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M.R. Asks 3 Questions: Pat Calhoun, Founder & CEO, Espressive

By July 3, 2019Article

With an intense focus on user experience and customer adoption, Pat Calhoun is set to transform the enterprise self-service experience to a consumer-like approach. No stranger to finding solutions that fill gaps in the IT Service Management field, Pat’s first startup, Airespace, grew revenues to over $80M in two years before being sold to Cisco for $450M. 

Holding 35 patents and published in more than 16 publications, Pat and I had no shortage of topics to discuss. 

M.R. Rangaswami: What market need drove you to create Espressive and how is the product filling a gap in the IT Service Management (ITSM) space? 

Pat Calhoun: I founded Espressive on the belief that getting help at work shouldn’t be so hard. With CIOs becoming increasingly focused on using AI in their digital transformation initiatives to reduce IT service desk call volume, reduce MTTR, and increase employee adoption, we knew there needed to be a shift in the way ITSM vendors approach the employee self-service experience. While ITSM incumbents, third-party providers, and other start-ups have in the past focused on solving the problems faced by IT service desk, with Espressive, we shifted the focus to the employee—because you can’t have self-service if your employees are not engaged. However, this doesn’t mean the help desk is left behind. When you improve the employee experience through automation, you reduce redundant help desk work, enabling agents to focus on more strategic projects.

We recently found that enterprises using ITSM tools are looking to adopt AI to solve challenges including low employee adoption and high call volume, according to the Pulse Report. In fact, 62 percent of respondents are at the consideration point or above in terms of implementing AI in the form of chatbots for ITSM, and 46 percent are actively researching AI solutions to meet their needs. 

When designing our virtual support agent (VSA) Espressive Barista, we knew that we needed to go beyond conversational chatbots in order to enable digital transformation of enterprise service management (ESM). Barista, our AI-based virtual support agent (VSA), brings the ease of consumer virtual assistants, such as Amazon Alexa and Google Home, into the workplace. Barista automates resolution of employee questions, issues, and requests with personalized experiences that result in employee adoption of 80 to 85% and reduced help desk call volume of 40 to 60%.

M.R.: With AI becoming mainstream in the enterprise, what is Espressive’s approach to leveraging AI and machine learning technologies, and how do you maximize adoption? 

Pat: In the ITSM space, many startups are trying to use AI to automate self-help and address the issue of low adoption of intranets and service portals. But early implementations of AI in ITSM have failed because they are either extremely complex and time-consuming to deploy, or they are bolt-on solutions to an existing ITSM tool that was originally designed to protect IT help desk resources instead of maximizing employee adoption. They have historically tried two approaches: 1) Platforms that enable organizations to build chatbots, as well as third-party tools like Watson or, and 2) Searchbots that use advanced algorithms to enable a more efficient search of existing knowledge base articles. 

Platforms require customers to hire an ongoing staff of linguists, AI experts, and data scientists to use them. However, with acute talent shortages in AI, this approach is not available to most. Searchbots, on the other hand, are hampered by the lack of a good knowledge foundation in most enterprises, and force employees to be precise in their language in order to find the information they need. To gain market traction, some searchbot vendors claim high (100%) adoption because they’ve integrated their chatbots into collaboration tools such as Teams or Slack. This is an unfortunate sleigh of hands, because across the industry email and phone calls still account for over 85% of help desk interactions. 

With both approaches, when employees ask these chatbots workplace-related questions, they typically get a highly fragmented service experience––instead of immediate answers, they will receive multiple knowledge base articles to review. If the chatbot is unable to provide an adequate response, or employees do not want to take the time to read multiple documents to find their own answers, IT tickets are created. Employees are then sent to a portal to manage their pending requests. When it comes time to interact with a human to get help, they are shifted to email. In the end, this cumbersome process discourages most employees from using it, and as a result, does not ultimately deflect phone and email requests from the help desk.

At Espressive, we’ve delivered a pre-built, consumer-like app that is accessible and intuitive. The way we’ve leveraged AI and machine learning technologies is that Barista comes with an extensive vocabulary tailored to the workplace. Through natural language processing (NLP), the Barista Employee Language Cloud understands over 500 million phrases across over 4,000 topics out of the box and growing. By incorporating leading AI technologies that enable Barista to understand what employees are saying in their own language, we are providing a personalized response and use machine learning to identify the correct team or department when a question can’t be immediately answered. Equally as important, the Employee Language Cloud is constantly growing, because as employees ask questions, Barista learns new phrases, phrase structures, synonyms and topics. This ever-expanding cloud is constantly available via a crowd sourcing model to all Espressive customers, while anything specific to a given customer remains their intellectual property.

For a virtual support agent to be adopted, it has to deliver a consumer-like experience that is both intuitive and accessible as a native app across Android, iOS, Microsoft Windows, and MacOS as well as through a browser. Achieving high adoption has historically been a challenge because old habits are hard to break, and most self-service tools have required employees to behave differently. Espressive believes that achieving high adoption also requires an omni-channel approach that is capable of capturing all help desk interactions. Barista is able to intercept messages sent through multiple channels including email, Slack, Microsoft teams, QR codes, and even calls to the help desk. Over time, employees learn that Barista is the one place to go for help. With the right solution in place, CIOs will be able to divert valuable budget dollars from answering repetitive questions to strategic initiatives. And, employee net promoter scores and productivity will also increase.

M.R.: In your opinion, what needs to be done to fully solve the employee self-help problem? 

Pat: According to recent Gartner research, the number of enterprises deploying artificial intelligence (AI) has tripled in the past year. The same report revealed that chatbots have displaced fraud detection as the top use of AI in 2019. While Gartner looked at CIOs overall, we sponsored a survey that focused specifically on IT service management (ITSM). That survey revealed that 62% of enterprises are currently considering or actively moving forward with implementing AI/chatbots for employee self-help.

There is no doubt that AI is well-positioned to enable digital transformation in IT and beyond, but it could just as easily turn into a lengthy, expensive, failed proposition. What can enterprises do to ensure that they get it right out of the starting gate?

For AI to deliver digital transformation to employee self-service, it can’t be based on legacy solutions—AI must be the foundation.

  • AI solutions need to be built in a way that encourages employee adoption because adoption is what will increase employee satisfaction and productivity, which in return will reduce call volume and MTTR

  • Vendors need to deliver pre-built consumer-like apps that are accessible, intuitive and understand the language of employees 

  • At the same time, these tools must increase the ROI of existing ITSM investments and deploy quickly without the need to hire expensive and rare AI resources to implement and support 

  • Further, it must include case management capabilities that are available to departments (e.g., HR, finance, legal) that are still operating off of email and phone calls

As Gartner pointed out in their recent research, AI will be a game-changer for digital transformation in 2019. If you base your AI initiative on the right technology, we agree.

M.R. Rangaswami is the co-founder of Sand Hill Group and publisher of 

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