The News: On February 14, Salesforce announced the rollout of Slack AI, an assistant to help users find answers, distill knowledge, and work faster. Here are the key details:
- AI-powered search. Users can ask a question and get an answer based on relevant Slack messages. Examples include learning about a new marketing campaign, getting up to speed on company policies, gleaning insights about past decisions from historical context.
- Channel recaps. Users can catch up on unread messages, summarize the last seven days, or set a custom date range to summarize.
- Thread summaries. Users can get the gist of a long conversation in one click. Sources are included in each summary, allowing users to dive deeper into a highlight.
- Slack AI’s large language models (LLMs) are hosted directly within Slack. Customer data remains siloed and will not be used to serve other clients, directly or indirectly.
- Slack AI does not use customer data for LLM training purposes.
- In the future. Native AI integration with Einstein Copilot, a new AI assistant for Salesforce CRM will provide answers to questions directly in Slack that are grounded in the customer’s data.
- Slack AI is available now as a paid add-on for Slack Enterprise plans.
- Slack AI is available now in US and UK English only.
Read the Slack AI launch press release here.
Salesforce’s Slack AI Becomes the Latest Generative AI Assistant
Analyst Take: First Microsoft’s Copilot, then Google Gemini Advanced, now Slack AI. In the span of just a few months, sophisticated generative AI assistants have been made available to the mass market, and there are more to come. What will the impact of Slack AI be? Here are our thoughts.
Safer Introduction of Generative AI to Mass Market
As we move through the first quarter of 2024, it is clear that some of the world’s AI leaders believe commonly used business applications are the best use cases to introduce generative AI to the public, and they are confident enough that they have monetized such options. The rationale is sound – these business applications are already highly integrated suites, that are mostly (but not entirely) cloud based. Given those factors – integrated applications based in the cloud – enables Microsoft, Google and Salesforce to leverage and control generative AI more easily than others compared to other potential generative AI use cases.
Consider the market impact and potential addressable market of these new launches:
- Microsoft: Office 365 users – 345 million users, $30/user/month Enterprise, $20/user/month Copilot Pro
- Google: Google Workspace users – 3 billion users/8 million paid users, $19.99/user/month/Gemini Advanced
- Salesforce: Slack users – 32.2 million daily active users, Paid add-on for Slack Enterprise plans
While Slack is not the exact equivalent of Microsoft 365 and Google Workspace, the focus of Slack AI is similar to the focus of Copilot and Gemini Advanced – to streamline business workflows. One of the interesting things about these offerings is the level of trust most users will assign to the offerings – all three companies are some of the most experienced AI companies in the world, and they have built in substantial AI safety policies. Salesforce has been very consistent in communicating a message of AI trust to the public, and their responsible AI policies and worldwide leadership in building responsible AI is an assurance that will go a long way towards building trust with generative AI for users.
The incorporation of generative AI technology into a workflow/collaboration platform such as Slack is perhaps an even more logical use case for a natural language-based assistant. Most organizations that utilize Slack do so because the sheer volume of communication between employees has overwhelmed their email or direct messaging application and require an efficient way to organize communications by groups of employees, projects, or subject area.
The challenge with Slack, of course, is it, too, can quickly become overwhelming as the number of channels and users ascend. Although the search feature can be useful to locate a specific message, there is still significant friction involved when trying to make sense of information that may be captured in disparate channels or within direct messages. The infusion of generative AI should address this challenge, by making it far easier to find, summarize, and make use of content contained within the platform, and the eventual integration of native AI integration with Einstein Copilot should further enhance the functionality and benefits to users.
Conclusion
The use cases Salesforce has envisioned for Slack AI are pragmatic and will likely resonate with users, even for the premium price. Salesforce, with their deep experience in AI, is in a position to garner new business for other Salesforce businesses should they see success with Slack AI. The deeper integration of Slack AI to other Salesforce applications will strengthen the offering. Slack AI, along with Microsoft Copilot and Google Gemini Advanced, are key to building trust in using generative AI and are in the vanguard of triggering mass market adoption of generative AI.
One of the key unanswered questions will be around the potential shift to consumption pricing around generative AI, particularly as the volume of usage rises. Delivered as a fixed-fee add-on to an enterprise license, Slack AI should generate significant initial usage as organizations experiment with the technology.
If Slack AI (or Salesforce, for that matter), eventually shifts to a consumption-based pricing model, it may be more difficult for some organizations to justify an add-on cost for internal workers that are not measured by time-based or task-based productivity KPIs, but by other measures, such as total revenue generation, which is usually influenced by a number of factors beyond individual task productivity increases. Ultimately, vendors may need to identify new metrics that more accurately capture the value created by these tools to justify add-on pricing.
While some organizations are likely to embrace any advances that make employees’ lives easier and enhance their productivity, even in an incremental fashion, others may take a far more granular look at the actual ROI these internal tools provide, particularly if the link between task-productivity and the workers’ primary metrics are not realized.
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:
Google Gemini Advanced: Google’s Counter to Copilot?
Microsoft Unleashes Copilot and Potential 2024 AI Revenue
Salesforce Announces New Data and AI Innovations for Retailers
Image Credit: Salesforce
Author Information
Mark comes to The Futurum Group from Omdia’s Artificial Intelligence practice, where his focus was on natural language and AI use cases.
Previously, Mark worked as a consultant and analyst providing custom and syndicated qualitative market analysis with an emphasis on mobile technology and identifying trends and opportunities for companies like Syniverse and ABI Research. He has been cited by international media outlets including CNBC, The Wall Street Journal, Bloomberg Businessweek, and CNET. Based in Tampa, Florida, Mark is a veteran market research analyst with 25 years of experience interpreting technology business and holds a Bachelor of Science from the University of Florida.
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.
