As we head into a new year and a new decade, I thought it was an appropriate time to build on my blog from earlier in 2019 The Future of Work Part 1 and take a look at what might be just around the corner in 2020 as Artificial Intelligence, Machine Learning and Digital Workers start to gain traction in real world business transformation solutions and applications.

There is much to think, and maybe worry, about as we enter a new decade with the continued presence of  political and social pressures that would have been hard to predict 10 years ago but are really influencing how people think about technology and if they should be pessimistic or optimistic about what the future holds. The Economist just wrote a year end special report on the contemporary worries of the impact of technology. A very worthy read if you subscribe online or can still find a copy on the shelves.

However, to me the challenge is much clearer and well defined and has been worked on actively by vendors in the ECM and BPM space for many years. The defining trend at the intersection of business and technology over the last 10+ years has been the drive for worker productivity (we could have called it “digital working” I guess – it is the same thing!) especially in white collar processes where costs are high and transformation to new business models hard to execute irrespective of the IT budget companies throw at their challenges. This is where the combination of content and process technologies has real proven impact and can continue to be leveraged as companies under take digital transformation projects to support new business models.

Achieving new levels of white collar worker productivity means making more of the workers more productive more of the time – essentially spreading expertise that used to be resident in one or two departmental “experts” to a much broader number of people but in a simpler and easier to consume way. This spreading, or democratization, of expertise can be achieved through better sharing of information, automation of work tasks and processes and adding intelligence and machine learning to many steps in what used to be manual processes.

Gartner just announced their Top 10 Strategic Technology Trends for 2020 and at #3 on the list is what they call the Democratization of Expertise – defined as “wider access to technical expertise (e.g., ML, application development etc.) or business domain expertise (e.g., sales process, economic analysis etc.) for users via a radically simplified experience and without requiring extensive and costly training”

This Gartner definition aligns with some of my thoughts expressed in The Future of Work Part 1 and  I believe the journey to a democratic work environment is going to be long and hard and full of business process automation challenges the many of the people who will read this blog will be very aware of and well prepared for. This combination of technical expertise and business domain expertise is really what information management has always been about.

My view is that in this brave new world instead of working the way some dark technology system says  workers should work, these digital workers will be given the power to work the way that is best for them – best for their customer, their supplier, their business partners – whomever their stakeholders are. The desire of corporations to build fixed business processes that provide predictable outcomes, hard coded into massive systems and technology platforms is breaking down due to AI and Machine Learning technologies. This could be seen as impending anarchy in the workplace, but the tools and skills exist today to bring an appropriate level of structure to digital business processes without constraining the creativity of a new generation of digitally aware workers. The concept of well trained “digital workers” being able to consume the services and application they need, when and how they want, is no longer an information management dream – solutions exist today that help workers collaborate, manage and process all types of work objects and “cases” in the way they believe will generate the best outcomes.

Companies will need to build a digital process environment where workers inside and outside the corporate firewall can pick the apps they feel will help them do their job best. And the chances are that, as with any normal distribution, some people will have the skills and capability to adapt to this new environment very quickly, the majority of people will do “OK” and 20% of the people will struggle to make the transition so this basically becomes a change management challenge more than a technology challenge.

If we make a broad assumption that a large percentage of the 20% that struggle will be retiring in the next 3-5 years then our focus should really be on how to leverage the 20% of leaders to capture their skills and best practices to enable and train the 60% in the middle of the curve.

Normal Distribution Curve

So, tools that offer flexible choices in task selection for digital workers but then map and analyze the best practice and the most productive end to end processes will be in high demand. These will include tools that analyze what information is accessed and when and how to complete a set of tasks with the highest quality outcome. There will also be a need to analyze tasks and map the timeline and sequence of task execution.

Many of these tools exists already, some have been packaged into solutions that focus on specific types of work like insurance claims processing or fraud investigation, others are available to be easily integrated with existing platforms like Salesforce.com, SAP etc.

Irrespective of the tools available the key will be the availability of skills and expertise in business process and information management techniques that transcend technology and, although these will need to be upgraded, there are many very well trained and skilled practitioners who already have deep knowledge of how to assemble digital processes and work practices. The AIIM community of professionals has a robust set of best practice, education courses and real world experience than can help organizations large and small in the continued pursuit of white collar productivity and transforming their workforces into true digital workers not just human robots!