The people who build AI are also the people who need it the most

There are many exciting use cases for artificial intelligence, from drug discovery to autonomous transportation. But the people reaping the most benefits from AI technologies to date are the technologists themselves – automating their operations and quality assurance, enabling faster application development, greater network optimization, and by eliminating manual tasks.

That’s according to a recent survey of 7,502 IT executives and professionals worldwide, commissioned by IBM’s Watson Group. Overall, 35% of companies report using AI in their business, up from 31% a year ago, and 42% are exploring the technology. AI is applied through out-of-the-box solutions, such as virtual assistants, and it is integrated into existing business operations, including IT processes.

The irony, of course, is that the people tasked with building AI-powered applications and systems — IT teams — need AI the most to support their efforts. This is not entirely surprising, as the development and implementation of AI makes things much more complex and requires higher levels of automation.

Remedy for the shortage of workers

About half of organizations see benefits from using AI to automate IT, business or network processes, including cost savings and efficiencies (54%), IT or network performance improvements (53%) and better customer experiences (48%).

Additionally, 30% of IT professionals say their organization’s employees are saving time with new AI and automation software and tools, especially in areas such as IT itself – where skills shortages are common. AI helps organizations address skills shortages, for example by automating tasks for skilled workers, or using AI-assisted learning or employee engagement.

The most advanced adoption of AI is occurring in areas such as IT operations, security and threat detection, and business process automation. A third of companies are already using AI to automate their IT processes (AIOps) which helps preserve application performance while making resource allocation more efficient. The majority of IT professionals in large enterprises use it to improve the efficiency of IT operations (ITOps) (54%), compared to only 40% in small enterprises.

In summary, the use cases for AI are:

  • Automation of IT operations 32%;
  • Automation of IT or software asset management 32%;
  • Activity monitoring 29%;
  • Automation of customer service experiences 28%;
  • Automation of business workflows 27%;
  • Real-time inventory management 26%;
  • 5G service 25;
  • Supply chain efficiency and resilience 24%.

The cost of AI

Top barriers to successful AI adoption by businesses include: limited AI skills, expertise or knowledge (34%), price too high (29%), lack of tools or platforms to develop models (25%), projects that are too complex or difficult to integrate and scale (24%), and excessive data complexity (24%).

AI transparency is also a concern. Four in five respondents cite being able to explain how their AI arrived at a decision as important to their business. Among the measures currently taken by IT professionals, data privacy protection is the measure they take to ensure that their AI is trustworthy and accountable. The majority of IT professionals report that their company taps into more than 20 different data sources to power their AI, BI and analytics systems.


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