Enterprises Expect a Two-Year Time Frame for Machine Learning to Go Mainstream
DURHAM, NC AND CAMBRIDGE, UK (JULY 31, 2018) – Enterprises anticipate that machine learning (ML) will permeate and influence the majority of business operations. Over half (52%) of enterprises expect this impact in the next two years, according to a new research study unveiled today by HFS Research in partnership with Infinia ML.
HFS’ new report, “How to Avoid Your Looming Machine Learning Crisis,” finds that enterprise decision makers do not consider machine learning to be an “over-hyped” technology, with only 29% believing it is overrated. On the contrary, the majority of leaders (86%) believe machine learning is impacting their respective industries. As machine learning takes centre stage in boardroom discussions, the C-Suite downward view ML as the here-and-now disruptive technology that will help them compete in the digital age.
While many enterprises have started down the machine learning path, the study finds that the speed and intensity with which organizations are developing capabilities does not match the importance they place upon machine learning. The survey covers 153 data science decision makers across the Global 2000 and finds that business leaders getting started with ML face challenges in multiple dimensions as they move from a few projects to a more robust ML function. Most enterprises have yet to make significant investments in ML (84% investing under $1M), have decentralized practices (8% have centralized ML functions), are mostly running a few projects (65% are running 1 to 3 ML initiatives), and believe that of those projects, only a fraction might deliver business impact.
Further, talent is emerging as a key challenge; 42% already recognize they have significant skill deficiencies, particularly when shifting from traditional IT to ML and data science skills. HFS anticipates that many enterprises have not fully discovered how acute these skills gaps are, but will as ML needs increase over time. You can find answers to these challenges in the “HFS ML Execution Guide," included in the HFS and Infinia ML report, designed to help business leaders get started with ML, deliver value over time, develop more robust capabilities, and ultimately, build industrialized, ML-enabled operations.
“Over three quarters of the report's respondents expressed optimism about the business value of machine learning, but over half agreed that a growing number of ML ‘experts’ are just capitalizing on industry hype,” noted Robbie Allen, CEO of Infinia ML. “Clearly, the future belongs to those who can separate hype from reality and take practical steps to implement machine learning, and that's what we do.”
Report author Reetika Fleming, Research Director of Smart Analytics and AI at HFS, shared that “HFS research highlights the rising prominence of machine learning as an enterprise capability, juxtaposed with the surfacing challenges surrounding ML development itself. Enterprises must address data modernization and ML talent development above all if they are to meet their two-year time to impact.”
Phil Fersht, CEO and Chief Analyst at HFS and co-author of the report, added, “Enterprises need to anticipate customer needs before they happen, which means having unattended and attended interactions with data sources both inside and outside of the enterprise. We must develop robust machine learning capabilities to deliver on this promise, to become connected, interactive enterprises in the near future.”
The complimentary report is available now.
About HFS Research
HFS’ mission is to provide visionary insight into major innovations impacting business operations, including: automation, artificial intelligence, blockchain, digital business models, and smart analytics.
We focus on the future of operations across key industries. We influence the strategies of enterprise customers to develop operational backbones to stay competitive and partner with capable services providers, technology suppliers, and third-party advisors.
About Infinia ML
Infinia ML is a team of advanced machine learning experts helping enterprise clients reduce costs, increase efficiency, and achieve breakthroughs. Infinia ML serves industries from manufacturing and healthcare to marketing and human resources. The company's capabilities include natural language processing, recommendation engines, object detection, 3D image modeling, and anomaly detection.
The company is led by CEO Robbie Allen, an experienced AI entrepreneur, Chief Scientist Lawrence Carin, Ph.D., one of the world's most published machine learning experts and Duke University's Vice Provost for Research, and Executive Chairman and Carrick Capital Partners Managing Director Mike Salvino. Together, the Infinia ML team has produced 31 patents, 11 books, 7 Ph.D.s, and more than 575 published papers.
Learn more at InfiniaML.com