Bootstrapping Is A Viable Option
Venture capital investors, accelerators, and incubators are queuing up to fund promising artificial intelligence startups. You need not be located in California or the Silicon Valley, investors are looking for AI technology everywhere and big tech firms like Google, Microsoft, Apple, and Facebook are purchasing AI companies at large scale.
Get the Most Out of Open Source Resources
First of all, you need not even develop an AI platform from scratch. Open source AI libraries are available as free-to-all open source projects by Google and Berkeley, among others. Intel also offers access to its AI research in exchange for closer cooperation. The same applies to Nvidia who are emerging as a rising force in fields like AR/VR and AI.
Hence, you can save on initial research and development expenditures and take advantage of open source resources on top of which to build your solution. Other companies may have more powerful AI resources than the open source ones available to you but you do not grow an AI startup without some knowledge in the field, right.
What matters most in innovative fields such as AI and deep learning is your initial idea. By taking advantage of open source resources, you can focus on developing your core idea and save time and money on building the underlying platform and infrastructure. If you develop a new programming language in the process, all the better, but what you usually lack at the start is namely the foundation on which to build on.
Build Revenue Streams Early
Bootstrapping any startup is all about self-funding. If you have enough funds to sustain your company during the first six months after launch, it helps. But what you really need to do is to seek revenues at the very early stages of developing an AI startup. Bearing in mind that within a decade each and every company will rely of a sort of AI, it is easier than in other IT niches.
Performing game-changing research may be tempting but revenues are which will fund further research and will give you competitive edge. Competing with early starters like IBM and Google is possible only when you possess money steams allowing you to resist acquisition attempts. If you have not created your AI startup with an early exit strategy in mind, of course.
Amount of Unique AI Patent Assignees
The good news is that you can attract customers for your AI virtually everywhere. You can ignore big players and look for prospects among the many small and medium sized companies that have no budget and talent to develop their own AI. Companies that are neither willing, nor able to pay for expensive AI platforms as well. Since you are in complete control over your company, you can build solutions big companies cannot afford to develop. They profit from scale, you can profit from customization.
Retain Your Talents and Grow
Look, the average AI startup cannot offer the perks provided by established companies. But what about finding co-founders who have the talent to grow your company in exchange for long-term benefits. Once upon a time, Apple’s stock was worth some $1.6 per share after all. Another viable option is to retain your top talent and grow by allowing stock options to them. You cannot classify this as funding, but it enables you to reinforce your positions in the field of innovation and only then to seek self-funding opportunities.
Top AI Patent Filers between 1965 and 2016
(Image Source: ClearViewIP)
Having top talent on board also opens the gates to alternative revenue streams through patents, for example. It is hard to find really innovative IT patents recently; nonetheless, the number of tech patents is skyrocketing, offering a viable funding alternative.
Bootstrapping an AI startup from the ground up is a matter of talent, access to open source AI resources, and clever corporate governance. Reap off the benefits of turning your talents into shareholders, staying clear of corporate debt and external funding in the process.
Having a multi-million budget for marketing your AI-enabled solution is great, creating internal value for your AI startup is better in the long term.
By Kiril V. Kirilov
Kiril V. Kirilov is a content strategist and writer who is analyzing the intersection of business and IT for nearly two decades. Some of the topics he covers include SaaS, cloud computing, artificial intelligence, machine learning, IT startup funding, autonomous vehicles and all things technology. He is also an author of a book about the future of AI and Big Data in marketing.