Building In-House AI Teams
Hiring a team of experts was, and is, and an expensive endeavor. The average data scientist commands a six-figure salary in the US, and building an AI team often includes data analysts, data engineers, AI engineers, and more. This team would be tasked with building custom models, which is a lengthy, expensive experimentation process. All that payroll quickly adds up - not to mention the high costs of maintaining big data hygiene efforts. This is part of why the large majority of big data and AI projects fail. It’s just a large, complex, and expensive effort. AutoML solutions by the likes of Google, Microsoft, and Amazon can speed up the process of model building, but are still complex solutions that require the involvement of experts.
Enterprise Software and Consultants
Besides building in-house AI teams, companies could deploy enterprise software solutions like DataRobot and Alteryx. However, these are extremely pricey solutions, as DataRobot costs around $100,000 a year, with a standard contract length of three years. Given that cost, it’s a very hands-on solution, and companies will need to dedicate internal resources to making the most of these technologies. In short, implementing DataRobot could cost you half a million dollars, without no guarantees that it’s worth it. Traditional consulting firms like Deloitte will easily charge $1 million or more, which simply isn’t feasible for most SMEs.
This is where no-code tools like Akkio come in. Unlike building in-house teams, deploying enterprise software, or hiring consultants, no-code tools are a simple, cost-effective solution. With a free trial, you can see results right away, risking $0 instead of up to a million.
In short, no-code is the best way to use AI in digital marketing and gain a competitive edge.