7 tips for scaling your AI strategy

Now that your enterprise has experimented in AI it’s time to consider how to expand the efforts. Here’s how, according AI visionary Andrew Ng, as well as experts from PwC and Deloitte.

7 tips for scaling your AI strategy
Getty Images
Current Job Listings

Pilot projects of artificial intelligence (AI) technologies proliferated in 2018, as many enterprises tested machine learning (ML) algorithms and an array of automation tools to cement relationships with customers, improve network operations or augment their cybersecurity postures.

Encouraged by early results, CIOs are preparing for the next challenge: scaling AI throughout the enterprise. Twenty percent of 1,000 U.S. business executives said their companies plan to implement AI across their enterprise in 2019, according to new research from PricewaterhouseCoopers (PwC).

Business aspirations are soaring. Companies are investing more in these emerging technologies, as IDC projects spending on cognitive and AI systems will reach $77.6 billion in 2022 — more than three times the $24 billion forecast for 2018.

But no matter how big the aspirations are, the road to scaling AI is fraught with perils such as warring strategies and shifting business priorities that can stifle cross-departmental collaboration. The dearth of talent to handle the technical work compounds the issues.

To continue reading this article register now

How do you compare to your peers? Find out in our 2019 State of the CIO report