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Managing AI and ML in the enterprise 2019: Tech leaders expect more difficulty than previous IT projects

Originally Published:
Mar 2019

Emerging technologies such as Artificial Intelligence (AI) and machine learning (ML) projects are well underway but concerns remain for CXOs regarding these initiatives.

To better understand how enterprises manage their AI/ML projects, Tech Pro Research conducted an online survey in March 2019. According to the survey, 56% of respondents feel implementing AI/ML projects will be more difficult than previous IT projects.

The survey asked the following questions:

  • Who is requesting your AI/ML projects?
  • Who's managing your AI/ML projects?
  • What is your AI/ML project approach?
  • What are your major concerns about implementing an AI/ML project?
  • How would you rate your staff's readiness for implementing and supporting an AI/ML system?
  • What steps are you taking to ensure that your AI/ML projects are successful?
Organizations recognize the value of AI/ML projects, however, they lack confidence in their team's readiness for implementation and management of such projects. For example, more than half of the respondents (53%) said that business users are not clear about what they expect from projects. While 47% of respondents are concerned that IT lacks the AI/ML skills for project implementation and support. Other worries include upper management lacking a good understanding of AI/ML (33%), time and cost overruns (22%), and lack of vendor support (13%).

This certainly introduces a more prominent role for AI/ML vendors and consultants in these initiatives since both IT and end users will seek guidance from outside sources as they learn more about the technology and its benefits.

Due to their lack of confidence, respondents are cautiously approaching their AI/ML initiatives. The majority of respondents (58%) are performing pilot or proofs of concept before full AI/ML implementation. Sixty-four percent of those respondents believe taking such steps will ensure the success of future AI/ML projects.

Other steps respondents are taking to ensure project success include investing in appropriate IT and user training (14%), selecting vendors and consultants with strong expertise in AI/ML (9%) and making sure to have C-level buy-in (5%).

The above concerns make sense when seeing who is asking for AI/ML projects. For example, 33% of respondents said CEOs or other C-suite executives requested the project, 25% said the request came from IT management, 24% said the request came from end business management.

To read all of the results from the survey, plus analysis, download the full report here: Managing AI and ML in the enterprise 2019: Tech leaders expect more difficulty than previous IT projects.

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