Chatbots in HR: ‘Digital Employees’ connected to your brand

Cat Mules

Cat Mules

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chatbots data & AI

“Hi! If you have questions, I’m here to help.”

Chatbots are now commonplace. Research by Intellectyx projects a worldwide market size of more than $1.3 billion by 2024 for chatbots, on the path to becoming a driving force for business communications. It’s a belief echoed by Siddharth Davé, Director of Operations at New Zealand-based chatbot specialist agency, Cultiv8.ai.

Chatbots are computer programs that use Natural Language Processing (NLP), a type of artificial intelligence for understanding and responding to written or spoken language.

“Conversational agents can be a meaningful tool to drive real ROI for your business, the key is knowing how to create a digital employee vs a “chatbot”,” Sid says.

Typically, chatbots are created to handle large volume questions in a similar manner to humans, but at scale and cost that humans cannot achieve. These bots are usually siloed to specific industries, such as human resources or sales, and do not handle a large array of topics at launch. The newer evolutions in chatbots though, are able to chat with each other and provide a holistic conversation for all of the platform visitor’s needs, guiding them with multiple pathways including FAQs, product or service information, payment process and sales. Bots are no longer limited to just one vertical.

The chatbot development process has also evolved. Sid explains how, “Traditionally you launched chatbots at around 90% completion, with today’s conversational agents we’re looking at a 60% completion on launch.”

As we cannot possibly know all the different ways a user may interact with us – that is, ‘ask questions’ – the key factor to delivering on the return on investment for a conversational agent becomes your “Post-bot iteration strategy” – aka ITERATION, ITERATION, ITERATION! The ability to move and improve the NLP model multiple times a day means we can have new journey releases, or feature updates, multiple times a week.”

Increasingly, chatbots generate robust business outputs focused on and contributing to real business outcomes. For business owners, one key value may be the money chatbots save. Another is that they make it much easier to maintain brand image across the board.

Sid explains that the word ‘chatbots’ is sometimes used informally but today they are more like conversational agents, aka your ‘Digital Employees,’ and with them everything becomes easier.

This can vary from answering simple FAQ’s to triggering a backend process to driving real business outcomes. Whether you’re submitting A CV for review, conducting initial interview questions, applying for your holiday leave, or any number of people and process focused business outcomes, the contribution of chatbots on improving business life is powerful.

Yes, chatbots can be a very easy and cost-effective option to consider when dealing with repetitive and mundane tasks that are holding up your employees time. Sid explains that chatbots never get tired, never complain, never want a raise, they always cooperate.

“This doesn’t mean we’re looking to replace human capital outright but rather free up the wasted time from doing repetitive mundane task to focusing on the more meaningful customer experience.”

“They can also be a highly effective means of data collection if utilised in the right way, they can help identify trends, understand the core intent and need of your customers allowing you to create a more meaningful experience overall.”

Hardly surprising, when we’re looking to chatbots to solve a problem online, speed wins. Salesforce’s State of the Connected Customer research finds that consumers expect chatbots to reply nearly as quickly as a service rep would a face-to-face conversation. They also expect a chatbot to respond faster than someone on the phone.

Sid provided us with some quickfire advantages for the use of chatbots in HR:

  • Recruiter – Interview candidates through chat, funnel and identify the right candidates for you
  • Internal Staff – Check and apply for leave
  • Candidates – Find the job that best fit for your skillsets

“The future and true value realisation will come from understanding chatbots as more than just your FAQ bot, but as a means to truly serve your customers,” Sid explains.

“By enriching them with different personalities, habits, communication styles based on demographics and regions, they’ll be Digital Employees. They’ll fill gaps and replace previously tedious tasks. They’ll be there for anywhere the human touch just isn’t good enough.”

Cat Mules

Cat Mules

Umbrellar's Digital Journalist, coming from a background in tech reporting and research. Cat's inspired by the epic potential of tech and helping kiwi innovators share their success stories.

Cultiv8.ai

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Helping digitise your workforce with the power of AI. We're an AI consultancy based in NZ but operating globally with clients & partners throughout NZ, Australia, USA, Singapore & more. Our mission is to help excite change in the modern-day by educating and empowering companies to take the leap into AI today not 5 years in. Helping reap the first-mover benefits.

Data, AI, BI & ML

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Artificial Intelligence and Machine Learning are the terms of computer science.Artificial Intelligence : The word Artificial Intelligence comprises of two words “Artificial” and “Intelligence”. Artificial refers to something which is made by human or non natural thing and Intelligence means ability to understand or think. There is a misconception that Artificial Intelligence is a system, but it is not a system. AI is implemented in the system. There can be so many definition of AI, one definition can be “It is the study of how to train the computers so that computers can do things which at present human can do better.” Therefore it is an intelligence where we want to add all the capabilities to machine that human contain.Machine Learning : Machine Learning is the learning in which machine can learn by its own without being explicitly programmed. It is an application of AI that provide system the ability to automatically learn and improve from experience. Here we can generate a program by integrating input and output of that program. One of the simple definition of the Machine Learning is “Machine Learning is said to learn from experience E w.r.t some class of task T and a performance measure P if learners performance at the task in the class as measured by P improves with experiences.”

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