In the ever-evolving landscape of technology, paradigm shifts represent technological innovation that can reshape industries over time.
Over the past 60 years, we’ve witnessed four distinct technological revolutions. From the dawn of mainframe computers in the 1960s and the rise of personal computers in the 1980s, to the internet boom of the mid-90s and the mobility era of the late 2000s, each shift has led to changes over time.
Now, we stand on the brink of a fifth paradigm shift—artificial intelligence (AI).
Our U.S. growth and core equity team has been monitoring the ways in which AI is beginning to influence various sectors and industries, particularly within the large-cap technology and consumer spaces.
Productivity Redefined
A hallmark of transformative changes, such as those that could be brought about by AI, is the enhancement of automation, efficiency, and productivity, says Jim Golan, CFA, partner, a portfolio manager on our Large Cap Growth strategy. Tasks like drafting emails or developing presentations are poised for automation, thereby freeing up time for more strategic activities.
AI technology should also help to improve voice tools, including Siri and Google Assistant, making them capable of handling more complex tasks such as rebooking flights and arranging travel accommodations.
In industries such as healthcare, AI could help enhance drug discovery and design by providing predictive analytics that can accelerate decision-making, reduce costs, and improve treatment effectiveness.
In addition, the advertising industry is undergoing change, with traditional media, such as print advertising and radio, being overtaken by digital platforms that AI could help to amplify. Several large-cap companies are beginning to leverage AI to achieve higher conversion rates for ads, resulting in better returns on ad spend.
Several large-cap companies are beginning to leverage AI to achieve higher conversion rates for ads, resulting in better returns on ad spend.
Consumer Goods: Streamlining the Supply Chain
Nancy Aversa, CFA, partner, a research analyst focusing on the consumer sector, believes AI could accelerate product time-to-market, optimizing supply chains by helping source raw materials, streamlining manufacturing, and refining logistics to ensure timely delivery to customers.
AI also has the potential to align inventory levels with consumer demand. This would ensure that products are available where and when they are needed, whether in stores or through e-commerce channels.
In addition, AI’s potential impact on supply-chain efficiency presents a sizable revenue and profitability opportunity for many large-cap consumer companies.
Today, consumer companies may take upwards of two years to bring certain products to market, which makes predicting trends challenging. AI could help analyze diverse data sources, such as social media and fashion blogs, to quickly identify trends and consumer sentiment related to products, says Nancy.
And by shortening supply chains, companies would be able to develop more frequent product line iterations, with collections potentially hitting stores every couple of months instead of seasonally.
Ultimately, shorter lead times and production cycles may benefit large-cap consumer companies—which have extensive global supply chains, significant market opportunities, and strong capital resources—helping them better align with consumer preferences.
AI’s potential impact on supply-chain efficiency presents a sizable revenue and profitability opportunity for many large-cap consumer companies.
Data Management: From Chaos to Clarity
Businesses have accumulated vast amounts of data that remains inadequate for AI projects due to fragmentation, quality, and governance issues.
According to Danny Goode, a research analyst focused on large-cap technology companies, the challenge lies with how this data can be efficiently structured for immediate use.
This dilemma reflects the broader issue of data readiness in the AI era, where the potential for insight and efficiency gains is significant but requires foundational work in data management.
Centralized infrastructure layers that link data security, governance, and orchestration are already being deployed, explains Danny. Some companies are exploring cloud migration to consolidate data, a trend renewed by AI's potential despite previous concerns over costs.
The primary beneficiaries of these developments have been large-cap software companies that have the infrastructure, data, and expertise to manage and optimize the entire process. They can quickly bring new AI tools to market, making them well positioned to capitalize on these advancements.
The race to organize and leverage data for AI applications will only intensify, and we believe the ability to effectively manage and utilize data will be a key determinant of a company’s competitive advantage going forward.
The primary beneficiaries of these developments have been large-cap software companies that have the infrastructure, data, and expertise to manage and optimize the entire process.
In Conclusion
At William Blair, our expertise in quality growth investing has spanned many decades—and paradigm shifts. We are excited about the potential of AI, but recognize its impact should be measured in years, not days, as the technology and its capabilities continue to unfold.
Jim Golan, CFA, partner, is a portfolio manager on William Blair’s U.S. growth and core equity team.
Nancy Aversa, CFA, partner, is a research analyst on William Blair’s U.S. growth and core equity team.
Danny Goode is a research analyst on William Blair’s U.S. growth and core equity team.
