Everyone wants AI and machine learning. But with so much hype and so many options, how can you be sure you’re choosing the right tool? Choose poorly, and you could end up throwing millions away on a half-baked analytics system that’s barely better (or, even worse!) than human analysis.
Over the last decade, I’ve watched at least half a dozen “AI companies” fade away because they couldn’t deliver real ROI for their customers. And I’ve seen twice that many data analytics projects crash and burn because they chose the wrong AI/machine learning tools. Based on these observations and my own experience, I’ve identified these 4 key questions every enterprise needs to ask before they choose an AI partner.
What’s the benefit for me?
That flashy “AI company” you’re chatting with might look good, but how will they deliver real business value for you? The true promise of AI lies in targeted solutions to specific challenges. Even before you begin looking for a tech partner, make sure you’ve identified the data problem or question you’re trying to solve. For example, maybe you’re analyzing video gaming forum posts, and traditional sentiment analysis can’t figure out when “that sucks!” is positive or negative. Once you’ve identified a specific problem, insist that your potential partners demonstrate the real quantified value they will deliver. If they can’t talk ROI, go find someone else who can.
“A company should speak confidently and openly about the techniques they use to build machine learning models and develop AI systems.”
How experienced is this company?
Everyone wants AI and machine learning, but nobody wants to work with an unproven startup. That’s because the key to a successful AI system, one that delivers real benefits, lies in the implementation. Remember: while degrees and certifications are useful, they’re no substitute for real-world experience. Make sure the company you’re partnering with has a proven track record of building and implementing AI and machine learning systems that deliver real business benefits.
“If they can’t talk ROI, go find someone else who can.”
How much can they tell you about their own systems?
Ask your potential partner how their AI and machine learning systems actually work. What algorithms do they use? How do they handle hyper-parameter optimization? What’s their methodology for maintaining gold-standard test sets? The answers will be revealing. Do they speak with certainty, or are they unwilling to go into details? A company should speak confidently and openly about the techniques they use to build machine learning models and develop AI systems.
What’s the real cost?
A complex AI system that claims to solve huge problems may look good now, but you’ll be far behind your competition after it takes two years to implement. On the flip side, a cheap “one-size-fits-all” machine learning tool, even if it gets up-and-running in days, will cost you far more in the long run. At best, that “one-size” tool will return mediocre results. At worst, it’ll lead you to make bad decisions based on misleading data.
Take the time to do your research and find a company with sophisticated software tools and a practiced methodology for implementing them. You’ll get a better solution in less time, while saving thousands of dollars in unexpected fees, costs, and delays.
“…the key to a successful AI system, one that delivers real benefits, lies in the implementation.”
Choosing the right AI partner
I’ve written at length about the potential benefits and pitfalls of AI and machine learning. Fact is, a targeted, well-trained AI system can deliver huge benefits to your company or your own clients. By using these 4 questions to guide your search for a technology partner, you can realize that ROI while avoiding the common traps that doom so many companies and projects.
If you’d like to learn more about how Lexalytics specifically applies AI and machine learning to natural language processing, be sure to check out our Solution Profile 3 Pager.