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What is an AI copilot?

What is an AI copilot?

The rise of generative AI and the massive popularity of OpenAI’s ChatGPT has led to widespread recognition that software applications are about to fundamentally change.  Generative AI offers the potential to both deliver breakthrough new application capabilities and transform the way people interact with software. Instead of interfaces like forms, menus, and buttons, users everywhere have become familiar with conversational interfaces to digital knowledge and task completion and are searching for powerful new ways to achieve more, faster, by leveraging AI.

So what’s behind the magic of ChatGPT and other next-generation AI products like Google’s Bard or Anthropic’s Claude? Large language models (LLMs) and increasingly large multimodal models (LMMs). These very large machine learning models, generically referred to as generative AI, are pre-trained on large quantities of diverse data spanning text, code, audio, images, and video, and then adapted or fine-tuned to become helpful conversational AIs that are capable of completing a wide range of data understanding and generation tasks.

For software applications, generative AI offers a radically new canvas of possibilities. This is evident in the rise of embedded AI copilots for applications.  

AI copilots: AI assistants powered by large language models (LLMs) and deeply embedded into applications to help users accomplish more, faster. 

While sometimes referred to as assistants, sidekicks, or other brand-specific names, software vendors everywhere are following industry leaders like Microsoft, who first leveraged its OpenAI investment to develop GitHub Copilot for developers and then followed up by delivering Microsoft Copilot for users of the Microsoft 365 productivity suite and beyond. These and other early copilot examples like Notion AI, HubSpot’s ChatSpot, Intuit Assist, Salesforce Einstein Copilot, and Shopify Sidekick have been rapidly followed by a steady stream of new AI copilots being introduced by SaaS vendors large and small in every vertical.

The rise of the AI copilot

While everyday sales and support chatbots have existed for many years, AI copilots offer a new and different opportunity to reimagine the value that software can deliver to users.  Unlike earlier chatbots, AI copilots use powerful LLMs like GPT-4 to answer questions, provide insights, and assist users across the application. They deeply understand how to use an application’s data and APIs and can be integrated across an application as both a conversational copilot and copilot-powered features and services.

High-level summary of traditional chatbots vs AI copilots

Why AI copilots?

AI copilots are embedded AI assistants that tirelessly help users accomplish more, faster, freeing time for higher value tasks. With the help of an AI copilot, users can focus on activities involving deeper problem solving, strategy, innovation or creativity, or simply get time back for other priorities. 

SaaS vendors can reduce user friction and boost user engagement while lowering operating costs associated with support, fueling growth.  Multiple SaaS providers are adding material incremental revenue by launching AI copilots priced as add-ons or offered at premium pricing tiers – proving that users are willing to pay for embedded AI assistance that unlocks new ways of working.

AI copilots benefit both users and SaaS operators by delivering three key copilot capabilities: answering user questions, assisting users with proactive insights, and accelerating and automating user tasks and workflows.

AI copilots answer questions

The ability to get immediate answers to any application or domain-related question by simply asking in natural language – without clicking around within or leaving the application to dig through other resources – saves users time and enhances user productivity. Whether getting information needed to move forward with a task, to enhance application knowledge, or to surface an insight, AI copilots give users the answers they seek on-demand, so they can get more done and avoid the frustration of searching around or contacting support. 

The impact of instant expert-level question answering capabilities over both product and application data can be significant.  A Microsoft commissioned study found that early Microsoft Copilot users were 4 times faster at catching up on a missed meeting and 29% faster in an overall series of tasks such as searching, writing, and summarizing information.

Microsoft Copilot helps people work faster. Source: Microsoft

For SaaS operators, unanswered user questions amount to friction and frustration that hinders adoption and productivity, lowers user satisfaction, and maximizes the burden on human support resources.  AI copilots instantly unlock answers from data, including application data, documentation, support resources, domain data and more. This means that users and support teams can skip the time-consuming research, synthesis and curation of knowledge that’s already contained within an application itself or product documentation.

AI copilots provide intelligent insights

In addition to tirelessly and instantly answering user questions, AI copilots excel at proactively summarizing, reviewing, and highlighting critical information to users.  For instance, a CRM copilot might summarize all previous customer interactions and flag high-priority follow-ups, or an accounting copilot may summarize accounting statements and flag line items for further review.  These proactive insights and suggestions help users work smarter, upleveling their knowledge and skills as they work. 

In a study of early Microsoft Copilot users, users leveraging an AI copilot realized improvements in ideation, creativity and quality of work as well as getting more time for higher value tasks.

Microsoft Copilot improves creativity, quality and focus. Source: Microsoft

AI copilots accelerate workflows

Beyond answering questions and offering proactive insights, AI copilots can accelerate and automate user tasks and workflows.  For content heavy applications, AI copilots are already demonstrating radical improvements in productivity.  A study of developers leveraging Github Copilot found that it led to 55% faster coding and 46% more code written, while significantly increasing job satisfaction.

In addition to boosting speed and productivity, GitHub Copilot makes developers more fulfilled. Source: GitHub

Similar results have been reported for other copilots that assist users with creative, knowledge, or repetitive tasks. With an AI copilot that can fluently draft and improve text, code, and other domain-specific assets, users are free to focus on innovation and quality, while also getting time back for other priorities.

In addition to generating and refining content more quickly, AI copilots are capable of combining application data and APIs with reasoning, planning and orchestration to accelerate and automate complex workflows on users’ behalf.  For these types of automation use cases, AI copilots offer virtually unlimited potential, particularly as underlying AI capabilities rapidly improve.

Learn more about AI copilots

AI copilots offer a once-in-a-lifetime opportunity to reimagine the value software can deliver to users.  Our next blogs in this series will explore five of the most popular AI copilots from industry-leading SaaS providers as well as dive into the technical architecture, tools and best practices for building and operating AI copilots for SaaS applications.  If you’re thinking about building an AI copilot for your application, we’d love to hear from you, or you can subscribe below to get updates on this AI copilot blog series.

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