Table of Contents
- Market Categories and Deployment Types
- Key Criteria Comparison
- GigaOm Radar
- Vendor Insights
- Analysts’ Take
- About Michael Azoff
- About Jon Collins
Intelligent virtual assistants (IVAs) are becoming increasingly common solutions for helping end users solve all sorts of problems that once required human intervention. These end users, often retail customers, are said to be on a journey from the initial query to its resolution.
Vendors use artificial intelligence (AI) technology to build automation at the core of their IVA solution. An IVA is not one monolithic piece of code but multiple automation pieces that combine to fulfill the tasks required to process an end-user query.
At the start of the customer journey, AI is used to convert speech to text and sometimes also to translate a foreign language to English before further processing. Once the end-user input is available as text, the next step is to pull out the intents—the end-user’s purpose—from the query. This is accomplished with the help of AI-based natural language understanding (NLU) and natural language processing (NLP). Furthermore, AI can be used to predict the outcome of the conversation, to answer fact-related questions, and to perform sentiment analysis. Finally, in the return part of the process, AI is used to convert text to speech (if a voice channel is being used).
These multiple AI elements are built in a variety of ways by different vendors and may be augmented by linguistic and semantic models. A key trend is the emphasis on ease of use in deploying a solution, with low code or no code (LCNC), a popular approach for enabling a business’s domain experts to build an IVA solution. Increasingly sophisticated IVA building blocks are becoming available from the major public-cloud providers, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Some enterprises use these building blocks to create their own IVA solutions and typically need developer expertise to do so, but the IVA players may also exploit these tools in building out their solutions. So while the cloud providers have increased competition in the market, they also provide opportunities to both enterprises and vendors.
The market for chatbots and IVAs continues to grow and improve, but the top end of the market—the sector satisfying the needs of large enterprises—must present solutions offering human-like performance and high scalability, which require more sophisticated capabilities, and this report assesses such capabilities. The companion GigaOm report, “Key Criteria for Evaluating Intelligent Virtual Assistants,” delves into the architecture of an IVA solution and the features that are critical for evaluating its capabilities.
How to Read this Report
This GigaOm report is one of a series of documents that helps IT organizations assess competing solutions in the context of well-defined features and criteria. For a fuller understanding, consider reviewing the following reports:
Key Criteria report: A detailed market sector analysis that assesses the impact that key product features and criteria have on top-line solution characteristics—such as scalability, performance, and TCO—that drive purchase decisions.
GigaOm Radar report: A forward-looking analysis that plots the relative value and progression of vendor solutions along multiple axes based on strategy and execution. The Radar report includes a breakdown of each vendor’s offering in the sector.
Solution Profile: An in-depth vendor analysis that builds on the framework developed in the Key Criteria and Radar reports to assess a company’s engagement within a technology sector. This analysis includes forward-looking guidance around both strategy and product.