Adam Oliner is Head of Machine Learning at Slack, the popular workplace collaboration platform. Prior to Slack, he served as Director of Engineering at Splunk, where he developed and led the machine learning team for four years. Adam holds a PhD in computer science from Stanford University, and was a postdoctoral scholar at UC Berkeley’s AMP Lab. You can find him on LinkedIn here.
At a time when coworkers can’t tap their neighbor to ask a question or request a document, Slack has become a business essential. As Slack usage soars, Adam reports that companies are relying on the technology more than ever before to stay connected.
But employees aren’t just leaning on it for instant communication—they’re also leveraging it as a digital history of all company conversations. In fact, Adam notes that Slack is actually an acronym, for Searchable Log of All Conversations and Knowledge.
Whereas video conferences, or even employee memories, are ephemeral records of information, Slack is persistent by default. By leveraging the smart search functionality, employees can access all digital conversations conducted throughout the company.
Adam shares that AI is persistent throughout Slack’s platform, in both user-facing features and in the backend of the platform. Semantic search, autocomplete and automated recommendations throughout the platform are three of the most commonly-used AI-powered functionalities, all designed to make the experience more intuitive and user-friendly.
For example, any time a user begins typing in the search bar, Slack’s machine learning technology suggests relevant people or channels they may be looking for. More recently, Slack added a similar feature for recipient recommendations; now, when a user begins to compose a message Slack suggests additional coworkers or teams the user often communicates with. Another common example is channel recommendations; ranked by internal priority, Slackbot will suggest channels to join that may be useful or relevant.
These smart features are increasingly important as companies rely more and more on Slack as a central repository for company conversations and historical knowledge. Slack understands this need, and is actively working to make information more readily accessible to users. In fact, when Slack recently rewrote the front end of the product it enlarged the search bar and made it more central to the platform display, offering a constant reminder to users that they can easily retrieve valuable information at any time.
As companies increasingly rely on digital methods of communication to succeed, Slack is dedicated to continuous improvement of the platform to make it even more useful. AI is a critical component of this vision; as it learns from user and team data over time, it creates an increasingly intuitive product. Slack’s data scientists also leverage AI in the backend to make better business and product decisions, too.
In addition to Adam’s belief that AI and machine learning will make Slack even more useful, he shares insight on Slack’s other strategies for product improvement, including customer feedback, extensive A/B testing and executive intuition to continuously create a more seamless product.
While Adam acknowledges that there are certainly many challenges with today’s remote work, he also notes that constraints can breed positivity, like creativity and innovation.
In fact, Adam believes that even Slack—a pioneer in keeping employees connected online—would have previously been skeptical that a global SaaS company could function entirely remotely. But the pandemic has created a stress test, and many companies have discovered what’s possible from afar. For many, the time saved from commuting, or even international travel, has been a boon for productivity.