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Report: Enterprises Expect Two-Year Timeframe for Machine Learning

Durham, N.C., and Cambridge, UK (Jul 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 by HFS Research in partnership with Infinia ML.

HFS’ new report, “How to Avoid Your Looming Machine Learning Crisis,” finds only 29% of data science decision makers across the Global 2000 believe machine learning is overrated. On the contrary, the majority (86%) believe machine learning is impacting their respective industries.

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 ML. 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. The report addresses these challenges through the “HFS ML Execution Guide,” 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 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. That’s what we do at Infinia ML.”

The complimentary report is available at InfiniaML.com/report.

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


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. Read more.

About Carrick Capital Partners
Who We Are
A firm of enterprise software and technology enabled services investors and operating executives with substantial experience founding, scaling, and optimizing market leading businesses.
Our Approach
We work with management to identify and improve critical areas of their business - focusing on the priorities that align with our experiences and that will deliver the highest strategic impact in both the short-term and long-run.
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We have a concentrated number of companies in our portfolio so that we can build substantial relationships with each management team and ensure our firm's commitment to each company's goals.
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