Lack of expertise and buy-in, not enthusiasm, holding back organizational AI deployments
O’Reilly, a company that delivers knowledge and training for technology-driven transformation, has revealed the results of its 2019 artificial intelligence survey, “AI Adoption in the Enterprise.” The results, similar to those of the company’s inaugural study last year, show that corporate culture and a skills gap are the main barriers to AI implementation.
The Lowdown: According to the O’Reilly survey, interest in AI remains strong among enterprises, but many lack the AI and/or machine learning expertise they need to deploy viable solutions.
Some notable findings of the study:
• Roughly eight out of 10 respondents (81 percent) work for organizations that already use AI; more than 60 percent work for organizations that plan to spend at least 5 percent of their IT budget on AI in the next 12 months; and 19 percent work for organizations that plan to spend at least 20 percent of their IT budget on AI.
• Almost one-quarter of respondents (23 percent) cited “company culture” as a key factor slowing down AI implementations. Other high-ranking factors include a “lack of skilled people” (18 percent) and “difficulties identifying use cases” (17 percent).
• More than half of all respondents indicated that their organizations are in need of machine learning experts and data scientists.
• AI spending levels depend on organizational maturity. Companies with mature practices plan to spend on AI at a much higher rate than less mature companies.
• Half of all respondents belong to organizations that use AI for R&D projects, while one-third use it for customer service or IT.
• More than half of all respondents (53 percent) applying deep learning use it for computer vision applications, but many more use it for “enterprise data,” including unstructured data (86 percent) and text (69 percent).
The Buzz: “AI maturity and usage in the enterprise has grown exponentially over the past year, and there are no signs of that slowing down,” said Ben Lorica, chief data scientist at O’Reilly, Sebastopol, California. “Mature organizations with plans to spend on AI tools that hire talent to identify use cases that fit those AI solutions will succeed, but for those less-mature companies with a lack of investment in AI, we expect the gap between leaders and laggards will only widen.”
Channelnomics Point of View: As organizations uncover more ways to apply emerging technologies such as AI to improve business outcomes, finding people with the requisite skill sets will become more critical still. Solution providers can play an important role in helping companies fill gaps in expertise and experience.