10 Predictions For AI, Big Data, And Analytics in 2018

A new Forrester Research report, Predictions 2018: The Honeymoon For AI Is Over, predicts that in 2018 enterprises will finally move beyond the hype to recognize that AI requires hard work—planning, deploying, and governing it correctly.

But Forrester also promises improvements: Better human and machine collaboration due to improved interfaces; enhancing business intelligence and analytics solutions by moving resources to the cloud; new AI capabilities facilitating the redesign of analytics and data management roles and activities and driving the emergence of the insights-as-a-service market.

As a result, 70% of enterprises expect to implement AI over the next 12 months, up from 40% in 2016 and 51% in 2017. Here’s my summary of what Forrester predicts will happen in 2018:

25% of enterprises will supplement point-and-click analytics with conversational interfaces.

Querying data using natural language and delivering resulting visualizations in real time will become standard features of analytical applications.

20% of enterprise will deploy AI to make decisions and provide real-time instructions.

AI will suggest what to offer customers, recommend terms to give suppliers, and instruct employees on what to say and do — in real time.

AI will erase the boundaries between structured and unstructured data-based insights.

The number of global survey respondents at enterprises with more than 100 terabytes of unstructured data has doubled since 2016. However, because older-generation text analytics platforms are so complex, only 32% of companies have successfully analyzed text data, and even fewer are analyzing other unstructured sources. This is about to change, as deep learning has made analyzing this type of data more accurate and scalable.

33% of enterprises will take their data lakes off life support.

Without a clear connection to change-the-business outcomes, many early adopters will pull the funding plug on their data lakes to see if they pay for themselves or die.

50% of enterprises will adopt a cloud-first strategy for big data analytics.

Forrester expects 50% of enterprises to embrace a public-cloud-first policy in 2018 for data, big data, and analytics, as they look for more control over costs and more flexibility than on-premises software can deliver.

66% of enterprises will deploy insight centers of excellence as a remedy for organizational misalignments.

With firms bringing the voice of the customer into every business decision in a unified way, 56% of enterprises already report creating customer insight centers of excellence rather than centralized or purely distributed models to accomplish this.

The majority of Chief Data Officers (CDOs) will move from defense to offense.

Business-oriented CDOs will explore opportunities to innovate with data, either through analytics embedded in internal business processes or through new external data-enabled products and services. In 2018, more than 50% of CDOs will report to the CEO, up from 34% in 2016 and 40% in 2017.

Data engineer will become the hot new job title.

13% of data-related job postings on Indeed.com are for data engineers, versus less than 1% for data scientists, reflecting the trend of big data initiatives becoming mission-critical and the need to provide broader support to the business analyst.

The insights-as-a-service market will double as insight subscriptions gain traction.

66% of enterprises already outsource between 11% and 75% of their Business Intelligence applications. Forrester predicts that up to 80% of firms will rely on insights service providers for some portion of their insights capabilities in 2018.

Academia will become the new insights partner for enterprises.

And not just academia—new research labs like the nonprofit Open AI help solve the most challenging analytic and AI problems for firms that submit requests.

This article was originally published on Forbes.com and was republished on the Attunity blog with permission from the author.

About the Author

Gil Press is the Managing Partner at gPress, a marketing, publishing, research and education consultancy. Prior to gPress, he held senior marketing and research management positions at NORC, DEC and EMC. Most recently, he was Senior Director, Thought Leadership Marketing at EMC, where he launched the Big Data conversation with the “How Much Information?” study (2000 with UC Berkeley) and the Digital Universe study (2007 with IDC). Gil is a regular contributor to Forbes and he blogs on his own sites: What’s the Big Data? And The Story of Information.

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