The growth of artificial intelligence, robotics and other next-generation automation technologies are prompting some corporate leaders to ask age-old business questions: How much should we pay for this? And who is in charge?

These and other issues are among the obstacles to fully deploying such tools cited by nearly 600 chief information officers, tech and business directors, and other C-suite executives surveyed by KPMG LLP.

Together they represent firms in a range of industries world-wide, each with $1 billion or more in revenue—including nearly two dozen with revenue above $10 billion, according to KPMG.

Roughly 30% said their companies have allocated $50 million or more to smart automation projects, and more than half have already spent at least $10 million. The initiatives include various combinations of robotic process automation, artificial intelligence, machine learning, cognitive computing and analytics.

“Once a foundational investment is made in tools, staffing, process redesign and core infrastructure including cloud, they can be applied across a wide-ranging scope of applications and functions to achieve scale,” Cliff Justice, KPMG’s head of intelligent automation, told CIO Journal.

So far, funding is being channeled into corporate finance and accounting functions, followed by group benefits strategies and compliance, and industry-specific core operations, the survey found. Other areas included supply chain and procurement and human resources.

More than half of the officials surveyed said their firm’s key strategic goal for implementing these tools is to improve or streamline customer services and front-office effectiveness. Roughly a quarter said their goal is to drive revenue growth.

Yet most of these efforts are still in the pilot-project phase. Only 17% of surveyed officials said their firms have smart automation technologies operating at full scale. As many as 30% haven’t begun investing in smart technologies or are unsure of their plans.

Among the top three obstacles identified as holding back full deployments was a lack of resources—from storage to staffing—necessary to build up smart technologies, the survey found.

Efforts also suffer through “inadequate change management and governance, lack of senior management sponsorship or lack of alignment of AI goals with overall corporate objectives,” Mr. Justice said.

Similarly, the next biggest hurdles were uncertainty about the amount of spending needed to make these deployments worthwhile, followed by a lack of “organizational clarity and accountability” to drive implementation projects.

That is prompting many companies to take a more piecemeal approach to smart automation, the survey found.

“The more ‘moonshot’ approaches to artificial intelligence or smart technologies have been cooling off over the last two years,” said Craig Le Clair, vice president and principal analyst at Forrester Inc. for enterprise architecture and business process professionals.

He said large deployments often require data science and machine learning expertise—adding to recruiting costs—while tending to have less clear timelines or business objectives.

Instead, many firms are finding a better return on investments in limited deployments of smart-tech building blocks, such as bots that mimic and replace low-value and repetitive tasks, Mr. Le Clair said.

Because smart-tech projects typically span different corporate divisions, they can include multiple corporate leaders.

The survey found that 43% of smart technologies deployments are led by IT units, and less than one-fifth involved IT and business units working together. “This scenario makes for a less than ideal outcome if a limited number of departments actually get involved,” KPMG said.

Michael Clementi, vice president of human resources for North America at Unilever PLC, said the key to successfully deploying smart technologies is getting people from across the business to work together.

Unilever recently used an AI-enabled application to identify promising job applicants, replacing a monthslong college-recruiting process.

Rather than lead smart-tech projects, chief executives and other top company officials should identify business problems that need to be solved. Tech and business unit leaders can then get together to assess the ability of smart tools to fix those problems, he said.

“There’s a big conversation constantly about how we can fast-track this technology,” Mr. Clementi said this week at the WSJ Pro Artificial Intelligence Executive Forum.

Write to Angus Loten at angus.loten@wsj.com