Any investment in artificial intelligence should aim to deliver substantial ROI. The basic promise is very simple: for each $1 investment to get >$1 of return within a certain time frame. This can only happen by automating costly procedures (cognitive $/hour) or to create new products that sell.

Increase in the enterprize value with IP is not necessarily measurable and too fuzzy to be included in the ROI calculation. What is an optimal ROI expectation? At Manxmachina we suggest the classic ROI expectation of an investment vehicle i.e. at least 7% ROI for each $ invested.

Positive ROI is our primary focus. Potential multiples of acquihire are not interesting to us when developing AI

If we backtrack the standard way companies are valuated e.g. during a potential due diligence for acquisition we will certainly trace the most ROI rich areas we could deploy AI within the enterprize.

Growth rate matters a lot when valuating companies. But it is also balanced with customer acquisition cost (CAC) . Simply put, all healthy companies have a CAC vs customer lifetime value that is below 1. Any AI product that decreases the customer acquisition cost and increases the lifetime value of a customer is a good candidate for positive ROI.

Diving deeper into operations: operational costs should be trending lower and revenue generation should trend higher. Always focus AI solutions to automation to reduce operational costs or revenue creating products.

At Manxmachina this is our initial discussion with customers that think about investing into AI. All the hype and acquihires out there are nice to know but at the end of the day AI should empower the business for the business to empower the AI. First create AI to reduce costs, increase profits. Then build meta products on top of those that create IP and barriers to entry for competitors. This meta level of products and barriers are what can create some creative accounting for increased valuation of the company but should never be the original focus of an investment in AI.

This is also our advice regardless of the size of the company from startup to enterprize. Mechanics of how companies work are always the same.

This is why at Manxmachina we have a strict “No Moonshots” rule. These are the projects to fail because they are not connected to the deep mechanics of how companies succeed.

We always focus on quick ROI, greater revenue, less costs, more cognitive automation.

Want to get in touch to discuss how you can achieve the above with artificial intelligence for your organization?

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