It's an interesting paradox, but thanks to the ubiquity of Siri, Alexa, and Cortana, the virtual personal assistant (VPA) remains more synonymous with our homes than the workplace.
Fortunately, the strength of opportunity presented means the reach of this technology, along with other Artificial Intelligence-infused smart apps, is expanding beyond the smartphone and domestic setting, taking us to the cusp of a radical disruption in the working environment.
By 2021, Gartner projects that 40% of new enterprise applications implemented by service providers will include AI technologies. They are poised to play a transformative role in boosting employee productivity and slashing costs, while optimising operating models and business processes.
Inevitably, apps that harness historical and real-time data to enrich and personalize the user experience, have long been viewed through a consumer-centric lens. As a result, it can be all too easy to lose sight of the benefits and indeed criticality of applying a similar investment to the workforce playing a key role in delivering the customer experience.
Ultimately, empowering employees through intelligent apps that can simplify their role and in turn boost their performance, optimize communication, collaboration, and engagement, can add meaningful business value and impact the standard of service provided.
Things have come a long way since the genesis of workplace task automation in the early 90s when invoice processing or the reconciliation of purchase orders were the sum total of the capabilities. Now, equipped with machine learning to draw deeper insights from data, the new breed of technologies can perform more complex and time-consuming tasks – the kind of which sap energy and focus, consequently undermining worker productivity.
Wading through emails is a case in point. A study by McKinsey & Co found that C-Level executives spend an average of 38% of their time on this task. Harnessing VPAs equipped to decipher which correspondence takes priority, has significant repercussions by freeing up time to focus on their core work and more creative endeavors.
As with a living and breathing PA, initial attempts at email management on behalf of the boss won’t be without trial and error, as VPAs are also on a learning curve. However, built to learn and continuously improve as their understanding of the employee’s behavior deepens, we will see fine tuning and refining so their intervention becomes ever more relevant.
Then there are the benefits set to be brought to meetings and conferences, which extend beyond automatic scheduling. Using voice-based commands to record the meeting proceedings, enables the minutes to be compiled and sent out to the attendees faster and with greater accuracy, relegating the time and effort involved in traditional transcription to the past.
In a similar vein, the explosion in virtual reality and immersive experiences will signal an end to the days when PowerPoint presentations were the only visual distraction to meetings.
The use of virtual reality screens to enable internal teams to explore and discuss manufacturing and marketing strategies using digital prototypes, is just one way that processes around research and development will be significantly speeded up and collaboration significantly boosted.
As AI becomes a prerequisite ingredient of EPR software, with advancements snowballing in recent years, we also see the exponential rise in unstructured data that businesses can still struggle to transform into actionable sight.
It’s a challenge that demands astute management, both in terms of creating a data-driven culture and the deployment of advanced analytics. Applying text-mining algorithms to discover relationships among data sources will do the heavy lifting behind the scenes to mitigate the heightened complexity of big data, while user-friendly interfaces and easy to interpret data visualizations will bring this intelligence to life.
Crucially, it is important not to view intelligent apps as part of a wider intelligent app ecosystem, rather than distinct entities, as these must be supported by agile and integrated architectural foundations that drive autonomous and adaptable business processes. Microservices and the ability to plug and play different machine learning models and services to deliver specific functionality becomes a more relevant proposition.
Furthermore, as employees work more collaboratively while becoming more specialized in their role, traditional processes need to move away from standardization, towards being ad hoc and contextual.It is this marriage of the two that will result in the truly smart enterprise.