16 February 2023

Consumerised interfaces: an Alexa for the office?

7 minute read


Jo Faragher

Jo Faragher

Jo Faragher is a writer and editor, specialising in HR and employment issues. She is a regular contributor to Personnel Today, People Management, First Voice (Federation of Small Businesses magazine) and Times Higher Education. She was awarded the Towers Watson HR Journalist of the Year prize in 2015 and was Highly Commended for the same award in 2019.


Employee experience Future of work HR transformation


Alexa-style AI interfaces could lighten the load for HR teams by fielding repetitive queries and requests from employees and managers. Here’s how to make it work for you

Voice assistants now occupy multiple rooms in our homes, doing everything from telling jokes to sharing weather forecasts and adding items to our shopping lists. For consumers used to the likes of Alexa and Google Home, it’s become second nature to ask them to turn on the lights or set an alarm. As our work and home lives have become ever more blurred, how has this affected our expectations of the technology that helps us do our work? According to Shimrit Janes, director of knowledge at Digital Workplace Group, the chasm between the consumer interfaces we have become used to in our personal lives and the technology we use at work has created a ‘user experience debt’. “There’s a disparity between the private experience we have as consumers and what happens at work, leaving us frustrated and asking ‘Why can’t it just work like that?’,” she says. “People feel that things should just work and be intuitive.”

Statistics from Dell back this up: 35% of employees surveyed for Dell’s Future Workforce Study said that the technology they have at home is far more advanced than what they have at work. Remote and millennial employees would be more likely than other workers to quit a job due to substandard tech, and seven in ten felt it influenced their new job choices. Consumer products and services are increasingly developed and improved through design thinking – an approach where the user is the

focus – but much of the tech we use at work is yet to catch up. “Today I believe the biggest change is not just the role of technology, it’s the need to focus on experience design for all aspects of work,” says top HR analyst Josh Bersin. “We can no longer think of HR as a function solely for creating and administering people-related programmes. We have to design and deliver experiences, just like we do for customers.”

According to Deloitte, the key to meeting these expectations is putting the user at the heart of how we build tools and services at work. “In order to create an enduring relationship, be social in nature, and create meaning, experience must come from and be focused on the individual,” the company advised in its 2019 Human Capital Trends report. “When experience comes from the individual (bottom-up), it is designed starting with the employee’s pre-existing tendencies to enable them to do their best work in the way that works for them. When experience is focused on the individual (personal), it is designed to incorporate all of the psychological needs that must be met in order for someone to perform their work well.” That said, investment in consumer-facing chatbots far outstrips their use for employee tasks such as HR self-service and helpdesk queries.

While we’re some way off the widespread adoption of voice assistants at work, many organisations are beginning to identify processes or tasks in their organisations that can be automated to create a smoother experience. These range in sophistication from simple chatbots that can route requests to back-end systems such as integrated HR and payroll software, to complex AI tools such as IBM’s Watson that can analyse complex datasets, offer intelligent suggestions, and even make low-risk decisions. They are well suited to a range of HR processes across the employee lifecycle because these tasks tend to be transactional – setting up an interview for a candidate, for example, or sending out a benefits statement. The chief benefits are in the time saved: technology services company Wipro launched an AI tool called Holmes to deal with IT helpdesk tickets using natural language processing in 2015. Over the space of two years, just 10% to 12% of the 5,000 daily service requests were being passed to a human and 20% of the requests were resolved end-to-end without any human involvement. Thanks to machine learning, AI-powered bots get better at handling tasks with each interaction, so time and cost savings improve and the ‘human’ team can focus on more strategic work.

Here are some other potential use cases for consumer interfaces:

  • An employee can ask a voice assistant how many days’ leave they have remaining
  • Processing an expenses claim while on the move, using voice activation on a smartphone
  • A bot proposes a meeting when a customer is due to renew a contract
  • Multilingual communication between employees in global offices
  • Accepting an invite while driving
  • A manager asking a chatbot to find a performance appraisal form
  • An employee commands the company AI to ‘fetch me this month’s revenue’ and the AI serves up the document

Such consumer-friendly interfaces are only possible when tools and platforms are seamlessly integrated behind the scenes. APIs allow applications to ‘talk’ to each other, and they can also link a chatbot on an employee portal or intranet to information from relevant systems ‘under the surface’. If this is done badly, the benefits of offering an easy user interface are lost, argues Henry Amm, managing director of Adenin Technologies, which builds consumer interfaces and digital assistants for intranets. “Companies often have multiple apps in production, with employees navigating anything between five and 15 on a daily basis,” he explains. “You can create a bot so someone can ask about an HR policy and the bot links to the HR system. But where the experience can fall down is if it then offers them an 80-page PDF they can’t read on their mobile phone. If it can give a direct and definitive answer, it’s saving that user clicks and time.” Organisations can use analytics to identify where requests are falling down and tweak the AI engines behind the interface. “You can tell the engine, ‘Here are 100 things people might ask’ or show it the words they might use for different requests. You need to teach the AI so people can ask things naturally,” adds Amm. Adenin constructed a digital assistant for tech giant Cisco for employees to access their everyday applications in one place; the company has since won awards for digital workplace readiness and experienced a 17% increase in workplace satisfaction.

As AI becomes more sophisticated and learns more about the context of an organisation and how people work, these interfaces can begin to act more like digital colleagues than technology tools, says Johan Toll, chief technology officer for IPsoft, which has developed a digital assistant called Amelia. “Use cases are beginning to change from having a bot that can answer a question to [one that gets] something done. So, the user might say ‘I need three days off next week’ and they are not sent a form, the time just gets booked in,” he explains. “If someone has lost their credit card, they can move to a hybrid model if they want to speak to a human, who then passes the resolution back to the assistant. This is what creates great experiences for employees.” Open APIs make most assistants ‘agnostic’ to the systems at the back end they’re connecting, which means organisations can customise and personalise the employee experience. Toll adds: “In the past, any kind of human-to-service case meant the user needed to adapt to the system – so if you move employer, you have to learn a new programme. By putting in a virtual assistant, this adapts to the employee rather than the other way around. This is a big change and also drives engagement.”

Just as we might put a human colleague on probation, time and effort are required to educate and test these interfaces. This can mean there is a frustrating period where employees do not receive the precise answers they need, and when HR or other teams need to review and adapt the data feeding its responses. It can help to communicate with employees that the system is still learning, and ensure support teams are available to answer questions in the interim. Organisational circumstances are also very fluid: consider asking a chatbot about furlough in 2019 before the pandemic began. Questions and responses will need to adapt as legal or business developments lead to changes in policies or allowances.

“As humans, we don’t do things the same way every time, but an assistant will carry out a task in a linear way each time. If you get a bad response, you won’t use it again, so you need to show it can deliver value,” explains Toll. He advises organisations to start with simple, real-life scenarios and build up from there. While we might assess human employees quarterly or even annually at an appraisal, AI interfaces are learning from feedback every day and adjusting their output accordingly. Janes adds: “The best success comes from having a period of experimentation – a ‘fail quickly’ mentality. This is why lots of organisations focus on transactional processes where it’s easy to define the knowledge base, and it’s still early days in terms of impact on employee experience.”

The next step is empowering employees and managers to create their own assistants, Toll predicts. “A HR person is the best [person] to know how their processes work, so how do we train them to train an assistant and create their own automations? This is how we democratise AI.” IPsoft has developed a ‘digital employee builder’ that enables subject matter specialists to piece together blocks of AI that suit what they’re trying to achieve. As this market evolves, it will also be incumbent on HR to work with other parts of the business to build frameworks for how managers interact with their virtual colleagues. They will need to build workflows to show how matters escalate when the digital tool reaches the limits of its support, and manage how data is stored and protected. We’ll see more specialist roles develop – such as ‘chief robotics officer’ – to manage such tools.

As organisations strive to create better experiences for their workers, it’s important not to assume that what’s ‘good’ for consumers will translate to the workplace. The reasons Alexa makes life easier at home may not equate to increased engagement at work, even if bots and assistants help us to be more productive. As Deloitte’s report concludes, consumer interfaces need to be part of a broader push for engagement that goes way beyond technology. “Employees are different from customers: they have an enduring, personal relationship with their employers, unlike customers who can stop buying an organisation’s products at any time. The employee experience is social: it is built around culture and relationships with others, moving well beyond a focus on an individual employee’s needs. And most relevant to the issue at hand, employees want more than an easy set of transactions; they want a career, purpose, and meaning from their work.”


Five key takeaways

  • Think about your organisation’s ‘use cases’ for a virtual assistant, chatbot or other consumer interface. What problem do you want it to solve?
  • Start small and break down processes to their simplest components; this increases the system’s chances of success
  • HR is a natural fit for consumer interfaces – automating responses to common employee queries is a good way to start an evidence base for more investment
  • Invest time to build knowledge in your AI tools and tweak if necessary
  • Talk to IT and marketing departments about consumer- facing tools – could something similar work for employees?


This is an extract from Good Work, Great Technology: Enabling strategic success through digital tools, published by leading UK HR software provider Ciphr. For more insight into how technology can change work for the better, download the complete book for free, now.