drive deeper insights, refine predictive models, and accelerate innovation. In addition, roles in administration and creative industries—spanning arts, media, and design—are also early adopters, using AI to streamline processes and augment creative output.
The Spectrum of AI’s Role: From Augmentation to Autonomy
Anthropic’s study reveals that roughly 57% of AI interactions currently support human efforts—assisting with tasks rather than fully replacing them. For example, writing tasks can be dramatically shortened, and complex negotiations streamlined. Yet, a notable 43% of interactions involve direct automation of tasks—a figure that, even in this pre-agentic era, signals an impending shift toward greater autonomy. As AI matures, these tools are expected to transition from supportive roles to independent agents capable of executing complex processes with minimal human oversight.
Altman’s Prediction: Transforming Knowledge Work
Sam Altman predicts that AI will fundamentally transform knowledge work by drastically reducing its cost and augmenting human capabilities. In his view, AI will act as an intelligent, scalable virtual coworker—capable of handling routine and data-intensive tasks at near-zero cost—freeing up humans to focus on creative, strategic, and interpersonal aspects of work. He envisions a future where even everyday tasks are performed by AI, allowing individuals to leverage an “army” of digital assistants. Applied to wealth management, these predictions suggest that AI will automate many data analysis, research, and routine administrative functions, enabling financial professionals to focus on high-level advisory roles, personalized client service, and strategic decision-making.
How Will AI Impact Wealth Management?
As AI automation permeates various sectors, wealth management is poised for a significant transformation. Here are several key areas where wealth management roles are expected to evolve:
Proactive Research & Portfolio Optimization: AI-driven research will become indispensable for analyzing vast amounts of financial data, identifying trends, and fine-tuning asset allocations “on the fly” to adapt to constantly changing market conditions.
Client Behavior Analysis & Personalization: In an era of big data, AI will parse detailed client profiles and behavioral patterns to create highly personalized investment strategies, analysis, and reporting.
Risk Management & Regulatory Compliance: With markets growing more complex, AI enhances the ability to predict and mitigate risks by continuously monitoring portfolios, flagging anomalies, and ensuring compliance with evolving regulatory frameworks.
Back Office Automation & Administrative Efficiency: Many routine administrative tasks in wealth management—from data entry to report generation—will be streamlined by AI, enabling professionals to dedicate more time to client-centric and strategic functions.
In essence, while some lower-level administrative tasks may be reduced, AI is set to enhance the role of research and analysis in wealth management. The professionals who integrate AI tools into their strategic toolkit—balancing automated insights with human judgment—will lead the industry in delivering superior client value.
Looking Ahead
In a post-AI world, the conversation is no longer about if AI will disrupt jobs but rather how to manage the transition effectively. In wealth management, transforming jobs by automating routine tasks and enhancing data-driven decision-making will enable personalized client services, all while freeing human professionals to focus on high-value strategic interactions.
Greg Woolf is an accomplished innovator and AI strategist with over 20 years of experience in founding and leading AI and data analytics companies. Recognized for his visionary leadership, he has been honored as AI Global IT-CEO of the Year, received the FIMA FinTech Innovation Award, and was a winner of an FDIC Tech Sprint. Currently, he leads the AI Reg-Risk™ Think Tank, advising financial institutions, FinTech companies, and government regulators on leveraging AI within the financial services industry. https://airegrisk.com
