Section 1 - Optimism and
high expectations
Companies are ramping up their spending plans as they expect to derive significant value from generative AI
Nearly everyone we surveyed (94.5%) said they plan to spend more on generative AI in the next 12 months, with none planning to cut back.
Business leaders in the US and Canada are optimistic that generative AI – as part of the larger AI juggernaut – has the potential to transform their companies. Many already spend significantly to integrate generative AI into their enterprises. These investments will only escalate in 2024, the so-called “Year Two” of generative AI, according to the business leaders we interviewed.
In generative AI’s break-out year, just over one quarter of the companies in our survey (26%) budgeted at least $5 million on generative AI initiatives (Figure 1). Yet a significant group merely dipped their toes into the water: nearly half (45%) spent less than $1 million on generative AI in the past year, while relatively few (5%) invested more than $10 million.
Figure 1. Generative AI investments set to accelerate in the coming year
Source: Infosys Knowledge Institute
Looking ahead, spending is certain to increase significantly and almost universally. A large majority of respondents (72%) said they plan to spend more on generative AI in the next 12 months, with none planning to cut back. And in many cases, they are flipping the most recent spending ratio, with very few companies only dabbling in the technology. In the coming year, just 13% of executives said they intend to spend less than $1 million on generative AI, while one-fifth said they will invest more than $10 million.
Overall, we expect that companies in the US and Canada will invest $2.3 billion more on generative AI in 2024 than 2023. Infosys used its survey responses — covering companies of various sizes and industries — and extrapolated their spending into the future. Conservatively, we estimate that companies in the US and Canada have invested $3.3 billion in generative AI in the past 12 months. Based on what executives told us, generative AI spending is expected to grow to nearly $5.6 billion — a 67% increase.
Generative AI wins the prize as the most hyped technology in the world today. But these dynamics differ from “disruptive” innovations of the past, such as blockchain or voice-activated tech, that lacked major uptake by large companies. Often, nimble startups adopt new technologies and show tantalizing hints of the value to come.
Meanwhile, large corporations wait and see how these innovations progress, or they simply are too large to turn on a dime.
This time, the largest companies are ahead of their smaller counterparts (Figure 2). We found that 73% of companies with more than $10 billion in revenue have implemented generative AI solutions. That is true of barely more than one-third (38%) of the companies that have between $1 billion and $10 billion in revenues. Even fewer of the smallest companies in our sample have implemented generative AI (27%).
Figure 2. Large companies more likely to report business value from generative AI initiatives
Section 1 – Optimism and high expectations
Generative AI Radar 2023: North America
These industry giants not only spend more but also generate more return from their investments. Around 30% of the larger companies said they deliver business value from their deployments, compared to less than 10% of the smaller firms.
These dynamics are the reverse of what we typically see from emerging technologies — and for good reasons. Generative AI emerged as a consumer tool, widely available and straightforward to deploy. Even companies with ingrained processes could quickly and relatively easily incorporate generative AI into their workflow, at least on pilot projects.
As a result, this innovation became surprisingly less risky for the traditionally risk averse. Rather than replacing existing processes, generative AI can be seen as additive. In other words, there is less opportunity cost for large firms (with capacity) to experiment with generative AI without impeding existing work, where a leaner, smaller company (without spare capacity) halts one initiative to test generative AI. In this context, it is logical that the largest companies more effectively apply their economies of scale to this emerging technology.
We are defining proofs of concept for generative AI use.
We are developing products based on generative AI.
We are implementing generative AI to create business value.
We are not currently using generative AI.
