A lot of companies are just now starting to create use cases for cognitive technologies and artificial intelligence. A bit ahead of them are those that are staging limited pilot projects. It’s early days, they may be thinking. Why rush now to invest a lot of capital and effort in something with an uncertain payoff?

But many of the companies with real wet feet — those with at least one operating cognitive prototype or full-scale implementation — don’t think they have a lot of time to waste in ramping up their volume of AI usage.

Indeed, why would they want to delay? They’re already seeing an impressive return on investment.

All of that is according to Deloitte’s second annual “State of AI in the Enterprise” report.

The firm surveyed 1,100 line-of-business and IT executives at companies within the above parameters. All were required to be knowledgeable about their company’s use of AI and cognitive technologies. (For purposes of the report, Deloitte considered those two terms to be synonymous.)

Nine of 10 of the participants have direct involvement in their company’s AI strategy, spending, implementation, and/or decision-making.

Just 11% of these early adopters said that implementing AI is of “critical strategic importance” today. But 42% believe it will be so two years from now. “That’s a small window for [these] companies to hone their AI strategies and skills, and they believe their success depends upon getting it right,” Deloitte wrote.

At the same time, though, these executives are becoming more realistic about the time required to accomplish this aim. In the survey, 56% of respondents said cognitive technologies would transform their companies within three years. That was well down from 76% in Deloitte’s 2017 survey.

Already, however, 64% of those surveyed said their adoption of AI is giving their companies a competitive advantage. The rest said adopting AI has allowed them to either catch up to or stay on par with competitors.

And 83% of participants said their use of the technologies — specifically, machine learning, deep learning, natural language processing, and computer vision — is generating either “moderate” or “substantial” benefits.

Here are definitions of those technologies, according to Deloitte:

Machine learning is the ability of statistical models to develop capabilities and improve their performance over time without the need to follow explicitly programmed instructions. Among the survey base, 58% are using it.

Deep learning is a complex form of machine learning involving neural networks, with many layers of abstract variables. Deep learning models are excellent for image and speech recognition. Fifty percent of those surveyed are using the technology.

Natural language processing is the ability to extract or generate meaning and intent from text in a readable, stylistically natural, and grammatically correct form. It powers voice-based virtual assistants and chat-bots and is increasingly used to query data sets. Usage among those surveyed: 53%.

Computer vision is the ability to extract meaning and intent out of visual elements, whether characters or the categorization of such content in images as faces, objects, scenes, and activities. The technology is behind facial recognition applications. Usage: 57% of the survey base.

Slicing and Dicing

One theme that’s evident in this year’s survey is a pullback in the proportion of respondents citing enhancement of current products as being among the top three benefits of using AI (44% of respondents, down from 51%).

That shift is accompanied by an increase in participants’ appreciation for the benefits of applying the technologies toward optimizing internal operations (42% of respondents, up from 36%).

“Operational change is often required before integrating AI into existing products and services can take place,” Deloitte wrote. “Respondents may be realizing they should make operational changes first.”

The interest in and value proposition for AI differs by industry. Unsurprisingly, both the level of investment in AI and the return on that investment is greatest in the technology and telecommunications industries, as well as media and entertainment.

Industrial products and services companies show lower-than-median investment in AI but ROI nearly as high as that for tech and telecom. Conversely, life sciences and health care companies are investing almost as much as tech and telecom but have little to show for it so far.

Sectors below the median level of both investment and return include financial services and consumer products.

Overall, respondents are “enthusiastic about the value cognitive technologies bring,” according to the report. “Their companies are investing in foundational cognitive capabilities and using them with more skill.”

However, Deloitte urged caution with respect to companies self-reported claims of ROI for cognitive technologies.

“Less than 50% of surveyed companies measure key performance indicators necessary for gauging financial returns accurately,” the firm wrote. Such indicators, it added, include project budget/cost, attaining productivity targets, cost savings, revenue, and customer satisfaction/retention.

“This lack of measurement gets to the heart of a significant problem with cognitive implementations: They are often not managed with the same rigor companies use with more mature technologies,” Deloitte observed.

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