Invest in Engines, not Tools

Sep 08, 2022

A recent piece by Gartner said that organizations should invest in "Invest in predictive and autonomous digital projects." How is this different from what we're doing now?

Apparently what we're doing is investing in tools - lots of them. A recent article in TechCrunch claimed that the average organization uses almost 300 different SaaS tools. Other data indicate that each department in these organizations uses 40-60 tools. One might argue that this is, as the TechCrunch article claims, a tsunami, but that's a whole different discussion.

How is a predictive, autonomous tool different from conventional tools? Let me go out on a limb here. A predictive tool is able to derive insights from the data it works on. An autonomous tool can then take actions based on these insights. Such tools don't require regular and continuous human intervention to deliver their benefits. They're better called business engines, rather than tools. You set them up to deliver a particular result, and then let them run.

Why are autonomous business engines so attractive? For starters, they have a much lower cost of ownership (TCO). You don't need to dedicate one or more FTEs to run an engine. A fractional FTE who sets up and monitors the engine should suffice. Engines can also be deployed at scale without blowing up your budget. When these engines have a direct impact on revenue, things get really interesting.

We built a revenue engine for video - AudienceGraph. Learn more at .

PS. The Gartner article specifies restricted distribution so I cannot link to that.

About AudienceGraph

AudienceGraph transforms your video from passive content to a revenue engine that engages every viewer on topics that matter to them right now. Its AI engine works in real time across millions of viewers to optimize engagement and drive revenue.

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