“Monetization” was one of the most frequently spoken words during Morgan Stanley’s 2025 Technology, Media & Telecom Conference in San Francisco.
After several years of heavy investment in artificial intelligence, companies are starting to see the benefits of the technology. The technology companies that offer AI solutions are optimistic about their prospects for revenue and return on investment. But in technology and beyond, the corporate leaders who attended the conference spoke to AI’s potential to aid in cost reduction, product development and broader customer reach, as well their own ability to leverage those benefits into stronger financial results.
“Software vendors can monetize the ability of GenAI products to bring new productivity gains for their end customers,” said Keith Weiss, who leads U.S. Software Research at Morgan Stanley.
Morgan Stanley Research estimates that AI-driven productivity could add 30 basis points to 2025 net margins for members of the S&P 500.
“Getting AI to work at an enterprise scale is very hard, but I’m finally seeing some signs of it. I am much more optimistic than before,” said the CEO of a large transportation tech company. “Over the next two to three years, we’re going to see hundreds of millions of dollars of benefits.”
This evolution hasn’t been lost on investors. “AI adopters are already outperforming the broader market,” said Andrew Pauker, Morgan Stanley Research U.S. Equity Strategist. “Companies discussing AI adoption have been rewarded in fourth-quarter earnings.”
Returns on investments are appearing in different ways. Here are three areas:
1. Cost Reductions
Companies are increasingly adopting “agentics,” an AI assistant with some level of autonomy to make decisions and take actions in some specific contexts. Agentics are trained, for example, to analyze inventory data and make necessary adjustments in response to changes in demand.
In contact centers, agentics can answer customer questions and act to resolve issues related to technical operation, delivery or payment. It’s a powerful tool to reduce labor costs and accelerate processes.
The CEO of a telecommunications company noted that customers are already calling contact centers less because AI not only addresses issues more efficiently, but it also improves service quality.
“Having fewer client calls reduces costs,” the executive said. “Good customer experience is good for the expense line.”
2. Product Development
Because of its capacity to quickly process large amounts of data, AI is a powerful tool to find the best solutions in product development.
The head of an AI software company spoke about how models are being applied in different phases of drug development, from research to trials. According to the executive, AI models have a much higher capacity than humans to cross-reference complex biological data and find accurate solutions. Processes in drug development that traditionally take months could be resolved in minutes.
3. Customer Reach
Media companies are using AI to get a fast and detailed reading of customer behaviors and preferences. With that information, AI can personalize messages to boost engagement with content, including pitching the subscription of a product. That can be done in any part of the world and in different languages.
AI’s ability to provide precise data on consumer trends is also boosting marketing and advertising efficiency. AI tools can adjust the product or service to what customers want at a specific time and then to develop campaigns that will better resonate with the target audience.
Challenges Still Exist
Despite the enthusiasm, executives are challenged to act fast. Monetizing AI is a competitive race, in which both traditional companies and startups are rushing to identify opportunities and adjust their investments.
Investing in projects that can be valuable in the long term is another challenge that emerges for executives. The CFO of a big hardware company noted that, despite the urgency to proceed with those investments, datacenters can’t be built overnight.
“We have to see AI as a durable asset,” the executive said at the conference. “We need to make sure that the results of AI investments are sellable and that we’re building a portfolio that will improve our returns in the long term.”
The Chief Product Officer of a social media company mentioned a third challenge, which is typical in any technology innovation cycle: over excitement.
The executive cited the example of projects for autonomous vehicles, about 20 years ago. At that time, many investors believed that the technology would be ready for use in about three to five years. But to this day, the use of autonomous vehicles is not yet widespread.
“Sometimes it will take it longer than people expect to see the results,” the CPO said. “We need to be patient.”
