AI’s time has finally come, if a new survey commissioned by ServiceNow is to be believed. Its results showed that nearly 90 percent of CIOs are at least dabbling with machine learning, with 53 percent calling it an area of strategic focus for their companies. What’s more, almost 70 percent of the CIOs surveyed say decisions made by machines will soon be more accurate than those made by humans.
The new survey was conducted by Oxford Economics on behalf of IT and enterprise software-as-a-service vendor ServiceNow. The survey, titled “The Global CIO Point of View,” was completed by 500 CIOs in 11 countries across 25 industries.
The report also fits neatly with evidence from other sources that CIOs are in charge of digital transformation. Just under 75 percent say they lead their company’s efforts to gear up for full-fledged digital business. Business intelligence derived from data analytics has always been a pillar of digital transformation. But with some 85 percent of CIOs reporting that machine learning provided “substantial value” or “transformative value” to the accuracy as well as rapidity of decisions, it’s beginning to change the way some organizations operate, according to the report.
Within three years, two-thirds of the respondents expect to be making an investment in machine learning. Today, one-third are investing. The size of spend as a percentage of the overall IT budget is relatively modest, however: something like 5 percent for machine learning.
One of the reasons for the move to machine learning is that sometimes you just have to do things smarter. “We were heading to a tipping point almost where there was just so much work coming in,” said Dave Wright, chief innovation officer, ServiceNow, talking about IT shops. “There was just so much work coming in; the workload just continued to increase year over year. CIOs want to know, ‘How do I get to the point where I can deal with this, because I can’t constantly throw heads at it.'” That’s why the report advises that companies direct their early machine learning efforts at the most commonly used services, freeing resources for more rewarding efforts.
Machine Learning’s Obstacles Aren’t What You Think
Machine learning technology has matured so much in recent years that it’s no longer the prime obstacle for CIOs. Instead the challenges are outdated business processes, incomplete insufficient skill sets, lack of quality data, insufficient data sources, risk assessment conflicts and budget limitations. When data is siloed across the company, accessing all the right data for the best decision-making is not always easy or possible. There’s also some inertia built into the organizational structures of most companies; the notion of making business decisions based on machine learning (a.k.a. “decision automation”) may require some handholding, for example. Technology is not the problem.
Early adopters to machine learning, which represent just under 10 percent of the survey sample, share some characteristics and ways of doing things: They prioritize talent. They are working on better business processes and have a road map for future changes developed by monitoring mistakes made by machines. The road map is also guided by the need to implement policies and processes that improve data quality. They have strong technology foundations, with an emphasis on data analytics, cloud, mobile and IoT. And they expect results. Nearly 90 percent of this 10 percent of early adopters expect decision automation to support topline growth.
What may be more interesting is that, of the other 90 percent of the CIO respondents, nearly 70 percent expect to develop revenue from machine learning. Looking at the data behind this report, the CIOs who’ve gotten their feet wet with machine learning are very excited by its prospects.
The report outlines five steps to achieve value from machine learning that are worth a quick summary:
- Build your technical foundation so as to improve data quality. Successful companies had already invested significantly in analytics, for example.
- Prioritize automation of the most common business use cases; they will return the greatest business benefit.
- Build an exceptional customer experience. If customers see the man behind the curtain in a machine learning-based tool, it may become a very negative experience for them. Spend extra time making the entire customer journey seamless.
- Attract employees with new skills and double down on culture.
- Measure and report. The benefits of machine learning may not be obvious to all. CIOs must set expectations, develop success metrics and build a sound business case to acquire funding. Build some success stories.
