The News: Smartsheet announced it had integrated Amazon Q on AWS to implement a new generative AI-powered assistant designed to help its employees improve productivity and securely access and use organizational knowledge. The integration deepens an existing partnership between Smartsheet and AWS. It is focused on helping Smartsheet consolidate all of its knowledge into a single AI engine that can provide workers with immediate answers via natural language queries.
You can read a press release detailing the news at Smartsheet’s website.
Smartsheet Implements Gen AI-Powered Assistant for Its Employees
Analyst Take: Smartsheet announced on July 10 that it had integrated Amazon Q on AWS to consolidate its company knowledge into a single AI engine that can provide workers with immediate answers via natural language queries. Smartsheet embedded Amazon Q in the company’s Slack app to help its more than 3,300 global employees quickly get answers to their questions without requiring them to know where the information is stored or managed within the organization. The implementation was conducted in just a few weeks, without developers needing to write a single line of code.
Typically, employees seeking organizational information need to know where the information is housed within the organization and then manually access that particular document or knowledge base. Searching may not yield fruitful results, particularly if the search terms are not semantically matched to the information.
@AskMe, the Smartsheet Amazon Q chatbot, is designed to address this issue by leveraging generative AI to ingest information from wherever it is stored and then make it available to employees via a natural language query. The chatbot has been trained on public help documents, training courses, and hundreds of all-employee Slack help channels.
To use the chatbot, Smartsheet employees can simply tag @AskMe in any Slack channel, ask a question, and Amazon Q will instantly give them an answer. According to the company, the chatbot has already saved Smartsheet employees significant time spent searching for answers to their questions so they can move faster to confidently support the company’s customers, drive innovation, and focus on doing the most impactful work.
Deploying Generative AI to Drive Efficiency
Generative AI is relatively limited in its ability to truly improve efficiency and productivity. However, implementing the Amazon Q chatbot at Smartsheet ticks all the boxes for deriving real-world benefits from generative AI.
First, generative AI must be trained and grounded in vetted datasets. In this case, the AI model was trained only on vetted company information, which includes formal documents, such as training courses and help documentation, as well as informal sources, such as communications between employees within Slack channels. This reduces the likelihood that the chatbot goes “off the rails” and hallucinates.
Second, the chatbot has been made accessible within Slack, thereby ensuring employees can use the tool within the flow of work and within a commonly used application of record. This accomplishes two tasks: it ensures employee uptake, which, in turn, will help ensure that the model gets better over time through increasing utilization. Note, however, that to ensure the model continues to function properly, human oversight is required to fine-tune the model and ensure that the model does not ‘drift’ from its original intentions.
Finally, the chatbot makes it easy for workers to find and interact with critical data. Previously, it was very difficult to ensure that workers would reference the proper source of knowledge, given the challenges in ensuring that all workers knew where to find and how to access this data. The use of a generative AI-based chatbot helps to address this issue of data accessibility.
Of course, internal uses of chatbots and generative AI technology are commonplace now and are often seen as a method of validating the efficacy of a particular technology solution. To generate similar results with non-partner customers, Amazon Q must work with them to ensure that the same implementation steps are followed, particularly around data availability, data cleansing and vetting, and model training and grounding.
Ultimately, the functionality of any generative AI chatbot is largely dependent upon following this approach. Smartsheet’s use of Amazon Q to power its @AskMe chatbot should serve as a blueprint for other organizations seeking to improve efficiency and productivity through generative AI.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other insights from The Futurum Group:
Smartsheet Q1 FY2025: Significant Revenue Increase and Efficiency Gains Despite Net Loss
Enhancing Security and Efficiency with Smartsheet Advance
The Six Five In the Booth at Smartsheet ENGAGE 23 with Ben Canning, SVP, Product Experiences
Author Information
Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.
From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.
A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.
An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.
Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
