There is a talent shortage for every technical skill, and AI is no different. There are fewer people with AI skills but also fewer good AI opportunities. Many smart people are learning about this technology and want to work on your team—you just need to identify your gaps and begin recruiting or developing the people to fill them.
You won’t need to compete with Apple or Google for rock-star researchers if you sell the job opportunity to the right people. We know because we’ve done it for people like you.
The work is complex but your plan will be relatively straightforward. You need to do a few things to create your AI strategy:
Yes, machine learning models rely on data. But you can systematically improve your data assets deploying your initial models. Trying to “fix your data first” is almost always a bad idea. You don’t know what data you need and you’ll always have data problems anyway.
Instead of obsessing about data problems, identify your most valuable data assets and build your first AI project with them. We know it’s possible because we’ve done it for people like you.
Spending months on a cutting-edge research effort, buying an AI company, or building out massive infrastructure first is almost always a bad idea. We suggest starting with simple models … and a few data sources … with open source tools … running on AWS/Google/Azure … a small team … and a short timeline.
Make a bigger bet later after you get a quick win. We know because we’ve helped people like you begin scaling after a quick win.
The business press is obsessed with AI research breakthroughs. Conferences, vendors, and LinkedIn articles are bombarding you with confusing technobabble. Building machine learning models—even with deep learning or cutting-edge research—isn’t your biggest challenge.