{"id":251694,"date":"2021-05-01T00:00:00","date_gmt":"2021-05-01T04:00:00","guid":{"rendered":"https:\/\/www.servicexrg.com\/blog\/ai-intro-for-support-2\/"},"modified":"2026-01-15T17:40:07","modified_gmt":"2026-01-15T22:40:07","slug":"ai-intro-for-support-2","status":"publish","type":"post","link":"https:\/\/www.servicexrg.com\/blog\/ai-intro-for-support-2\/","title":{"rendered":"What Support Leaders Need to Know About Applying AI to Support"},"content":{"rendered":"
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Artificial Intelligence is not a silver bullet it is a tool. This tool however holds the key to fundamentally changing the way support is delivered. With the right application of AI fewer resources can handle more interactions and potentially in a more proactive and productive way.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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What is AI<\/h2>\n

AI, or Artificial Intelligence is a convenient term that is widely accepted to represent access to a new type of intelligence \u2013 not artificial, but machine based. The promise of AI in in its ability represent human knowledge, make recommendations or predictions about something based on what it understands, and to extract meaning from vast amounts of data.\u00a0 AI can process and represent information with speed and accuracy at a scale beyond human capacity.<\/p>\n

One of the pioneers of AI, Arthur Samuel, described it as a \u201cfield of study that gives computers the ability to learn without being explicitly programmed.\u201d Samuel coined the term machine learning, which more accurately represents the state of AI today.<\/p>\n

For the purposes of this article we will use the term AI to represent a new type of machine intelligence that we can leverage as a tool.<\/p>\n

Types of AI<\/h2>\n

Today\u2019s AI technologies are focused on representation of human knowledge typically within specific focus areas. Machines are taught a set of rules to perform actions or represent knowledge.\u00a0\u00a0 Current AI is classified as\u00a0Narrow AI<\/strong>.\u00a0\u00a0Strong AI<\/strong>\u00a0is the next level of machine intelligence where rules, knowledge and learning enable machines to create new knowledge, solve unfamiliar problems and operate in ever-changing circumstances.<\/p>\n

Examples of true machine intelligence exist in Hollywood and perhaps in the research labs, but for the purposes of applying it to post-sales services, we are limited to narrow AI capabilities.<\/p>\n

Making Machines Intelligent<\/h2>\n

The reason we have introduce AI into the services lexicon is that the ability to make machines intelligent is now possible without a team of PhDs on staff (although some companies do have these types of resources on staff).\u00a0 AI-enable technologies provide services teams with the ability to introduce intelligence into the service process without having to develop customized software and algorithms.<\/p>\n

Whether AI is enabled through custom software or out-of-the-box solutions, there are common elements that make AI possible.<\/p>\n

Machine Learning<\/h3>\n

For AI to act intelligent it must be taught about the domain in which it will be working. For technical support, a machine must be taught about products, operating environments, issues and solutions customers are likely to encounter.\u00a0 Machines may also be taught to identify circumstances that can cause a problem to occur.\u00a0 We may also choose to teach machines to understand customer sentiment so that we can monitor the health of customer relationships.<\/p>\n

Teaching machines may involve defining a set of rules for it to operate against.\u00a0 Machine learning may also involve deep learning techniques where a large collection of data is provided as a basis for the machine to infer meaning from the words and structure of the data.<\/p>\n

Whether through an out-of-the-box application interface or coded deep within the algorithms of a customer AI solution, teaching the machine is the first step to applying AI to support.<\/p>\n

Natural Language Processing<\/h3>\n

The methods we use to teach machines to be intelligent will also require us to help machines understand our language. When machines can process and \u201cunderstand\u201d the way we speak it is referred to as Natural Language Processing.\u00a0 The natural language we speak and understand is more than just words, it is sentence structure and the meaning derived by how words are organized.<\/p>\n

We must be certain that systems understand the nuance of our language and the lexicon of our domain.\u00a0 As an example, we need machines to understand the difference between how the word\u00a0\u201ccrash\u201d<\/strong><\/em>\u00a0is used.<\/p>\n

In a hospitality environment, crash may refer to a place to relax and may generally have a positive connotation.<\/p>\n

It was a great place to\u00a0<\/em>crash<\/strong>\u00a0for a night\u2026<\/em><\/p><\/blockquote>\n

In a tech environment crash typically refers to an unplanned event with negative implications.<\/p>\n

My computer\u00a0<\/em>crashed<\/strong>\u00a0after installing the new upgrade.<\/em><\/p><\/blockquote>\n

For most AI systems, Natural Language Processing is a fundamental capability for receiving input and presenting knowledge. Fortunately, Natural Language Processing is commonly found in many out-of-the-box solutions.<\/p>\n

Applying AI to Support<\/h2>\n

Teaching machines about our products and support-related issues and language processing (our support-specific lexicon) are foundations upon which we can build intelligent support applications.\u00a0 These basic building blocks make it possible to leverage machines for the delivery of technical support.<\/p>\n

Machines can be taught to recognize patterns and concepts and respond with appropriate actions.\u00a0 In some cases, AI can identify and help prevent issues before they impact customers (e.g. analyzing telemetry from system and application monitoring).\u00a0 Some of the benefits of AI for Support may include:<\/p>\n

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  • Machine intelligence can \u201cunderstand\u201d a user\u2019s need even if it is not expressly stated.<\/li>\n
  • AI can identify customer sentiment expressed in cases records and customer feedback.<\/li>\n
  • Knowledge can be recalled by expressing a need or concept. No longer do we need to depend upon matching a search term or phrase within a collection of written human intelligence.<\/li>\n
  • Machine intelligence can interact with a user to collect necessary inputs to resolve issues.<\/li>\n
  • A machine can execute the most logical action in response to a user need such as presenting the right answer or routing a user to an expert that can help.<\/li>\n
  • AI can identify patterns that may cause problems and help to prevent issues.<\/li>\n
  • Machines can see the things that humans may miss (data analytics).<\/li>\n<\/ul>\n

    Making Support More Human<\/h2>\n

    With the right application of AI fewer human resources can handle more interactions and potentially in a more proactive and productive way.\u00a0 While machines handle some of the support burden, support staff can focus on building and sustaining relationships through human-to-human activities:<\/p>\n

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    • Develop plan to help customers adopt and apply products.<\/li>\n
    • Develop personal rapport with customers.<\/li>\n
    • Understand customer needs and expectations.<\/li>\n
    • Advocate for customer needs.<\/li>\n
    • Empathize when something goes wrong.<\/li>\n
    • Detect early signs of dissatisfaction.<\/li>\n
    • Maintain a personal relationship.<\/li>\n
    • Reinforce value of the relationship.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

      Support has been relentless in the pursuit of continuous improvement, yet the function of Support has remained fundamentally unchanged for decades. AI is a critical catalyst that will help enable …<\/p>\n","protected":false},"author":4,"featured_media":251695,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":"","_wp_rev_ctl_limit":""},"categories":[30,46,50,14],"tags":[82,109,69,52,53,37,110,111,112,56,57],"class_list":["post-251694","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-transform","category-support","category-scale","category-technology","tag-ai","tag-analytics","tag-automation","tag-chat","tag-chatbot","tag-customer-support","tag-machine-learning","tag-natural-language-processing","tag-proactive","tag-search","tag-self-help","post_outcome-scale-delivery-capability","post_outcome-transform-and-innovate","post_activity-automate","post_activity-self-help-and-automation"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.servicexrg.com\/wp-json\/wp\/v2\/posts\/251694","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.servicexrg.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.servicexrg.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.servicexrg.com\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.servicexrg.com\/wp-json\/wp\/v2\/comments?post=251694"}],"version-history":[{"count":9,"href":"https:\/\/www.servicexrg.com\/wp-json\/wp\/v2\/posts\/251694\/revisions"}],"predecessor-version":[{"id":254936,"href":"https:\/\/www.servicexrg.com\/wp-json\/wp\/v2\/posts\/251694\/revisions\/254936"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.servicexrg.com\/wp-json\/wp\/v2\/media\/251695"}],"wp:attachment":[{"href":"https:\/\/www.servicexrg.com\/wp-json\/wp\/v2\/media?parent=251694"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.servicexrg.com\/wp-json\/wp\/v2\/categories?post=251694"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.servicexrg.com\/wp-json\/wp\/v2\/tags?post=251694"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}