There are many interesting use cases for artificial intelligence, from drug discovery to autonomous transportation. But the people who have seen the greatest benefits from AI technologies so far are the technologists themselves—automating their operations and quality assurance, enabling faster application development, network optimization, and eliminating manual tasks.
That’s according to a recent survey of 7,502 IT managers and professionals worldwide, commissioned by the IBM Watson Group. Overall, 35% of companies now report using AI in their businesses – up from 31% a year ago – and another 42% are exploring the technology. It is used through off-the-shelf solutions such as virtual assistants and embedded in existing business operations, especially IT processes.
The irony, of course, is that the people tasked with building AI-driven 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 greater levels of automation.
About half of organizations see benefits from using AI to automate IT, business or network processes, including cost savings and efficiency (54%), improved IT or network performance (53%) and a better customer experience (48%).
Another 30% of IT professionals say their organization’s employees are saving time by using new AI and automation software and tools, especially in areas like IT itself – where skills shortages are common. AI helps organizations address skills gaps, for example by automating tasks for skilled workers or using AI-powered learning or employee engagement.
The most advanced implementation of AI is in areas such as IT operations, security and threat detection, and business process automation. One-third of companies are already using AI to automate their IT processes—AIOps that help preserve application performance while making resource allocation more efficient. The majority of IT professionals in large companies use it to increase the efficiency of IT operations (ITOps) (54%), compared to only 40% in smaller companies.
AI use cases include:
- Automation of IT operations 32%
- IT or software asset management automation 32%
- Activity monitoring 29%
- Automation of customer service experience 28%
- Automation of business workflows 27%
- Real-time inventory management 26%
- 5G services 25%
- Supply chain efficiency and resilience 24%
The main obstacles to the successful implementation of AI in companies are limited AI skills, knowledge or expertise (34%), too high a price (29%), lack of tools or platforms for developing models (25%), projects are too complex or difficult to integrate and scale (24% ), and too much data complexity (24%).
AI transparency is also a concern. Four out of five respondents see the ability to explain how their AI made a decision as important to their business. Actions currently taken by IT professionals include protecting data privacy as they exercise their AI reliability and accountability. Most IT professionals report that their company uses more than 20 different data sources to inform their AI, BI and analytics systems.