man working on laptop sitting on a parapet wall
PHOTO: Avi Richards

Three years ago, I attended an event where a representative from IBM presented on the potential of Watson in various sectors. The presentation turned out to be very good, but unfortunately we had to wait 10 minutes while an AV guy sorted out the projector, cable and other assorted issues before it could start.

The irony of a situation where technology paints an exciting picture of the future but then somehow fails to deliver on some of the basics wasn’t lost on the audience.   

To me, this is an analogy for where we are with any concept of the “intelligent workplace” — a heady future mix of artificial intelligence (AI), machine learning, algorithms, data analytics and enterprise search which will deliver various benefits. Yes, we can see the potential and sure, there are pockets of exciting activity where we are making headway. But it also seems like an awful lot of work must be done on the foundations before we can make the “intelligent workplace” both impactful and sustainable.

Where Are We With the Digital Workplace?

If we look at our collective record across different elements of the digital workplace so far, it doesn’t bring much confidence of our ability to deliver on AI, search and other data-related initiatives, in the short- to medium-term. Our progress is somewhat underwhelming.

For example, the Digital Workplace Group and CMSWire’s joint 2017 survey into the “State of the Digital Workplace” asked over 200 organizations to rate the effectiveness of their various digital workplace tools. Across every tool, no more than 32 percent of those questioned stated any tool was currently “working well” and for the majority of tools, the relative response rate was under 20 percent.

If we can’t get some very mature tools to “work well,” how can we expect the “intelligent workplace” to successfully emerge? Search is a case in point. It’s a mature discipline which has a lot in common with AI in terms of the skills, disciplines and approaches needed to make it a success, but we all know search in many organizations does not meet needs and is often under-resourced.

While search has shown improvements, it would be a shame if AI and data analytics became the new area where digital workplace teams traditionally struggle.

To really build for the future of the intelligent workplace, we need to work on the foundations. I break this down into three elements — strategy, governance and change management.

Related Article: The Clue to Your Digital Workplace Problems Lies in Your Employees' Work-Arounds

Strategy

Organizations, departments and functions need to have a strategy for what they want to achieve around the idea of the “intelligent workplace” if any progress is to be made. This could be one component of a broader digital workplace strategy. Indeed, some forward-thinking organizations are incorporating this into their strategy, such as MITRE Corporation, who last year added “Anticipatory knowledge delivery” as a new strand of its knowledge-driven enterprise strategy.

However, as technology is still advancing rapidly and practices are emerging, companies are taking a “wait and see” approach before deciding what they want to do. Many organizations are now actively experimenting with different AI-related products and providers and it may be that more comprehensive strategies will result in due course.

Moreover, something like AI is such a loose concept that can creep into different disciplines and processes (e.g., HR, recruitment, marketing, etc.), it is not always applicable to have a single enterprise-level strategy.

Governance

For the intelligent workplace to work we need governance in place, not only around things like data standards and information management, but also in the use of systems. For example, if a future highly intelligent, machine-learning enterprise search indexes Microsoft Teams for all its documents and nuggets of knowledge, when all the action is happening on Slack, it will never succeed.

Governance and oversight needs to also protect individual data and the ethical dimension. When “the intelligent workplace” is unchecked and the workforce basically becomes the subject of psychological experiments, which according to a New York Times article is close to what happened at Uber, we’re in trouble. 

The boring, inconvenient truth is we need more governance in these areas of the digital workplace, not less.

Related Article: Governance Still Matters in the Digital Workplace

Change management

Change management is needed in all of this. Using individual data makes many people nervous, especially considering how much mistrust there is in the workplace.

Moreover, many of the de facto owners of different content and data silos (standalone systems, specialist applications, databases, restricted sites, etc.) often feel nervous letting go of their data for reporting, search or for improving AI. 

Businesses need a change management effort to get everyone comfortable with allowing their data to be used to help drive AI.

Build Those Foundations

For anyone doing almost anything meaningful in the digital workplace, none of this will come as a surprise. We need strategy to give us direction, consensus and prioritization. We need governance to make it all happen and make it sustainable. And we need change management because people are people. 

I suspect the challenges around AI and the intelligent workplace will present themselves in these aspects, rather than in the technology. And we should be pretty used to that in the digital workplace.