Dive Brief:
- Nearly one-third of enterprises are investing upwards of $50 million in intelligent automation (IA) solutions, which includes artificial intelligence, machine learning, cognitive computing and robotic process automation, according to a KPMG survey of almost 600 international business leaders.
- However, investments in IA technologies are stalled by "splintered" strategies when it comes to putting them into practice, according to the report. More than 60% of enterprises use IA solutions, yet just 11% leverage an integrated solution approach.
- Nearly one-third of companies expect adoption of IA to be scaled and industrialized at the functional level in the next year whereas 39% say it is already there. The enterprise level is a bit slower, with only 22% having scaled and industrialized IA adoption.
Dive Insight:
The technologies that sit under the IA umbrella are having a moment across every industry.
By 2018, RPA became a common phrase executives threw around in earnings calls, but just as KPMG reported, scaling is weak. The interest in automated solutions come not to replace workers with physical robots, but alleviate the labor that goes into repetitive tasks.
Automation stands to cut global workforce costs by $2 trillion as companies become more efficient. Companies like Pinterest are looking for their AI implementations to start small, with primary focus on storing and analyzing the right user data on the platform.
Understanding what customers want is primary. The restaurant industry is accomplishing this with mobile platforms. TGI Fridays is using IA solutions, integrating AI on platforms and through email campaigns, bots on social media, and Amazon’s Alexa.
But TGI Fridays also relies on a strategy most companies need before investing in a technology that has little return — trial and error. It led the company to create a personalized cocktail platform equipped with a virtual bartender named Flanagan to craft custom beverages.
Walmart is also using the solutions and proving to have a strong ROI track record.
The retailer sought the technology to cut costs related to back-office systems and to allow reinvesting the savings into the front end. The retailer began its AI use case by demonstrating the technology’s ability to impact commodity processes in the back office.
