The predictions for the future of AI are wildly contradictory: It will either create a work-life paradise or it will take all our jobs—if it doesn’t kill us first.

Business leaders know they need to reckon with AI. The questions are when and how? It’s especially challenging for midsize companies, which struggle to fund the technology they already have, much less something as new and shapeshifting as AI. Do they prioritize it in their business strategy now, or do they wait for the hype to settle a bit to see which choices become clearer?

An SAP Insights survey of 12,000 executives in companies with 250–1,500 employees explores both scenarios. Roughly half of the respondents say they are steaming ahead with AI—specifically, generative AI (or GenAI)—as a high priority despite the uncertainty that surrounds it.

Let’s call these executives AI optimists. We compared them to respondents who consider GenAI to be a low priority or not a priority at all—tellingly, only about 8%—who we’ll call AI skeptics. We found that the AI optimists not only are significantly more likely to be using AI right now, but they also have higher expectations for AI to transform a wide range of business processes to help their companies thrive.

“Over the last 25 or 30 years, technology has gotten better, which means analysis has gotten better, which means organizations have gotten better,” says a CFO from an industrial machinery company who we interviewed as part of this research. “AI is the next version of that.”

Confidence from AI experience

The AI optimists’ confidence may come from their early experience. They are much more likely than the skeptics to say they are using AI to a strong degree in a wide range of applications. These include crucial processes that benefit from AI’s powers of prediction, such as detecting fraud, developing forecasts, and monitoring for cybersecurity threats. The optimists are also more likely to see the value of AI for improving efficiency. For example, they are significantly more likely to be using it to a strong degree to create management summaries and annual reports and to manage interactions with customers.

It isn’t a surprise, then, that the optimists are significantly more likely to put a high priority on transforming a variety of business processes with AI, including forecast-focused processes, such as enhancing data security and privacy, and enabling more accurate and effective decisions.

Better data, beter AI-supported decisions

A consulting company in the oil and gas industry built a GenAI-based tool to help its customers better navigate and understand complex engineering data about oil wells and mines around the world. Previously, customers needed to be experts to know what to look for, which limited access to a handful of people in their organizations, says the company’s CISO.

Not anymore. “We’ve built a GenAI interface on top of that data so that now anybody can use it and they can literally ask natural language queries.” Better customer access to data has led to better business results, he says.

Meanwhile, an industrial machinery company hired a data analyst to create a comprehensive data repository with AI tools to analyze growth trends, improve revenue forecasting, and predict the probability of the sales team closing individual transactions. “We’re doing it to get more insights into our business and help drive better business decisions,” says the company’s director of finance.

Both companies have one thing in common: a high-quality data store to work with. The optimists and the skeptics are similar in their need for better quality data and tools to make decisions to ensure business growth, but the optimists tend to see this challenge as less of an issue.

“We have the data, that’s not the problem,” says a CIO from a bank. “The first challenge is that data is very unstructured in our environment. The second is that the data exists on multiple systems and those systems don’t talk to each other. It is a long-term project to incorporate all these other legacy systems and their databases into one.”

Open to AI-driven change, but mindful of risks

The optimists have another advantage over the skeptics when it comes to AI. They appear to be more ready for change. The optimists are significantly less likely than the skeptics to report a lack of change management processes as a challenge to growth.

The optimists are also more sensitive to one key obstacle: having the people they need to carry out their AI plans. The optimists are significantly more likely to cite finding, attracting, and retaining AI talent as a risk. That’s to be expected from organizations that have gotten their hands dirty. They are more aware of what they need to advance.

Yet both the optimists and the skeptics view many other AI-related risks equally. For example, both groups are similarly concerned about the risk that they will act on incorrect information generated by their AI systems, not have sufficient data to train their models, or face legal liability for AI’s inaccuracies.

In our interviews, we detected differences in corporate culture that may influence how companies manage both change and risk. Does the culture encourage employees to try AI?

Some executives we interviewed say their companies have blocked employee access to tools like ChatGPT for fear that confidential information could seep out. Others point out that unless employees can experiment with AI, they won’t discover how best to use it. At their companies, they employ the same guidance for AI as for any other technology: Don’t be stupid.

“You would never take your client’s name and just put your problem with the client into Google, right?” says the CTO of a law firm. “And therefore, we teach people, don’t put that into generative AI either.”

Trust goes a long way. Employees will make mistakes, and they need to know they will be supported, adds the law firm CTO: “If something doesn’t look right, it’s okay to ask.”

A culture that encourages curiosity is another advantage, especially with technologies that change so rapidly, like GenAI. “Encourage them to figure out where they can use it and then let them have a little bit of fun with it,” says the industrial machinery company CFO, who describes the company culture as “inquisitive” and a place where leaders see new technologies as a way to make the business better. “The curiosity in and of itself is probably one of the main drivers of [our AI] success.”

The chicken or AI problem

One of the promises of AI is that it will simplify business processes. On the other hand, if you’ve already simplified processes, it’s going to be easier to apply AI. Though our survey doesn’t tell us which came first, the AI optimists say reducing complexity in business processes is much less of a concern than it is for the skeptics.

Certainly, there are some simple ways to reduce process complexity using one of AI’s strongest features: natural language processing, which plows through reams of internal documents to find the most important tidbits. “Instead of having a lawyer read through a 500-page deposition, we can virtually just go through and search for the parts that we need and have it summarized,” says the law firm CTO. “We’re using electronic discovery so that we can go through 10,000 e-mails or 10,000 documents and it will show us the hottest documents first.”

The firm also uses AI to pore through an internal database of case law to find the most relevant precedents and summarize them. This means lawyers can now spend more of their time focusing on case analysis rather than hunting down information.

AI innovation for resilience

The AI optimists have one more distinguishing trait. They are significantly more likely than the skeptics to see investments in new technology and business innovation as buffers against economic uncertainty and building blocks for resilience.

The skeptics, meanwhile, tend to be driven more by tried and true strategies. They are slightly more focused on strengthening the supply chain and outsourcing nonessential functions.

To know AI is to consider AI

It’s not a stretch to conclude that when leaders see technology and business innovation as the most important ingredients to a bright future, the door opens wider for investments in AI. And when leaders are focused elsewhere, AI will be a lesser priority overall.

While skeptics might wait for more experience before making AI a bigger priority, optimists are already focusing on AI as they experiment to see what succeeds.

Which will you choose?