Artificial intelligence is no longer a side story or something “up and coming.” It is shaping market leadership, corporate strategy, and workflows within financial firms. That opens a real opportunity, but it also concentrates risk. The job for planners and portfolio managers is to harness the wave without letting a few names quietly drive all client outcomes.

Concentration Check

The recent strength in United States large-cap equities continues to come from artificial-intelligence leaders and the ecosystem surrounding them. As of early to mid-2025, more than forty percent of companies in the S&P 500 cited “AI” on their earnings calls for the fifth straight quarter, and this trend doesn’t show any signs of letting up soon, as the pattern appears to be continuing. What looks like “diversified large-cap exposure” may, in reality, be tightly linked to a dominant technological force.

Meanwhile, access to the market’s upside via a handful of names risks tilting portfolios even if the cap-weighted index appears broad. One must quantify how much of a client’s equity return is riding on artificial-intelligence exposure. Stress-test portfolios for continuation of this trend, as well as for what could happen if the potential bubble bursts. This may be a unique time, but refrain from uttering, “this time it’s different…”

Corporations are Rewriting Playbooks

Boardrooms are not just talking about artificial intelligence. They are reorganizing around it through restructuring, budget shifts, and targeted headcount reductions. Amazon recently confirmed that its corporate workforce will shrink over the next few years. And while they argue it’s not purely due to AI adoption, there is truth behind generative artificial intelligence taking over many repetitive tasks. The company is redeploying both capital and talent toward machine learning infrastructure, automation, and AI-powered customer systems. This is clearly a bet on artificial intelligence and is part of a long-term plan to integrate generative AI across logistics, retail, and cloud operations, reflecting a larger movement among corporations using artificial intelligence as both a cost lever and a growth driver. For many companies, this is the future.

Accenture made a similar move earlier this year, announcing job cuts alongside new investments in digital automation and predictive AI tools. They announced thousands of job cuts while committing billions of dollars to expand their AI and automation capabilities. Accenture is investing heavily in generative AI tools and retraining programs to position itself as a leader in enterprise transformation through automation and analytics. The move highlights how artificial intelligence is no longer a future concept, but an immediate force reshaping workforce structures, consulting models, and capital priorities across global industries. It’s already happening. Companies are changing rapidly and are betting on value now, which could pay literal dividends for the foreseeable future.

Finance is Implementing at Scale

Wealth and asset management firms are moving from experimentation to execution with artificial intelligence. For example, the KPMG 2025 asset-management outlook report shows that firms in the industry are now shifting from concept to development-phase AI programs. Meanwhile, a study by Citigroup and CREATE-Research found that 41% of respondents in investment management said they were in the implementation phase for AI, and 26% specifically for generative AI. Implications are clear. When a firm like Goldman Sachs or JPMorgan Chase deploys AI-driven tools into research production, distribution systems, or client-service workflows, the investment universe shifts.

You need to assess how many of your clients’ portfolios reflect companies investing heavily in data infrastructure, model training, automation, and scale-out deployment. You also need to think about this from the perspective of operations: what you can do to mimic and add value, and what gaps will be created along the way as larger operations make this shift. This is a time to be clear with clients about where AI is being used, what it can and cannot do, and to avoid the promise of automatic alpha. The edge now lies in delivering consistency, speed, and insight rather than chasing perfect predictions. The human touch has never been more important; now it will be paired with new tools.

Final Thoughts

Artificial intelligence is both a theme and a tool. As an investment theme, it has delivered strong returns but with growing concentration, requiring careful risk management. As a business tool, it is reshaping budgets, staffing, and capital priorities, influencing future earnings and competitiveness. For financial professionals, it represents both an opportunity to chase and a potential market to fill in the gaps. The goal is to help clients participate in the transformation while keeping diversification, position sizing, and process at the center. That balance is what turns short-term excitement into lasting results.

Author: Phil Stuczynski is an associate teaching professor in finance at Penn State Behrend. 

Editor: Greg Filbeck, CFA, FRM, CAIA, CIPM, PRM, Samuel P. Black III, Professor of Finance & Risk Management, Penn State Erie, mgf11@psu.edu.