Special Feature
Part of a ZDNet Special Feature: Managing AI and ML in the Enterprise

Survey: Tech leaders cautiously approach artificial intelligence and machine learning projects

A recent Tech Pro Research poll found that most respondents feel their AI/ML projects will be more difficult than previous IT projects.

Siloed IT teams hinder AI and automation deployment Survey finds things slow-going for AI and robotic process automation.

Special Feature

Special Feature: Managing AI and ML in the Enterprise

This ebook, based on the latest ZDNet / TechRepublic special feature, advises CXOs on how to approach AI and ML initiatives, figure out where the data science team fits in, and what algorithms to buy versus build.

Read More

Enthusiasm for artificial intelligence (AI) and machine learning (ML) remains steady for 2019. However, tech leaders admit some trepidation in terms of AI/ML project management and support. How companies manage their AI/ML projects was the topic of a recent survey by ZDNet's premium sister site, Tech Pro Research.

Overall, survey respondents said that their AI/ML projects will be more difficult than previous IT projects. Respondents cited a lack of staff readiness for implementing and supporting an AI/ML system as a cause for concern. More specifically, 38 percent of respondents said that their company employs insufficient technical personnel who can develop applications for, and support, an AI/ML environment, while 22 percent said that business analysts could use more experience defining system requirements and work with end users. Another worry (for 14% of respondents) was system programmers and architects lacking experience in integrating AI/ML applicants with existing infrastructure. Training end users and modifying business processes caused unease for 13 percent of respondents, while only 8 percent felt that their IT staff were up to the task of managing AI/ML projects.

SEE: Special report: Managing AI and ML in the enterprise (free PDF) 

Staff readiness wasn't the only concern respondents noted about imminent AI/ML projects. More than half of respondents (53%) remain uncertain about the business value of AI/ML. Echoing these sentiments, 47 percent of respondents worry that IT lacks necessary AI/ML skills for implementation and support. Further, 33 percent expressed apprehension that upper management won't stay committed to AI/ML projects. Time and cost overruns and insufficient vendor support rounded out the list of respondents' concerns. This makes sense, because AI and ML are emerging technologies. Identifying and implementing business opportunities for AI/ML will increase once organizations gain more confidence in their AI/ML management and support skills.

Interestingly, 6 percent of respondents thought that their AI/ML projects would be less difficult than previous projects, and expressed no hesitation about AI/ML project execution or support.

IT leadership is driving AI/ML projects. Respondents cited project requests originating from the offices of the CEO or other C-suite executives (33%), IT management (25%), and end business management (24%). While C-level, end-business managers, and IT managers will promote AI/ML, IT will lead the deployment and support of AI/ML projects.

To combat impending difficulties with AI/ML projects, more than half of the survey respondents are performing small pilot projects and proofs of concept before full implementation. This approach allows organizations to try out a solution before enabling it, which ultimately, will protect the investment. The more comfortable organizations become with AI/ML initiatives, the more likely they will pursue additional projects.

The infographic below contains selected details from the research. To read more findings, plus analysis, download the full report: Special report: Managing AI and ML in the enterprise (free PDF) .

aimachinelearning-infographic-final-1.jpg

Also see