2018 Will Mark the Beginning of AI Democratization

Advances in virtual assistants and deep learning will foster adoption of artificial intelligence.

Artificial intelligence (AI) is poised take a prominent place within organizations in 2018, and the coming year will mark the beginning of the democratization of AI. In other words, a much broader range of companies and government departments will use AI.

“Throughout 2018, AI performance will continue to improve,” says Chirag Dekate, research director at Gartner. “The increased availability of AI capabilities embedded in applications and platforms like cloud office suites and deep neural network (DNN)-based virtual assistants, such as Alexa and Siri, will boost intelligent conversational interfaces to products and services.”

CIOs view making progress with AI initiatives as one of their top-five priorities for 2018. Gartner’s latest CIO survey of 3,160 CIOs from 98 countries, found that 21% of CIOs are already piloting AI initiatives or have short-term plans for them. Another 25% have medium- or long-term plans.

Gartner: Deployment of AI Initiatives in 2018

“In 2018, organizations will strive to improve their understanding of what AI is best suited to, and how to deploy it,” says Dekate. “By 2020, 85% of CIOs will be piloting AI programs through a combination of buy, build and outsource efforts.”

However, CIOs will have to overcome challenges. Many are dealing with data of poor or uncertain quality. Their organizations often have minimal AI skills. Some CIOs are struggling to understand the capabilities of new AI techniques, and how to identify use cases to which AI may be applied productively.

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Seizing fresh AI opportunities

DNNs are opening up new opportunities for AI. Many early DNN adopters are aggressively prototyping and openly sharing their techniques, providing enterprises with templates for replicating AI success stories. Over the next three years, more software companies and cloud providers will integrate DNN capabilities into their products, further reducing the complexity and barriers associated with AI projects.

Dekate shared an example of a business-to-business company that has used an AI-powered advanced analytics platform. The platform helped it analyze all its customer data, locate inefficiencies in internal processes and understand where it could improve the customer experience. The platform ingested the data and interpreted the patterns it discovered, which enabled the company to identify six processes for improvement and automation.

Gartner expects that cloud service providers, including big names like Amazon, Google, IBM and Microsoft, will introduce robust machine-learning environments and API-driven services in the near future. These will enable organizations to rapidly integrate machine-learning capabilities for key use cases such as fraud detection, customer churn prediction and precision marketing.

Lack of available skills remains the greatest challenge for CIOs in terms of AI deployment. However, Gartner expects that the skills gap will shrink dramatically over the next three years as more universities offer and expand AI courses.

CIOs who have begun experimenting with AI technologies will continue to make sense of machine learning and other AI technologies, figure out their roles in digital business, and launch the internal pilots that will test their knowledge and insight on AI.

Gartner clients can read more on this topic in the report titled "Predicts 2018: Artificial Intelligence," by Chirag Dekate, et al.

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2019-2021 Emerging Technology Roadmap for Large Enterprises

We gathered expertise from IT professionals across 198 organizations to benchmark adoption stages and risk and value factors for 108 infrastructure and operations technologies for this year. The emerging technologies profiled are spread across six technology buckets: compute and storage, compute and storage (cloud), digital workplace, IT automation, network and security.

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