Due Diligence: 3 Questions to Ask Your AI Startup

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Separating AI hype from reality is not always easy. Yes, AI capabilities are evolving quickly, but translating that into real-world business benefits can be hard. Now Deloitte is stepping up with a guide to help buyers navigate the sometimes-tall claims of AI startups.

You’ve likely been subjected to a pitch from a vendor selling an AI product or services that sounds too good to be true. It leaves you wondering: Can the AI really do that? How would that work at my business? And should I invest my company’s money to implement?

Finding answers to these questions can be difficult. But help is on the way in the form of Beena Ammanath, executive director of the Deloitte AI Institute, who has put together a handy guide to walk would-be AI purchasers through the vetting process for AI startups.

There are three important questions that customers should ask AI startups before they sign on the bottom line:

1. “Can the solution adapt?”

It’s often the case that an AI product or service that works well for one company won’t necessarily work for another, Ammanath writes. “If the product was built specifically for another client, it may need additional changes to work for you,” she writes.

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At a bear minimum, the product or service should do what the company claims it can do. That is, there needs to be some actual “AI” in that AI offering, “and not just data analytics to orchestrate applications and workflows,” writes Ammanath, who is a 2020 Datanami Person to Watch.

Sometimes, an AI solution will only work for a particular industry, and not another, according to Ammanath. In addition to the ability to customize, the critical customer should also look at quality control at the vendor, how quickly the vendor brings it to market, and its ability to stay up on the latest regulations, especially around fairness, bias, discrimination, diversity, and privacy.

2. “Is the AI startup stable?”

Nobody wants to invest their company’s money in a vendor that will be out of business in a couple of months, but this is a possibility in the high-risk world of startups. During the initial months or years of a company, the executives will likely be focused on getting funding, which is a distraction from their core business, Ammanath points out.

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In particular, Ammanath suggests taking a close look at the folks in charge of the AI startup, who may also be its founders. Are they 20-something entrepreneurs with little real-world experience, or are they former CTOs who have been in the business for 20 years?

“[D]on’t assume one is better than the other,” she writes, “but do account for mitigating different risks based on the management team makeup.”

Keep in mind that visionaries do exist. Without them, we wouldn’t have all these great tech solutions in the first place! But it’s often the case that folks who are blessed with a clear technical vision and ability are not also equipped with the managerial skills necessary to scale a company after the initial technical buzz has worn off.

3. “Can the company scale?”

Going from an AI pilot to full production is a process fraught with difficulty. But for an AI startup, scaling up the solution is a critical step for long-term success. Scale is a bit of a conundrum for a startup, Ammanath writes, “because typically only with a scalable product comes the big revenue needed to keep the startup on firm footing.”

An AI startup must be able to scale not only in the product front, but also in the business sense. In addition to being able to attract the requisite talent needed to build a compelling AI product or service, the company must be able to do all the other things that a startup must do to grow the business beyond the skeleton crew that it starts with.

Beena Ammanath is the executive director of the Deloitte AI Institute

The startup’s culture (or lack thereof) also factors in here. “Unless the company is lucky enough to have experienced leadership, startups often begin their journey without a definitive culture, which often leads to internal challenges, conflicts, disappointments, and employee turnover and can significantly impact its long-term viability,” Ammanath writes.

While there are risks to choosing an AI startup over a more established brands, there can be significant upsides too, including saving you development time, creating a competitive advantage, and possibly resulting in an outstanding return on investment by solving your company’s real problems, Ammanth writes.

Ultimately, the answer to whether you should partner with an AI startup will be had by performing a good old fashioned risk-benefit analysis that considers all of these factors. “It can be part culture, part people, part product, part possibilities, part ‘can’t put my finger on it.’” Ammanth writes. “And it may be exactly what you need.”

You can read more about Deloitte’s advice for dealing with AI startups here.

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