AI's Business Value: Lessons from Enterprise Success

In partnership with NewtonX, we surveyed 400 of Google Cloud’s AI customers to reveal the use cases with which organizations have realized business value. Below are the key insights that can help you do the same.

Over the last year and a half, organizations of all shapes and sizes have been experimenting across a wide range of generative AI use cases — and in record time. In mere months, companies have gone from playing with simple pilots for answering questions and making predictions to building powerful generative AI agents that can book your next vacation, help manage inventory and keep shelves stocked in stores, draft clinical documentation, or even become the biggest virtual influencer in the world.

But with so many opportunities there for the taking and a constant stream of new capabilities emerging on what feels like a daily basis, it can be difficult to zero in on the places where AI is already delivering business value. As more and more organizations start the journey towards putting AI experiments into production, though, it will be more critical than ever to determine the use cases driving demonstrated value as they seek to capitalize on quick wins while still investing for the future.

In a new global survey conducted in partnership with NewtonX, we explored the current applications of AI that are bringing concrete benefits to organizations right now. Based on responses stemming from more than a thousand use cases from over 400 Google Cloud customers, here are five key insights we found within organizations gaining traction with AI:

1. High impact, low time-to-value use cases unlock ROI success.

When you’re starting with AI, it’s often best to start with lower risk, low-hanging fruit that can deliver positive results to help you build momentum and gain support for longer-term investments. Looking deeper into the reported use cases, we wanted to know which ones have a high revenue impact and a low time to realize value — we call those “Best Bets.”

The survey results indicate that typically the strongest “Best Bets” involve applying AI to improve back office business processes, such as next-best automated task actions, prioritization recommendations, productivity analysis, and more streamlined workflows in areas like HR and IT. Other “Best Bets” included use cases for developer productivity, digital commerce and enhancing experiences, and individual productivity — all of which took on average less than six months to deliver revenue increases of more than 10% according to the survey.

2. Transformational AI use cases are the key to delivering maximum value.

When considering applications for AI, we see organizations pursue use cases that create better customer experience and drive revenue (business growth focus) or improve productivity, security, cost efficiency or sustainability (internal efficiency focus). According to the survey, the winning formula for creating high value is when AI can be leveraged to create significant value both in business growth and internal efficiency.

In general, the majority of AI use cases are still focused on providing benefits for customers or driving efficiency within the organization, but in the future, we expect to see an increasing number that will address both needs at the same time. While less than 5% of the currently reported use cases are delivering substantial impacts in both areas, hitting that proverbial sweet spot is worth it. This small group of “transformational” use cases delivered on average more than 5X more value than all other use cases.

What are these use cases? We saw that developer productivity is mentioned most frequently as the impact area of transformational use cases (e.g., assisted coding). The next most frequent area is use cases that create new products and services (e.g., externally available products and services for customers).

In other words, the most successful AI use cases for generating value are those that can deliver both external and internal benefits for your organization. Leaders looking to realize tangible results should therefore aim to implement AI use cases that deliver improvements and streamline operations across the entire spectrum of business value, rather than those that focus on a single area.

3. AI is the next productivity powerhouse.

Given the recent enthusiasm about gen AI’s ability to streamline workflows and augment repetitive tasks, it’s no surprise that the primary type of value gained with AI is productivity — more than 30% of all value metrics collected from respondents mentioned productivity, followed by business growth (20%) and cost efficiency (19%).

According to the results, customers are already achieving significant productivity gains using AI. Companies have been able to accelerate time to insight by 40%, boosted IT (38%) and business (37%) productivity, and reduced time to market for products and services (36%). In addition, productivity use cases are typically easier to measure, with customers tracking value metrics, such as increased accuracy, task completion and processing times, or improvements in employee output.

Overall, the results already show that the most immediate type of value to be gained with AI is better productivity, which can in turn deliver tangential benefits that enhance performance and create more satisfying customer experiences. For example, improving the accuracy of forecasting wind patterns can reduce unforeseen cancellations and flight delays, ensuring travelers arrive happily at their destinations.

4. Developer AI carries significant potential to generate value at scale across the organization.

Intriguingly, the types of AI use cases that hold some of the most potential for driving productivity may not be the ones you expect.

The survey indicated that developer productivity was the area that not only had the highest number of use cases reported over all, but these use cases also form the largest group within transformational use cases. Customers shared a wide range of tasks where they are applying AI, including code assistance, root-cause analysis, testing, and error detection.

We might be tempted to think these use cases only “make developers’ lives easier - that’s great, but why should the overall organization care”? In fact, developer productivity changes the needle for everything else: The faster your developers create high quality code, the faster your products and services ship to market. This is of utmost importance because developers are a scarce resource.

In particular, using AI-assisted coding to deliver more robust code faster was shown to not only reduce business and IT costs by an average of 63%, but also led to an improved ability to identify threats (88%) and productivity gains that lifted revenue by 18%. Developer productivity AI use cases were also among the fastest types of use cases to implement, with an average time to value of five months.

5. Security is the hidden value champion of AI.

The relationship between AI and security has two dimensions - applying measures to secure AI systems and applying AI to strengthen security protections. According to the survey results, organizations embracing AI technologies have seen measurable progress in their ability to secure their businesses.

Specifically, incorporating AI has enabled our customers to improve their ability to identify threats by 55% — the greatest percentage improvement out of all the other business value metrics in all areas. Better threat detection has also served to deliver other improvements, such as reduced time to resolution (37%) and the number of security tickets (36%).

When we looked at the use cases that created the highest security value, interestingly, they are not technical at all. These use cases speak about improving business processes or customer experiences - in a secure way. The effect seems to be similar to what we described for developer productivity - solving a “tech” problem with AI empowers the whole organization to boost business value.

Looking forward: The value of AI is being confirmed.

The results of this study confirm what we learned from the recent The ROI of Gen AI study. Although both studies were conducted independently from each other, with different respondents and questions, they both confirm that companies that embrace a holistic approach to AI adoption — prioritizing strategic use cases, and investing in the tech teams, security and data enabling these — are the ones already realizing substantial returns today.

Research Methodology

This report is based on a survey of 400 of Google Cloud’s AI customers. Respondents were senior leaders (director+), representing organizations from North America, Latin America, EMEA, and APAC, and across key industries including Public Sector, Financial Services, Manufacturing & Automotive, Retail & Consumer Packaged Goods, Telecommunications, Healthcare & Life Sciences, and Media & Entertainment. This was an online survey conducted in partnership with NewtonX.