As AI continues to evolve and gain depth along several functional vectors, it’s expanding in its utility and applicability. For example, we’ve gone from the age of apps to the age of assistants. Next up is the age of agents. Along with that agentic trend, we’re seeing another area of development: multiplayer AI.
For those unfamiliar, this involves AI that’s built for groups of people (think: a marketing team) to access AI-powered tools. Multi-seat access is nothing new in the enterprise software world, but here we’re talking about AI’s ability to learn from and serve a targeted group of users across several surfaces.
Advantages include the ability to learn from the goals and preferences of several users individually. And on an aggregate level, AI tools that do this can process a more effective profile of a group, team, or company – whatever the scope may be. In that sense, it could be well aligned with SMB teams.
“Most AI tools for small businesses today are built for one person: each staff member opens their own assistant in their own window and works alone,” vcita founder & CEO Itzik Levy told Localogy Insider in a recent discussion on this topic. “That isn’t how small businesses actually run. The front desk, the owner, and the service providers all share the same clients, the same calendar, and the same revenue goals.”
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Multiplied Value
We mention this now because we’ve seen the term multiplayer AI invoked with greater frequency. In a recent Q&A with Brian Chesky, for example, the AirBnB chief noted how agentic AI is well-suited for rote decisions like booking a flight. But when it comes to vacation rentals, manual research is half the fun.
That escapism of the process could save Airbnb from agentic threats. Instead, AI could assist the human experience by filtering listings. That brings us back to multiplayer AI, as it can be tuned for several users – such as family members planning a reunion – so assistants can train themselves on group parameters.
Another example is Yext’s recently-launched multiplayer agent harness. It sets up marketing teams to work from the same data and with the same agents for multiplied utility. Agents continually monitor attributes like online visibility, reviews, and SEO, then spark the right actions across a given team.
“Scout’s multiplayer harness puts it all in one workspace,” Yext CEO Mike Walrath told Localogy Insider. “So a lean team and its agents can cover every channel and every location a brand shows up in, and spend where it actually moves the business instead of where they’re already winning.”
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Cover More Ground
Beyond the advantages noted above – including training and executing across several surfaces – multiplayer AI accomplishes something else: scalability. When looking at AI’s ability to elevate rather than replace human productivity – a growing sentiment – multiplayer AI compounds that positive effect.
“Agents don’t replace great marketers,” said Walrath. “They let a handful of them cover ground that used to take an army.” This applies acutely to local marketing – whether it’s multi-location brands challenged by the need to scale efforts across thousands of locations, or resource-starved SMBs at one location.
That brings us back to vcita, which focuses on the latter. Levy tells us that the platform’s agentic tools can surface opportunities across the business. That includes everything from a client that’s due to rebook, unpaid invoices, or leads that go cold. The right action can be prompted in each case.
“As agents start doing real work, siloed AI will create blind spots, with duplicated effort, missed handoffs, and no clear view of who did what,” said Levy. “Interfaces built for the next stage have to be multiplayer, so humans and agents work in the same place with full transparency.”
Header image credit: Vitaly Gariev on Unsplash
