Suwin Puengsamrong | Dreamstime
Smart factory concept: Engineer using laptop control with CNC machine in automotive industry.
Smart factory concept: Engineer using laptop control with CNC machine in automotive industry.
Smart factory concept: Engineer using laptop control with CNC machine in automotive industry.
Smart factory concept: Engineer using laptop control with CNC machine in automotive industry.
Smart factory concept: Engineer using laptop control with CNC machine in automotive industry.
Stononame | Dreamstime
Siemens PLC for industrial process control.
Siemens PLC for industrial process control.
Siemens PLC for industrial process control.
Siemens PLC for industrial process control.
Siemens PLC for industrial process control.
Pichaya P | Dreamstime
Worker, technician checking solar cell panel for sustainable manufacturing.
Worker, technician checking solar cell panel for sustainable manufacturing.
Worker, technician checking solar cell panel for sustainable manufacturing.
Worker, technician checking solar cell panel for sustainable manufacturing.
Worker, technician checking solar cell panel for sustainable manufacturing.
Sompong Sriphet | Dreamstime
Smart manufacturing concept photo-illustration. Photo 126723670 © Sompong Sriphet | Dreamstime.com
Smart manufacturing concept photo-illustration. Photo 126723670 © Sompong Sriphet | Dreamstime.com
Smart manufacturing concept photo-illustration. Photo 126723670 © Sompong Sriphet | Dreamstime.com
Smart manufacturing concept photo-illustration. Photo 126723670 © Sompong Sriphet | Dreamstime.com
Smart manufacturing concept photo-illustration. Photo 126723670 © Sompong Sriphet | Dreamstime.com
Komgrit Pradissagul | Dreamstime
Manufacturing data assessment.
Manufacturing data assessment.
Manufacturing data assessment.
Manufacturing data assessment.
Manufacturing data assessment.

90% of Businesses Plan to Invest in AI

Nov. 15, 2019
A global research report finds ERP execs are looking for Artificial Intelligence to improve employee productivity, but "technologies themselves are not a panacea," an expert cautions.

Enterprise software developer IFS released a research study involving 600 ERP executives and managers in a wide variety of business sectors worldwide, revealing that an overwhelming majority — about 90% of the total — have some plans to implement artificial intelligence (AI) in their organizations. Industrial automation us the most likely object of AI investment, for 44.6% of the respondents; customer relationship management (CRM) and inventory planning and logistics shared for the second rank among respondents, at 38.9%.

Asked how they plan to use AI, 60.6% of respondents reported they expect the technology to help current workers to become more productive. Almost half of respondents, 47.9%, said they would use AI to add value to products and services they sell to customers.

About of respondents (18.1%) said they would proactively use AI to replace existing workers.

“AI is no longer an emerging technology. It is being implemented to support business automation in the here and now, as this study clearly proves,” according to Bob De Caux, IFS v.p. of AI and Robotic Process Automation (RPA.)  “We are seeing many real-world examples where technology is augmenting existing decision-making processes by providing users with more timely, accurate, and pertinent information.

“In today’s disruptive economy, the convergence of technologies such as AI, RPA, and IoT is bolstering a new form of business automation that will provide companies that are brave enough with the tools and services they need to be more competitive, and outflank larger competitors.”

One "early adopter" of AI and robotics cited by IFS is Cheer Pack — manufacturing of packaging products: It deployed a fleet of AI-powered autonomous vehicles to robotize material movements in its U.S. factory.

“We expect the costs savings to be over $1.5 million/year,” offered Cheer Pack’s IT director, Alex Ivkovic. “In addition, each and every employee will be re-tasked to a higher-skilled position, helping us with our labor shortage.”

De Caux concluded that the study and real-world examples indicate that “the time is right for companies to reap both business and financial benefits from technology automation. Falling for the hype of AI is easy, but success requires disruption to existing business models. The technologies themselves are not a panacea, nor are they a universal solution to any problem.”

He added, “with the right data model and viable use cases, AI can support improved productivity and deliver significant benefits to both operations and the wider business.”

The full study is available for download.