CIOs Cutting Through the Hype and Delivering Real Value from Machine Learning, Survey Shows 

New survey reveals progressive CIOs tap machine learning to solve everyday work problems

SANTA CLARA, Calif. – October 17, 2017– A survey of 500 Chief Information Officers (CIOs) from around the world by ServiceNow (NYSE:NOW) finds that machine learning has arrived in the enterprise making material contributions to everyday work.  To realize its full value, technology leaders must find skilled talent to work side-by-side with machines in addition to redesign their organizations and processes.

For “The Global CIO Point of View,” ServiceNow surveyed CIOs in 11 countries across 25 industries to uncover the competitive benefits of adopting machine learning and hear how those leaders are driving results. IDC estimates that investment in machine learning will nearly double by 2020,* and recent analysis shows that machine learning specialist are among the fast growing roles in IT.**

Humans Work Side-by-Side with Smart Machines for Better Accuracy, Speed and Growth of Business

The survey finds a growing sense of confidence among senior executives that machine learning will lead to faster and more accurate decisions. Machine learning software possesses the ability to analyze and improve upon its own performance without direct human intervention, allowing them to make increasingly complex decisions over time:

  • More than half (52%) of respondents say they are advancing beyond the automation of routine tasks, such as security alerts, toward the automation of complex decisions, such as how to respond to alerts.
  • 87% said that they would get value from the accuracy of decisions.  In fact, 69% say decisions made by machine learning will be more accurate than those made by humans.
  • 57% said that routine decision making takes up a meaningful amount of employee and executive time, so the potential value of automation is high. CIOs expect this decision automation to contribute to their organization’s top line growth (69%).

“We see three kinds of processes as targets for machine learning—anything requiring rating, ranking or forecasting,” said Chris Bedi, CIO at ServiceNow. “Everyday work such as the assignment of IT tickets and prioritizing sales leads are already delivering results. Machine learning has rapidly moved from hype to reality.”

Machine Learning Specialists Alone Won’t Help CIOs Succeed in Digital Transformation

Nearly three-quarters (72%) of CIOs surveyed said they are leading their company’s digitalization efforts, and more than half (52%) agree that machine learning plays a critical role. Nearly half (49%) of the CIOs surveyed say their companies are using machine learning and 40% are planning to adopt the technology.

But there are key talent, organization and process areas that must be addressed in order for companies to take full advantage of machine learning technology:

  • Only 27% of CIOs have hired employees with new skill sets to work with intelligent machines.
  • Fewer than half (40%) of CIOs have redefined job descriptions to focus on work with intelligent machines, 41% cite a lack of skills to manage intelligent machines and about half (47%) say they lack budget for new skills development.
  • CIOs cite data quality (51%) and outdated processes (48%) as substantial barriers to adoption.
  • Fewer than half (45%) have developed methods for monitoring mistakes made by machines.

“Machine learning allows enterprises to digitize in ways that were not possible before,” Bedi said. “To realize the full potential of machine learning technology, CIOs must elevate their role to be transformational leaders who influence how our organizations design business processes, leverage data, and hire and train talent.”

First-Mover CIO Advantages – Delivering Results Today

A select group of CIOs surveyed (fewer than 10%) are running ahead of their peers in the use of machine learning. These “first movers” provide a model for how CIOs can better utilize machine learning:

  • Almost 90% of first movers expect decision automation to support top-line growth vs. 67% of others.
  • Roughly 80% have developed methods to monitor machine-made mistakes vs. 41% of others.
  • More than three-quarters have redesigned job descriptions to focus on work with machines compared with 35% of others.
  • More than 70% have developed a roadmap for future business process changes compared with just 33% of others.

“First-mover CIOs who combine machine learning with new business processes and skillsets will better support their enterprise growth,” Bedi said. “They report higher levels of maturity in the use of leading platforms, which allows them to concentrate on innovation, such as automating complex decision-making, which immediately impacts the bottomline.”

Financial Services Leads, Healthcare Industry Lags

The survey uncovered viewpoints from CIOs in the financial services and healthcare sectors. Of note:

  • CIOs from financial services are more likely to say their company is moving from the automation of simple decisions to the automation of increasingly complex decisions (68%, vs. 52% of others). They are more likely to have made organizational changes to accommodate digital labor, including redefining job descriptions to focus on work with machines (62% vs. 36%), developing a roadmap for future process changes (52% vs. 35%), and recruiting employees with new skill sets (42% vs. 25%)
  • CIOs in the healthcare industry remain cautious. They are less likely to use machine learning across the organization and less likely to say the technology will have a positive impact on top-line growth, competitiveness, or reducing risk. They are lesslikely to expect value from decision automation in a number of functional areas, including security (70% vs. 80%), operations (46% vs. 58%), risk and compliance (36% vs. 58%).

Five Steps to Achieve Value from Machine Learning

ServiceNow recommends how CIOs can jump start their journey to digital transformation with machine learning:

1)     Build the foundation and improve data quality –One of the top barriers to machine learning adoption is the quality of data. If machines make decisions based on poor data, the results will not provide value and could increase risk. CIOs must utilize technologies that will simplify data maintenance and the transition to machine learning.

2)     Prioritize based on value realization –When building a roadmap, focus on those services that are most commonly used, as automating these services will deliver the greatest business benefits. At a high level, where are the most unstructured work patterns that would benefit from automation? Commit to re-engineering services and processes as part of this transformation, and not simply lifting and shifting current processes into a new model.

3)     Build an exceptional customer experience –A core benefit of increasing the speed and accuracy of decision-making lies in creating an exceptional internal and external customer experience. When creating a roadmap to implement machine learning capabilities, imagine the ideal customer experience and prioritize investment against those goals.

4)     Attract new skills and double down on culture –CIOs must identify the roles of the future and anticipate how employees will engage with machines—and start hiring and training in advance. CIOs must build a culture that embraces a new working model and skills. That means establishing guidelines for executives, engineers, and front- line workers about their work with machines and the future of human-machine collaboration.

5)     Measure and report –The benefits of machine learning may be clear
to CIOs, but other C-level executives and corporate boards often need to be educated on its value. CIOs must set expectations, develop success metrics prior to implementation, and build a sound business case in order to acquire and maintain the requisite funding. CIOs should also consider building automated benchmarks against peers in their industry and other companies that are of similar size.

ServiceNow applies machine learning to four of the biggest use cases that IT has today. Preventing outages, categorizing and routing work, predicting future performance, and benchmarking performance against peers are examples of everyday work ServiceNow automates in leading enterprises.

Survey Methodology

ServiceNow commissioned Oxford Economics to survey 500 CIOs about machine learning and automated decision-making. Respondents are based in Austria, Australia, France, Germany, the Netherlands, New Zealand, Singapore, Sweden, the United Kingdom and the United States, and represent a broad range of B2B and B2C sectors. The survey was administered via Computer-Assisted Telephone Interviews (CATI). Founded in 1981 as a joint venture with Oxford University’s business college, Oxford Economics specializes in evidence-based thought leadership, forecasting, and economic impact analysis.

*Worldwide Semiannual Cognitive/Artificial Intelligence Systems Spending Guide, IDC, October 2016. Spending on artificial intelligence and machine learning is expected to grow rapidly from less than $8 billion in 2016 to $47 billion by 2020, according to IDC.


About ServiceNow

ServiceNow makes work better across the enterprise.  Getting simple stuff done at work can be easy, and getting complex multi-step tasks completed can be painless.  Our applications automate, predict, digitize and optimize business processes and tasks, from IT to Customer Service to Security Operations and to Human Resources, creating a better experience for your employees, users and customers while transforming your enterprise.  ServiceNow (NYSE:NOW) is how work gets done.  For more information, visit:


The latest in curated technology related news collected from many of the leading news distribution, industry research and technology vendor firms on the planet.

Here you will find recent news sources from companies such as Reuters, Marketwired, IDC, Gartner or directly from cloud vendors such as Google, Microsoft or Amazon.

How to Start Incorporating Machine Learning in Enterprises

How to Start Incorporating Machine Learning in Enterprises

Incorporating Machine Learning in Enterprises The world is long past the Industrial Revolution, and now we are experiencing an era ...
Looking to 2018 and the Future: Do You Think We Are Entering a 4th Turn or 5th Wave?

Looking to 2018 and the Future: Do You Think We Are Entering a 4th Turn or 5th Wave?

2018 and the Future Wow! 2017 sure was something. Looking ahead do you see darkness – the 4th turn – or ...
Gartner’s Hype Cycle for Emerging Technologies, 2017 Adds 5G, Edge Computing For First Time

Gartner’s Hype Cycle for Emerging Technologies, 2017 Adds 5G, Edge Computing For First Time

Gartner’s Hype Cycle for Emerging Technologies Gartner added eight new technologies to the Hype Cycle this year including 5G, Artificial ...
3 Ways to Protect Users From Ransomware With the Cloud

3 Ways to Protect Users From Ransomware With the Cloud

Protect Users From Ransomware The threat of ransomware came into sharp focus over the course of 2016. Cybersecurity trackers have ...
What’s Next In Cloud And Data Security For 2017?

What’s Next In Cloud And Data Security For 2017?

Cloud and Data Security It has been a tumultuous year in data privacy to say the least – we’ve had ...
Safeguarding Data Before Disaster Strikes

Safeguarding Data Before Disaster Strikes

Safeguarding Data  Online data backup is one of the best methods for businesses of all sizes to replicate their data ...
Cloud Computing Certification Courses

AWS S3 Outage & Lessons in Tech Responsibility From Smokey the Bear

AWS S3 Outage & Lessons in Tech Responsibility Earlier this week, AWS S3 had to fight its way back to ...
IoT Trends

The Internet of Attacks: Disturbing Online IoT Trends

Disturbing Online IoT Trends If you thought the worst thing to come out of the Internet of Things (IoT) trend ...
State of the Cloud Report In 2017

State of the Cloud Report In 2017

Cloud Report 2017 As the definitive guide to the biggest trends in the cloud industry, this year’s “State of the ...
What Does The Transition To New Energy Teach Us About Cloud?

What Does The Transition To New Energy Teach Us About Cloud?

New Energy Shift CIOs report that private cloud is all the rage now. The Cisco’s of the world argue that ...