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AI and New-To-Market Vendors: A Few Words of Advice

Of all the possible markets in which to bring a venture to life at the current moment, AI is a bold and brave choice. Today, the artificial intelligence field is one of the hardest and one of the most promising market niches in existence.

The potential of AI to improve our use of data exponentially, and to use that data in solving our problems, both old and new, means investor interest, capital, and support has flocked to that space. For early-stage founders and new-to-market vendors, the opportunity is certainly there. But making early AI claims stand out from the others in the space is a sizable venture all in itself; below are a few thoughts for founding teams looking for differentiation and distinction in the AI space.

Standing Out In A Moment of Market Opportunity

The biggest problem in the space is the overpopulation of lofty claims. Every vendor is promising powerful market analytics, advanced data mining, and high-level behavioral learning.

The problem is two-fold. If founding teams engage in the lofty-claim approach, they face doubtful investors, who have been hearing these claims for years now, and they’re in need of a way to differentiate their claims.

But if founders fail to speak to the potential of their venture, they risk losing investor interest to another startup in the long list of AI-enthusiasts.

A winning strategy for software vendors is to show rather than tell and above all, to avoid over-telling. The tried-and-true ‘case study’ method becomes an answer to both of these problems. For real success in the information technology industry, a vendor only needs to offer a career-changing experience to one business. Every owner in every industry has considered AI for similar pain points. The founder who can solve them once is in the best position to do so at scale.

In finding the right investor fit and attracting funding, proof of the solution in small scale is the best persuasion strategy out there. By focusing most of their energy on the pipeline in front of them, early-stage founders can be slowly shaping and supporting their pitch, making it impossible to say no by the time they reach investors—and without losing time or sales in their actual business.

The Client’s Eye

So a successful case study might be good enough for investors…but how do green-thumbed founders find their early pipeline? And how do they carry a product to market, even with investor support?

More than anything, business owners are looking for AI solutions that integrate seamlessly into the operational set-up that they already have. Budgets remain low in the face of an economic challenges. The list of necessary improvements, changes, and investments is long and continues to grow. In addition, the talent shortage has left many business owners wary of spending more resources on hiring, and the thought of onboarding new team members to support AI integration can be more than enough to delay an AI investment.

Founders need to aim at solutions with low barriers to integration, both in terms of price and skill-based adoption. AI technologies that are easily trainable, and that can communicate seamlessly with different sales platforms, communications software, and back-end workflow are in the best position to win client affinity. Understanding those pain points—the constraints of tight budgets, the daunting task of hiring in the after-COVID job market—founders can answer the questions and concerns that are at the top of the client’s mind.

Above all, clients are fighting for relevance in the new business landscape. While it’s true that most companies will need to leverage the power of AI and ML going forward, that fact alone isn’t enough to turn a customer’s stress into a sale. Vendors should speak with the customer’s specific goals in mind. Rather than explaining how AI is going to change the world, they should start with how AI is going to change this customer’s day, one day at a time.

Back To Business—A Winning Model

Facing a recession, any investment seems like a barrier to entry. Larger sized enterprises might still have the capital reserves necessary for big technological investments, but most companies are only a few months out of survival mode. For this reason, software-as-a-service companies (SaaS) are advantaged. Their initial ask is lower, and most business owners can better wrap their heads around paying an ongoing, manageable fee rather than making a larger point of sale payment. This is a win-win, since the optimal operating model for software companies seems to be the service model, which offers them more recurring revenue and more client visibility.

A Few Things To Avoid

Buzzwords might be accurate when it comes to a product description, but they also might make a previously attentive audience roll their eyes. At this point in the AI conversation, founders need new words for old concepts. How many times have we heard the word ‘predictive’ thrown around? Instead, try a substitute: dynamic, personalized, aware. All of these words are aimed toward the same thing, but vendors should never estimate the power of novelty when it comes to sales phrasing.

Finally, avoid talking about AI as a one-size-fits-all solution. Instead, tailor the offering, and speak with specificity toward a business owner’s unique need. Luckily, there’s no shortage of pain points in the COVID-19 market. Founders should feel empowered to pick their niche and keep it top of mind through every sales interaction. For those that are able to do so successfully, clients abound, and investors will follow closely behind.