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Blockchain Is Transforming Cyber Security

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Blockchain Is Transforming Cyber Security Introduction Computer technology and the internet have disrupted the old way of doing business. New revenue streams continue to come up, and business models of yesteryears are all but forgotten. But these changes are not without a price; technology introduces

Machine Learning’s Greatest Potential

  • Enterprise investments in machine learning will nearly double over the next three years, reaching 64% adoption by 2020.
  • International Data Corporation (IDC) is forecasting spending on artificial intelligence (AI) and machine learning will grow from $8B in 2016 to $47B by 2020.
  • 89% of CIOs are either planning to use or are using machine learning in their organizations today.
  • 53% of CIOs say machine learning is one of their core priorities as their role expands from traditional IT operations management to business strategists.
  • CIOs are struggling to find the skills they need to build their machine learning models today, especially in financial services.

These and many other insights are from the recently published study, Global CIO Point of View. The entire report is downloadable here (PDF, 24 pp., no opt-in). ServiceNow and Oxford Economics collaborated on this survey of 500 CIOs in 11 countries on three continents, spanning 25 industries. In addition to the CIO interviews, leading experts in machine learning and its impact on enterprise performance contributed to the study. For additional details on the methodology, please see page 4 of the study and an online description of the CIO Survey Methodology here.

Digital transformation is a cornerstone of machine learning adoption. 72% of CIOs have responsibility for digital transformation initiatives that drive machine learning adoption. The survey found that the greater the level of digital transformation success, the more likely machine learning-based programs and strategies would succeed. IDC predicts that 40% of digital transformation initiatives will be supported by machine learning and artificial intelligence by 2019.

Key takeaways from the study include the following:

  • 90% of CIOs championing machine learning in their organizations today expect improved decision support that drives greater topline revenue growth. CIOs who are early adopters are most likely to pilot, evaluate and integrate machine learning into their enterprises when there is a clear connection to driving business results. Many CIO compensation plans now include business growth and revenue goals, making the revenue potential of new technologies a high priority.
  • 89% of CIOs are either planning to use or using machine learning in their organizations today. The majority, 40%, are in the research and planning phases of deployment, with an additional 26% piloting machine learning. 20% are using machine learning in some areas of their business, and 3% have successfully deployed enterprise-wide. The following graphic shows the percentage of respondents by stage of their machine learning journey.

  • Machine learning is a key supporting technology leading the majority Finance, Sales & Marketing, and Operations Management decisions today. Human intervention is still required across the spectrum of decision-making areas including Security Operations, Customer Management, Call Center Management, Operations Management, Finance and Sales & Marketing. The study predicts that by 2020, machine learning apps will have automated 70% of Security Operations queries and 30% of Customer Management ones.

  • Automation of repetitive tasks (68%), making complex decisions (54%) and recognizing data patterns (40%) are the top three most important capabilities CIOs of machine learning CIOs are most interested in.  Establishing links between events and supervised learning (both 32%), making predictions (31%) and assisting in making basic decisions (18%) are additional capabilities CIOs are looking for machine learning to accelerate. In financial services, machine learning apps are reviewing loan documents, sorting applications to broad parameters, and approving loans faster than had been possible before.
  • Machine learning adoption and confidence by CIOs varies by region, with North America in the lead (72%) followed by Asia-Pacific (61%). Just over half of European CIOs (58%) expect value from machine learning and decision automation to their company’s overall strategy. North American CIOs are more likely than others to expect value from machine learning and decision automation across a range of business areas, including overall strategy (72%, vs. 61% in Asia Pacific and 58% in Europe). North American CIOs also expect greater results from sales and marketing (63%, vs. 47% Asia-Pacific and 38% in Europe); procurement (50%, vs. 34% in Asia-Pacific and 34% in Europe); and product development (48%, vs. 29% in Asia-Pacific and 29% in Europe).
  • CIOs challenging the status quo of their organization’s analytics direction are more likely to rely on roadmaps for defining and selling their vision of machine learning’s revenue contributions. More than 70% of early adopter CIOs have developed a roadmap for future business process changes compared with just 33% of average CIOs. Of the CIOs and senior management teams in financial services, the majority are looking at how machine learning can increase customer satisfaction, lifetime customer value, improving revenue growth. 53% of CIOs from our survey say machine learning is one of their core priorities as their role expands from traditional IT operations to business-wide strategy.

By Louis Columbus

Louis Columbus

I am currently serving as Director, Global Cloud Product Management at Ingram Cloud. Previous positions include product marketing at iBASEt, Plex Systems, senior analyst at AMR Research (now Gartner), marketing and business development at Cincom Systems, Ingram Micro, a SaaS start-up and at hardware companies. I am also a member of the Enterprise Irregulars. My background includes marketing, product management, sales and industry analyst roles in the enterprise software and IT industries. My academic background includes an MBA from Pepperdine University and completion of the Strategic Marketing Management Program at the Stanford University Graduate School of Business. I teach MBA courses in international business, global competitive strategies, international market research, and capstone courses in strategic planning and market research. I've taught at California State University, Fullerton: University of California, Irvine; Marymount University, and Webster University. You can reach me on Twitter at @LouisColumbus.

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