Earlier this week I had raised questions for folks to ponder when weaving AI into their B2B products:
How can AI create a major increase in task productivity?
How can AI accelerate shifting novices to power users?
How can AI extend the reach of my network effects?
There is absolutely friction on each of these dimensions that previously was either a fixed cost that had to be paid (e.g. a complex setup process) or a heavy tax that was hard to get around (e.g. learning curve for new users) - the value of AI is to fundamentally revisit and rethink these costs and taxes - do they even need to be paid and could they be managed much more cheaply in terms of user / buyer time and effort?
The video above is a conversation with Anurag Wadehra on how to think about layering AI into your B2B product and motion. The visual below was key to framing the discussion:
The big takeaways from this framework are that the “jobs to be done” within an enterprise that a B2B product tries to map to fundamentally involve:
multiple players
feedback loops
varying ROI levels
And by incorporating AI into your product you can eliminate redundant tasks, automate repetitive work, provide real-time relevant assistance, and even reason about your business differently such that goals can be re-framed and de-risked.
We covered a broad range of questions with the audience over the 1 hour discussion, but some of the most interesting takeaways from my perspective were:
