How AI Creates Digital Workplaces?
Gartner has published a report in 2018, “Applying AI in the Digital Workplace”, explaining the main areas that AI will affect and leverage in an enterprise that aims to become a digital workplace. Gartner asserts that, over the next 20 years, AI will offer employees “information awareness and insight, freedom from low-value-add activities, and the ability to easily use complex technologies”. Therefore, it will provide a competitive advantage to the early adopters. Gartner’s report examines the areas that will leverage the workplaces. Referring this report, we will briefly cover them in this blog. The aim is to provide a high level overview of the application areas for application leaders and human resources managers.
Recently, companies became aware of the fact that talent is scarce and it is crucial to recruit the most fitting employees, to develop their skills and to succeed in engaging them. This is a challenge for the companies – as important as the customer side. Therefore, the companies work hard to find better ways to create a better place to work. Creating digital workplaces where human is at the heart and augmented by the power of technology is the most important way of it. AI has an essential role in creating a digital workplace. As opposed to the widespread thought, the potential of AI is not limited to the customer related sphere. It is not only to leverage customer experience, to increase efficiency and to make more revenue. AI has a great potential on the internal side that targets employees, namely the internal customers of the enterprises, as well.
First, let’s explain two concepts – everyday AI services vs. targeted AI services. The former, everyday AI, is introduced as a normal course of work and perceived as a new feature of the existing tools. Employees use it as an option and the impact is slow. Employees will experience everyday AI as improved personalization, recommendations, alerts and search. Those elements will be done through machine learning, NLP and conversational interfaces. However, the latter, targeted AI, changes the roles and functions dramatically. Employees perceive it as a new system and they are obliged to use it, the impact is immediate.
Currently, what we see around is mostly everyday AI services. According to Gartner, the successful sustained implementation of everyday AI will pave the way for more-targeted AI use cases. Gartner predicts that employees see AI services, but they will not recognize them as AI. However, they will be constantly added. Everyday AI can be considered as an introductory phase in the digital workplace for long-term AI investment.
What are the fields that digital workplaces use AI technologies?
Cloud Office AI
These are the most common workloads such as email, calendar, file sharing, shared workplaces instant messaging and web conferencing applications. According to Gartner, 70% of enterprises worldwide will be running a cloud office suite by 2021. Microsoft and Google dominate this field and Gartner asserts that they seem to continue their domination.
According to Gartner, cloud Office AI delivers 3 basic benefits:
— Information awareness — Making employees aware of resources
— Task automation — Creating time efficiencies by helping employees perform everyday tasks
— Expertise augmentation — Helping employees perform complex duties
For years, collaboration tools have been driven by manual interaction because of the lack of information about the broader work context. However, AI helps to overcome these barriers. AI has the potential to predict the collaborative activities and needs before participants realize that they need to work together and provide the required information.
Content Services / Knowledge Management
Most organizations have a large content, however it is difficult to reach the information needed because of poor discovery mechanisms. AI has a potential here in the form of automated classification. The auto classification we refer here is not done by rules analysis, but realized by machine learning techniques. Such techniques provide deeper levels of understanding for the classification of business-related texts, including sentiment analysis, entity extraction, image recognition. Classification can trigger other systems in digital workplaces, as well. For example, workflows can be identified and assigned to the right team based on the entities identified.
Besides classification, AI has a potential with 2 aspects:
— Expand the data sources and capture, extract, and organize knowledge by pattern recognition, correlation, clustering and predictive modeling.
— Create and manage knowledge transfer channels that deliver relevant knowledge to the employees that need it, by modeling the user context and using AI mechanisms that include conversational AI platforms, chatbots or virtual assistants.
Another aspect of content / knowledge management is search and insight engines. It includes indexing, querying and displaying by using NLP processing / generation, graph technology and machine learning.
Intranets and Digital Experience Platforms
Most of the AI technology in the intranet and digital experience platforms were previously implemented in consumer facing digital experience applications. The two use cases are very similar, whereas the major difference is the desired outcomes. Regarding the customer facing use case, customer retention, product sales, cross sales constitute the desired outcomes, and on the workplace side the outcome is employee engagement and digital dexterity.
Digital workplaces apply AI technologies to intranets and digital experience platforms in three ways:
— Supporting employee services such as HR, finance and the IT service desks by chatbots and virtual assistants. It is important to make these services automated and proactive function that predicts the current and future needs of the employees.
— Capturing and sharing knowledge, such as expertise location
— Personalizing the experience by context awareness
Human Capital Management / Recruiting
AI helps digital workplaces to manage human capital involving – recruitment, deployment, development and management of talent. Gartner defines 4 areas:
— Recruitment – Matching a candidate for a job, predicting recruitment success or optimizing recruitment marketing. Chatbots are becoming very common in this field. We see candidate-facing chatbots with FAQ, recommendation, interview scheduling functions.
— Skills and job taxonomies – Using NLP techniques to establish skills and job taxonomies on a global basis
— Sentiment analysis and theme detection – measuring employee engagement and feedback in a more advanced way
— Recommendation engines – Using engines in the fields like content, mentors, career paths
IoT in the Digital Workspace
Machine learning and IoT are the two technologies that potentially help to make workplaces more digital while reducing the maintenance and management costs. There is a huge potential in the interaction of them.
— The IoT devices provide the data to analytics systems.
— This data feed through a machine learning network can create opportunities for cost saving and enhancement of employee experiences.
Meeting Solutions and Virtual Meeting Assistants
Another area that AI can contribute is the meetings management. By certain actions, AI can increase the effectiveness, productivity and performance of the meetings in an enterprise. Some important actions are:
— Automating the scheduling of attendees
— Aggregation of necessary meeting content
— Booking meeting spaces
— Logging action items
— Gathering feedback
In the future, we can expect generating agendas, analyzing meeting attendee engagement, participation and sentiment; real-time language translation; assessing the quality of collaboration; and ensuring compliance with appropriate processes.
Virtual Employee Assistants
As we see the rise of customer facing chatbots and virtual assistants, many enterprises create powerful use cases to use virtual employee assistants. Virtual employee chatbots and virtual assistants can help employees engage the employees through web, SMS, mobile apps, intranets. They might interact via voice or text.
These assistants mostly use knowledge repositories and NLP technologies. They may reply employees queries in any domain, HR, IT, role-specific expertise, processes. Actually, these assistants can potentially help employees about all the fields explained above.
Artificial intelligence has a huge potential to transform the workplace and make it more digital and intelligent. A better workplace will create more efficiency, productivity while increasing the employee engagement and loyalty. This eventually will contribute to the bottom line of an enterprise. Even the application of everyday AI requires the transformation of the enterprise involving redesign of the existing workflows, identifying the roles / tasks that will be augmented by the AI, identifying which data can be analyzed by AI techniques, planning the AI-based features that will be involved.
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