Anyone following the enterprise AI space cannot help but notice the recent shift in marketing AI tools from targeting individuals (code assistants, GPT chatbots, image generators) to targeting teams (Team Copilot, Google Workspaces, Atlassian Confluence). The keywords “team” and “collaborate” could be heard on nearly every keynote stage in recent months, and this is significant. Tech companies are doubling down on positioning AI as an instrument for accelerating business. Enterprise generative AI, we are told, will revolutionize the ways that companies operate. But what does this evolution bode for individual contributors, and developers specifically? Some imagine a Kafkaesque nightmare in which AI note takers summarize AI-written emails, and in the process generate a mountain of text that no one ever reads. Others worry that by integrating AI into every node of the software development lifecycle (SDLC) AI code assistants will start QAing code written by AI code assistants in systems architected by AI. Garbage in; garbage out. But despite these fears the tech companies selling AI services are bullish about AI’s potential for augmenting organizational velocity, efficiency, and productivity.
Era of Collaborative AI
The goal of using AI to support and accelerate business is longstanding. Salesforce touted authoring internal communications as one of Einstein’s earliest use cases. But so far this has largely been aspirational. All the air in the room has been taken up with how AI can enable individuals. AI code assistants like GitHub Copilot and AWS Code Whisperer support single developers, namely during their focused coding time. Similarly, personal ChatGPT accounts allow individuals to generate responses as unique as themselves—from vegan taco recipes to wedding vows. All of these distinct and private uses elevate the human by giving them super powers. Tasks that previously took hours, such as writing thank you notes or persuasive emails to your landlord, could now be accomplished quickly and (relatively) eloquently.
But the era of collaborative AI has arrived, or so enterprise tech companies would have us believe. Here are a few examples.
During his Think 2024 keynote, IBM CEO Arvind Krishna plugs the suite of watsonx AI tools that include watsonx Code Assistant for enterprise Java applications, watsonx Assistant for Z to transfer knowledge and expertise, watsonx Orchestrate assistant builder capability, and watsonx Code Assistant for Z natural language. Krishna effuses that these tools are not only secure, but also a boon for accelerating the workplace:
Our teams have so much trust and get so much creativity out of them, tasks that used to take two to three weeks a year, year and a half ago, the teams are now getting done in a couple of evenings. That really, I think, speak to the power but also the trust that we have.
During her Google I/O ‘24 keynote, Aparna Papou, VP of Google Workspace, enumerates Gemini’s use cases for collaboration:
And it’s not just how we collaborate with each other, but we each have a specific role to play in the team. And as the team works together, we build a set of collective experiences and contexts to learn from each other. We have the combined set of skills to draw from when we need help.
Atlassian President Anu Bharadwaj demonstrates the integration of Atlassian Intelligence, meaning AI in Atlassian cloud products, into their whiteboard during her Atlassian Team ‘24 keynote. The popular collaborative whiteboard feature, which is used for remote brainstorming and ideation sessions, is now enhanced by the use of AI:
But there is always the blank slide problem. How do you put in the first idea? This is where Atlassian Intelligence comes in. AI can analyze customer feedback, stored across Jira and Confluence, automatically creating stickies for these ideas and bringing them into the whiteboard. Ideation is off to a flying start.
Finally, Satya Nadella’s Build 2024 keynote (the only one of these keynotes I attended in person) explains of Microsoft’s Copilot for Teams:
You’ll be able to invoke a team Copilot wherever you collaborate in Teams … It can be your meeting facilitator when you’re in Teams creating agendas, tracking time, taking notes for you. Or a collaborator writing chats, surfacing the most important information, tracking action items, addressing unresolved issues. And it can even be your project manager, ensuring that every project that you’re working on as a team is running smoothly.
AI for Teams
As the RedMonk team comes down from the 2024 April/May conference season, and the analysts finally lift the OOTO tabs from our calendars, it seems we have emerged fully into the era of enterprise AI for teams. While the impact of this transition is legion, the move to make generative AI an organizational accelerant will have significant repercussions for developers.
We believe it starts all the way at planning, and goes all the way into operations and maintenance. Actually, I personally believe it will impact requirements gathering, too!
— Adam Seligman (@adamse) May 9, 2024
The RedMonk team recently spoke with Doug Seven, Director and GM at AWS, about Amazon Q and the rise of AI for developer collaboration. He characterizes this trend as:
Shifting from developer productivity to development productivity, meaning moving from the individual developer and their code writing to how do we [developers] apply generative AI across the organization
As AI technology has become technologically approachable and priced more accessibly, companies are finding new ways to harness it in the workplace. Text, code, and image generation for personal use was the first era, but strategy and synthesis is the next horizon. This sort of high-level work has always been the dream for an AI future in business. Indeed, decluttering email inboxes is one of the first tasks the fictional AI assistant Samantha (voiced by Scarlett Johansen) accomplishes in Spike Jonze’s Her. But it is also the marketing reality for enterprise AI vendors today. In terms of software engineering, by shifting to encompass more of the SDLC, AI is being positioned as a tool for optimizing organizational success, rather than just a siloed assistant.
Disclaimer: AWS, IBM, Microsoft, Google, Atlassian, and Salesforce are all RedMonk clients.
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