IT Leaders are increasingly feeling the heat, with end-users being exposed to phenomenal experiences in technology outside of work. This has resulted in ~70% of end-users globally being disillusioned with internal IT.
IT Leaders in their mission to transforming end-users experience, optimizing costs and streamlining operations are increasingly looking at Artificial Intelligence (AI) and Automation, as the key innovations. Artificial Intelligence adoption is at various stages of maturity across enterprises. AI based Virtual Agents (bots) have been around for quite some time however they have become mainstream in enterprises only in the last couple of years, and chatbots are one such example. Across the length and breadth of businesses, there is a definite wave amongst IT Leaders to deploy platform agnostic chatbots, as digital assistants to be able to hold engaging conversations with employees (and customers alike). IT Leaders are looking to transform the digital employee experience by empowering them with chatbots backed by Artificial Intelligence (AI), Natural Language Processing (NLP) & Machine language (ML).
At the moment, there are no established industry frameworks for chatbot development or even deployments. Every deployment is unique, and enterprises are learning on the journey. At a very high level almost every chatbot initiative/program, has two key strategic intents:
- Employee Experience – digital assistant to empower the employees (customers) with seamless self-service capabilities;
- Operational Efficiencies – relieve support teams (IT, HR, Admin, Finance, Customer Service etc) of mundane repetitive tasks to improve their productivity.
IT Leaders in their desire to be innovative are going all out to ensure that both strategic intents are achieved instantly. Nirvana for any chatbot initiative would be if the employees start using the bot as their Digital Personal Assistant for all their needs anytime, anywhere across any language and medium (chat, voice, video). However, there is no magic wand, AI based chatbots need time to train and learn, apart from infinite use cases that can be enabled. Most of chatbot failures are due to lack of clear vision and strategy. IT Leaders need to adopt the ‘think strategically and act tactically’ approach when it comes to this technology – have the strategy but develop one feature at a time and get the adoption wheel rolling.
A phased approach to chatbot development and deployment is important, as small quick wins define the experience for employees (customers) and help improve adoption.
Training the chatbot with How To’s and FAQ based use cases with ML and NLP across IT, HR, Admin, Finance, Customer Service, Product Support etc, is a good starting point, as not only does it take away mundane activities from support staff but is also a good conversation builder for employees. This ‘Basic Chatbot’ is a good way to promote awareness and initial adoption.
Once there is comfort amongst employees on self-service, the next phase is further empowering them with actions that can be performed via chatbot, like self service password reset, app install, issue resolution on end point device with one-click solutions etc. When a good adoption of chatbot has been achieved and increased preference to get issue resolved by chatbot rather than a human agent, it is a good time to move on to advancing the capabilities. It is important to note that there will always be cases where chatbot simply cannot resolve, hence the transfer from chatbot to human need to be as seamless as possible without reducing user experience.
Integrations with business & infrastructure applications to be able to get the bot to perform advanced tasks like meeting room bookings, expense claims etc. is the next logical phase along with moving from just being a chatbot to an advanced Digital Personal Assistant which can be contacted over chat, phone or video across preferred language. Though there is not one right strategy, the entire process needs to be customized around that is the business requirement and target audience – internal or external.
IT Leaders need extreme focus on what problems they want to solve or let’s say the capabilities they want to support. A well-defined chatbot strategy is extremely helpful not only to determine investments, but to gain stakeholder buy-in along with clear forecasted returns at every step.
The focus on use cases, user experience and adoption of chatbot are amongst key success criteria, there a quite a few considerations that need to be factored during the development and deployment cycle along with continuous improvement. Some of the key considerations would be:
- Business Requirements & Target Audience: Getting the business and employees involved and understanding the business & technology challenges that need solving. Narrowing down the requirements and understanding the target audience, their behaviours and motivation.
- Platform, Features & Security: Once the requirements are frozen and audience determined, identification of platform on which the chatbot will be developed. A traceability matrix with around requirements vs features along with access and security.
- Program Plan: A phased approach as explained above with clear milestone not only covering the technical aspects of platform, security and features, but the overall governance, communication, training, awareness and adoption plans. What gets delivered when, how is it delivered, who get what and when, how do they get it and where do they get it – success factors. Define what determines success of the program – user engagement, return on investment, perception, ratings, user experience, employee productivity.
- Learning & Tracking: AI needs training and learning. Clear plan on learning, sources of knowledge, integrations, testing and improvements. Tracking of progress, tweak if needed and elimination of bias form the bot – on it handles data, queries, preferences and even promoted.
- Innovation & Improvement: AI is in continuous state of learning and development. Having an identified team whose focus would be on adding features, innovation, integrations, improvement – to ensure that the chatbot will leverage any AI service(s) available in the market today and will also scale for future services. Invest in competencies that include experimenting, developing, and maintaining chatbots
Finally, there is the human aspect. As with any program there will be resistance to change. IT Leaders need to ensure that support staff is made aware of the benefits of bot deployment and given confidence that bot is aimed at only relieving them of their repetitive work and thereby making them more productive.