4 High-Potential Sectors for AI and ML Startup Success
Today, the explosion of development in artificial intelligence (AI) and machine learning (ML) technology has created a market for which it appears there’s no limit. No matter the industry, if you name a reasonably-sized (or larger) company, there’s a good chance that they’re investing in AI and ML technology as a cornerstone of their strategic plans. With each passing day, it’s even becoming part of the small business equation, too. Here are four high-potential sectors for AI and ML startup success.
The takeaway is that there are as many ways for businesses to use machine learning as there are businesses. It’s the kind of burgeoning market that is perfect for fueling startup growth, and entrepreneurs have started to take notice. That’s why there’s been such a recent boom of startup activity in the sector – creating what many analysts are referring to as a 21st-century gold rush.
The problem is, like in the original gold rush in the late 1800s, there’s going to be a point where the majority of those rushing to stake their claims will see their odds of success dry up. That’s why it’s more critical than ever for entrepreneurs to understand which parts of the AI and ML space still have plenty of room for startup innovation, so they can mine the right vein and strike it rich.
Educational AI Systems
As AI and ML technology started their march into the business world, much of the attention paid to AI with respect to the education sector centered on producing the skilled worker’s businesses would need to operate their new technological platforms. Very little initial movement or investment went toward developing AI or ML solutions for the education sector.
In recent months, however, that has started to change. Education-focused platforms have been starting to roll out AI-powered tools and are increasingly viewing the technology as a game-changer for the industry. An analysis of spending by the education sector on AI and ML technology predicts that it will be the industry with the biggest spending growth by percentage through 2022. For an education-focused AI or ML startup, that’s a very encouraging sign.
Human Resources AI Technology
Another industry that’s been somewhat slow to adopt AI and ML technology is human resources (HR). The one exception has been in the adoption of applicant tracking systems (ATS) that use ML techniques to perform application screening for potential hires. That alone has spawned a cottage industry of AI-enhanced services meant to improve applicants’ chances of passing muster, as these machine-created resume examples should attest.
The thing is, the surge in ATS use is expected to be just a prelude to much wider adoption of AI and ML technologies in the realm of HR, with industry experts expecting adoption rates of the technologies to pick up significant steam in the coming years. That means it’s a great time to launch an HR-focused AI or ML startup now, to capitalize on the all-but-certain growth in the space.
AI-Powered Marketing Tools
As the world edges closer and closer to an always-on internet-connected reality with the emergence of IoT technology, businesses everywhere are coming to grips with the fact that there are more marketing channels to manage than ever before. The only feasible solution is to turn the bulk of the work over to AI-powered marketing systems, using ML to adapt and evolve marketing efforts over time.
Already, such tools are cropping up in all phases of the marketing industry, from social media management to content marketing and all points in between. That, however, is just the beginning. Businesses that have already seen how AI-influenced marketing decisionmaking can help them grow are now looking for ways to turn more of their marketing efforts over to AI-powered solutions. A startup that focuses on delivering an AI solution to enable real-time marketing automation at scale could find itself well-positioned for long term success.
Financial AI Solutions
When startups are seeking an AI or ML market with solid growth prospects, their best bet is to go where the money is – which in this case means to the financial sector itself. AI and ML technology adoption in the world of finance has been so swift and complete that it spawned the whole new business category of fintech. In particular, asset managers are already going all-in on the technology as are hedge funds, financial advisors, and the entire banking sector.
It’s also an industry that has almost inexhaustible resources to pour into worthwhile AI and ML technology, which bodes well for any startup that looks to build solutions for the industry. The size and scope of the sector mean that there’s a near-limitless number of opportunities to be had in the space – and they’re all there for the taking for any savvy entrepreneur who finds an innovative way to capitalize on them.
Fools Rush In
The bottom line here is that there’s no shortage of opportunities to be had for AI and ML startups, as long as they choose their markets carefully. It’s not a coincidence that analysts are starting to call this the AI gold rush – they’re doing it because the stampede of development will eventually lead to an oversaturated market that can’t sustain the number of startups that it is spawning.
When that happens, only the entrepreneurs that made it a point to work within sectors that have long-term growth prospects will see their startups survive. When the bubble bursts, it won’t be because interest in the technologies has waned, it will be due to two factors – a systemic need to cull underperforming members of the startup herd, and a round of consolidations that will see the best of the bunch scooped up by larger entities.
Startups in the above four sectors will stand a good chance of being part of the latter group. As for those in the former group, I suggest they do some research into the end of the last gold rush for some insight into their ultimate fate.