Having already invested in building an engaging digital workplace to drive employee productivity, many firms are looking closely at simple AI technology to heighten this experience even further. From voice-activated search becoming the norm, to IoT devices making the leap from home to the office and the increasing use of AI and robotic process automation, the digital workplace landscape is changing into the intelligent workplace and it's all about flexibility and integration here on out. By 2020, Gartner predicts over 50% of medium to large enterprises will have deployed product chatbots. Further, IDC forecasts global spending on cognitive and AI systems will grow to $19.1 billion this year, and grow to $52.2 billion by the end of 2021. Adding an AI layer to the digital workplace to spur intelligent transformation is expected to be one of the early areas of investment in the enterprise as companies push to use technology to further push worker productivity.

Business adoption of artificial intelligence is accelerating, fueled by an explosion of data, the rapid growth in cloud computing and the emergence of advanced algorithms. In a survey of IT decision-makers that my company, CCS Insight, conducted in July 2017, 58 percent of respondents said they are using, testing or researching the use of artificial intelligence (AI) in their organizations. Respondents also estimated that as much as 30 percent of their business applications would be enhanced with machine learning within the next 24 months -- a bullish view, considering the technology's well-documented problems with trust, cost and the lack of skills needed to train machine learning systems. Speech-based and image-based cognitive applications are emerging at an accelerating rate for use in specific markets, such as fraud detection in finance, low-level contract analysis in the legal sector and personalization in retail. AI is also beginning to appear in systems designed for corporate functions such as customer service, HR, sales and IT.

Gartner reports that 85 percent of information in a company is unstructured, and that a company's information doubles every 18 months. Moreover, according to a Dimensional Research survey commissioned by my company, M-Files, nearly 50 percent of professionals struggle with documents and content scattered across disparate applications and storage locations. In order to keep up with the exponential growth in the volume of information, the paradigm of knowledge and information management in today's digital workplace must shift to include contextual understanding. Artificial intelligence (AI) plays a major role in this, and the industry is taking three steps toward the day when fully automated digital assistants will support an intelligent workplace. The journey to an intelligent workplace begins with the content itself.

With all the hype around artificial intelligence (AI), cognitive search and intelligent intranets, it's hard to understand how to actually apply those new technologies to improve the workplace. But it may not be that difficult: If you get a few of the basics right, you can put an effective cognitive search system in place and set it up for ongoing growth. Machine learning (ML) is behind all this, and it is advancing incredibly quickly. Sometimes it's touted as almost magic, but in fact the underlying algorithms in machine learning have not really changed in a decade. The advances are the result of fast, cheap computing, the availability of huge sets of data, open-source software and models, and easier administration and development environments.

AI has been kicking around for a while now, though many associate the concept with Alan Turing, who introduced what we know as the "Turing Test" in a 1950 paper, "Computing Machinery and Intelligence." What is new is the ability to scale human to machine conversations -- once the realm only of humans -- where the machine provides relevant answers to specific questions at an individual context. We see this scale in the mass market thanks to entrants from large consumer electronics brands such as Apple's Siri and Amazon's Alexa, but this capability has yet to reach the corporate market. AI-enabled search promises to transform the way people interact with information and digital assets, driving new efficiencies and creating value from information that has been all but lost in the "digital junk drawers" that are our corporate information management systems. For AI to deliver on its promise, these junk drawers need preliminary organizing structures before the vision of conversational interactions can be realized.

The old saying, "It's not what you know, it's who you know that matters" is in desperate need of a 21st-century makeover. In today's digital workplace, a more appropriate adage might be, "What you know depends on who you know." Pioneering businesses have recognized this and replaced outdated hierarchical management structures with dynamic cross-functional teams. That, in turn, has fueled unprecedented innovation. Yet even as advances in collaboration and technology allow people to collaborate in ways unimaginable a generation ago, the pace of change and volume of data has made finding experts and their invaluable knowledge more challenging. That's forcing many leaders to think outside the (search) box.