The people who build artificial intelligence are the ones who need AI the most

The people who build artificial intelligence are the ones who need AI the most

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There are many interesting 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, who are automating their operations and quality assurance, enabling faster application development, better network optimization, and eliminating manual tasks.

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

The irony, of course, is that the people tasked with developing AI-based 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, requiring higher levels of automation.

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

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 shortages of skills are common. AI helps organizations close skills gaps, for example by automating the tasks of skilled workers or using AI-assisted learning or employee engagement.

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

AI use cases include the following:

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

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

AI transparency is also a concern. Four in five respondents cite being able to explain how their AI arrived at such an important decision for their business. Actions currently taken by IT professionals include protecting data privacy as a measure they take to ensure that their AI is trusted and accountable. A majority of IT professionals say their company relies on more than 20 different data sources to inform their AI, BI, and analytics systems.

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