Is AI set to enter a phase of exponential adoption growth? UBS weighs in

U.S. AI adoption reached 9.7% in Q3, projected to hit 10% by year-end, with UBS analysts anticipating an exponential growth phase that will disproportionately benefit companies in the intelligence and application layers, prompting a recommendation for balanced positioning with a bias towards AI laggards. Concurrently, a Deutsche Bank survey indicates the U.S. leads in at-work AI usage at 56% and reveals a significant demand for employer-led AI training across both U.S. and European workforces, highlighting a critical need for corporate upskilling initiatives.

Analysis

Third-quarter data indicates a steady, albeit modest, increase in U.S. AI adoption among firms, rising to 9.7% from 9.2% according to a U.S. Census Bureau report cited by UBS. The investment bank anticipates this rate will reach 10% by year-end and, more significantly, projects the sector is approaching an exponential growth phase. This inflection point is expected to disproportionately reward companies positioned in the 'intelligence and application layers' of the AI stack. Consequently, UBS analysts advocate for a balanced portfolio across semiconductors, software, and internet industries, with a strategic bias towards 'AI laggards' that may offer untapped value. Complementing this firm-level data, a separate Deutsche Bank survey highlights strong user-side momentum, with 56% of U.S. respondents reporting at-work AI usage. The survey also uncovers a critical gap in corporate strategy: while over half of employees in the U.S. and Europe express a desire for on-the-job AI training, a similar percentage has not pursued self-education, indicating a clear and unmet demand for employer-led upskilling programs.

Key Decisions for Investors

• Investors should increase scrutiny on companies within the software and internet sectors, prioritizing those in the 'application layer' that can demonstrate clear paths to monetizing AI, as this is where UBS projects disproportionate benefits will accrue.
• Consider adopting a value-oriented approach to AI investing by identifying potential 'AI laggards'—fundamentally sound companies that are in the early stages of AI integration and may be undervalued relative to the market's current leaders.
• The significant demand for employer-led AI education signals a growth opportunity; investors should evaluate companies in the corporate training, e-learning, and HR technology sectors that are developing solutions for AI workforce upskilling.
• With the firm-level adoption rate still below 10%, it is crucial to differentiate between marketing and material impact by demanding tangible metrics on AI implementation and revenue generation from portfolio companies.