Almost Half of All Companies Have Deployed Machine Learning

If you're concerned (or super excited) about machine learning (ML) condign mainstream, a recent survey by Oxford Economics on behalf of human resources (60 minutes) and IT nugget management company ServiceNow should pique your interest. The report, which surveyed 500 Principal Information Officers (CIOs) in 11 countries and across 25 industries, found that 49 pct of the companies are already using ML to improve traditional business processes.

Of the 500 CIOs surveyed, 200 said they're already beyond the pilot stage and have begun deploying ML in some capacity. CIOs are hoping to limit user error and errors in judgement by introducing automation. Almost 70 percent of CIOs said decisions made by machines volition be more than accurate than those made by humans. According to the survey, CIOs today are primarily focused on using ML to automate repetitive tasks (68 percent), make complex decisions (54 pct), recognize data patterns (40 percent), and establish links between events (32 percent).

"One of the reasons you're hearing so much near ML is that it'southward the wave of productivity that will divide companies from the contest," said Chris Bedi, CIO at ServiceNow. "It's faster and offers [the potential for] better decisions. Humans take biases, algorithms don't."

Bedi said he sees huge potential for ML in industries such as enterprise resource planning (ERP), inventory direction and supply chain, among many others. Forty-1 percent of CIOs in the survey cited a lack of skills every bit the main event stopping them from deploying ML today. Conversely, but 16 per centum of CIOs and their companies accept plans for workforce size and role changes to suit ML.

(Image Via: ServiceNow)

ML and Jobs

The numbers released in the Oxford Economics survey are curt-term projections, unlike a report past management consulting firm McKinsey & Visitor. Their report projected that half of today'southward work activities could be replaced by automation from 2035-2055, depending on diverse factors. The firm's study analyzed 2,000 work activities across 800 occupations and found that virtually $2.seven trillion in wages are spent on jobs that could ultimately be automated.

"ML will modify people's roles," said Bedi. "I don't subscribe to ML taking abroad people'due south jobs; information technology volition change people's jobs. Mundane decisions will go automated, which will free people up. New jobs will become created."

Bedi said the primal to leveraging ML to improve the bottom line while maintaining the rank and file is shifting current employee skill sets and hiring new talent to manage ML capabilities. "Talent is a big issue," said Bedi. "Data Scientist has got to be one of the hottest jobs out there. Nosotros really demand to wait at what is our 3-twelvemonth talent and skill road map? And be really purposeful about building those skills. We've got to train employees but also figure out culling sources to that talent."

Bedi urged employers to rent and train employees to take advantage of ML-based processes. Once humans are comfortable with ML'southward ability to produce reliable data and make correct decisions, he said the industry volition transition [to] automobile conclusion making guided by human oversight.

(Image Via: ServiceNow)

The Late Adopter Dilemma

The Oxford Economics survey isolated fifty companies that were deemed "First Movers." The survey studied these companies' business processes and talent strategies to determine how and where ML would be advanced in the coming years. The report establish that First Movers are more likely to have redefined job descriptions to focus on how humans work with machines, and take made plans to develop specialized teams focused on developing and using ML technology. Unlike their peers, these companies are more likely to have developed route maps for future processes, capturing errors and ensuring data accuracy.

Unfortunately, other reports indicate that the smaller the organisation (and the fewer resources an system has), the less probable it is to exist prepared for the ML wave. A recent study past Bluewolf (an IBM company) constitute that only 33 percent of pocket-sized businesses planned to invest in artificial intelligence (AI) and ML within the next 12 months. This is in contrast to the 30 percent of large companies that have already invested in the technologies and the 44 percentage that planned to begin investing within the next 12 months. That's a total of 74 percent, or 20 percent more the total of small-scale businesses.

"We're early in the journeying," said Bedi. "People and companies that are ambitious will separate themselves from the companies that aren't. Information technology feels like there's a call-to-activeness to become do this. Companies that lean in are going to starting time to separate themselves from the competition. That separation volition increase. CIOs will really beginning pushing on this in the near future."

Source: https://sea.pcmag.com/feature/17875/almost-half-of-all-companies-have-deployed-machine-learning

Posted by: brustbronds.blogspot.com

Share this post