National Entrepreneurs' Day: 5 Ways You Can Avoid AI Startup Failure
Success requires lateral thinking, planning ahead, and smart strategies to emerge among a horde of potential competitors.
The artificial intelligence (AI) hype is getting hold of a lot of young developers and startup entrepreneurs who see this new technology as a huge opportunity to make profits. (Read How I Got Here: 12 Questions With Web Entrepreneur Angie Chang.)
However, things are rarely simple, and this amazing technology that promises to disrupt so many verticals is generally not well understood and frequently confused with a lot of fluff and empty claims.
Success requires lateral thinking, planning ahead, and smart strategies to emerge among a horde of potential competitors. (Read The Ultimate Guide to Applying AI in Business.)
Let’s wrap up some actionable advice that could help you be among that 0.1% of entrepreneurs that make it instead of the 99.9% that fail.
Provide Value Beyond the Mere Product
Times are changing, and in order to be successful a startup needs to provide customers with more than just a cool but short-lived product. Looking for profit is fine, but we are entering in an age of change and revolution since our society doesn’t work anymore.
Climate change, widespread inequalities, unscrupulous exploitation of resources are driving our capitalistic model to self-annihilation. Following the statement of Salesforce CEO Marc Benioff, “the new kind of capitalism that is going to emerge is not the Milton Friedman capitalism, that’s just about making money.”
In order to provide value, you need to ride the wave and leverage the disruptive power of AI to spearhead the change. An AI-based technology may look scary if it contributes to the dehumanization of our society.
Any new product should provide value to the human society, and contribute to make the world a better place in some way (i.e. fighting pollution, reducing waste, promoting inclusion, etc.).
Your company must be able to embed this idea both into the product that is offering to its future customer base and its brand message as well.
The key to a future that is all about connectivity is knowing how you communicate a message of transformation and evolution.
Selling Smoke Will Only Provide You with Air
Let’s be honest about that: very few people truly understand what AI is, and even less know how to handle and implement it. (See INFOGRAPHIC: Artificial Intelligence vs Machine Learning vs Deep Learning.)
Most of its capabilities are yet to be discovered, the value it offers is often misrepresented, and there’s a lot of hype surrounding it.
As a technology writer, one of the most frequent issues that I personally face when writing about AI is that nearly half of the products that allegedly advertise the “amazing capabilities of their AI” actually do not use any AI.
And even if those managers and executives you’re targeting for your marketing campaign probably can’t tell the difference, rest assured that they got at least one skilled CTO or IT department manager that is able to!
Focusing on the technology while ignoring its marketing strategy
Yeah, I’m pretty sure that your product can make the difference and really is the solution that everyone in that specific vertical was looking for.
However, who cares if no one in that vertical will ever heard about it? Do you know how many great ideas ultimately got stolen by other companies who simply marketed the same thing in a much better and more compelling ways (*cough* Apple *cough*)?
Operating inside a tech bubble is, sadly, a common scenario for nerdy people like us. Technology alone won’t grant you success if you’re not able to market it effectively, and reach the right people.
Digital marketing for AI companies isn’t easy, especially since even those who may look like they’re actively looking for your product will be undecided 90% of the time.
Allocating at least a portion of your resources beforehand to build a successful business and marketing strategy isn’t just important. It’s hands down vital.
Don’t Get Caught in an Endless Development Phase
The number of skilled developers who are able to handle and code AI is really limited, and most of them must be paid a lot to be hired. The most likely real-life scenario is that since your startup is working on this AI project on a limited budget, the people you could employ may have very little experience with this new and complex technology.
This should not discourage you — everybody knows that AI technologies are still in dire need of refining, and wasting a year behind closed door to create the perfect software isn’t going to do any good. You will likely lose money in the process, and still end up with an incomplete or imperfect product that still needs to be polished by testing it in the real-world.
That doesn’t mean that you should release too early a buggy tool that fails at every turn, obviously. But vegetating in a never-ending design loop will only lead to missed opportunities, wasted resources, and lack of key feedback from users.
Keep Your Customers' Needs in Mind
I know that the informatics technology sector is a complex field, and that the AI niche is even more complicated. Developers, data scientists, and IT professionals need to understand each other quickly, and the unintelligible jargon just comes with the territory.
However, if you don’t know how to communicate value to your customers and audiences you are going to fail. Really, it’s just that simple — not every one of them is a geek.
Always communicating in an understandable way is just the tip of the iceberg. A product must be designed around then needs of your customers, and assuming that everybody will find “really simple to set up a DNS server for their domain” may prove to be a tragic error.
Functionality should never be prioritized over form: after all people who never saw your tool and have zero experience with it will need to use it, don’t they?
What We've Learned
There are a lot of pitfalls and obstacles to dodge if you want to avoid condemning your AI startup to bankruptcy before your journey has even begun. The list of failures is long, and includes some of the biggest names of the IT industry, as well.
Knowing how you can fail is vital to identify those challenges and skip through them as easily as possible.