An Overview on Why AI Projects are Failing to Meet ROI

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According to a recent report on AI success and profitability, more than 80% of the AI projects have a very high failure rate. Close to 90 percent of these projects report zero or negative ROI on their investments, leading to tremendous churn within the industry. Despite hiring top talent from the certified Artificial Intelligence Training in Warsaw, a large number of data science and AI teams never get to work on more than two product development assignments from the same company. Reason: failure to deliver on ROI that justifies their cost of hiring and employment. We can blame the failure to deliver, but there is more than one problem associated with this trend. In this article, we will explain the common mistakes made in the AI projects and how these mistakes impact the ROI outcomes from the projects.

Problem 1: AI’s boom is causing enormous volatility in the marketplace

The race to become an AI company is pressing organizations to look out for powerful technologies that can solve complex business problems. Unable to identify the actual outcomes of the AI project, the business leader often makes the biggest mistake of expecting too much too soon with too little.

  • Too much, in terms of results and profits
  • Too soon, in terms of product life cycle management (months reduced to weeks and days)
  • Too little, investing too little on talent and automation 

With AI companies shelling more than 25% of their resources on marketing and branding, the core product teams are left with barely anything to test and improve on the AI product. This is the biggest problem in the current AI market, as per the recent trends in analytics and inputs provided by senior data scientists.

Problem 2: AI teams are trying to re-engineer and repackage old products into new ones with little or no improvements whatsoever 

In the last two years, the world of Artificial Intelligence product development and marketing has seen a massive uptick in terms of delivery to the marketplace. We have witnessed a phenomenal growth in the number and varieties of AI projects that are built exclusively for a business to solve a unique problem in the system and its periphery. With thousands and hundreds of use cases arising from the AI world, it has become imperative for trainers involved with the top AI courses in India to judiciously analyze and identify the present and upcoming trends in the marketplace. 

But, the failure to come up with a unique proposition and marketing value cost businesses heavily in the AI world. Developing a new product or a solution requires new kinds of experimental and experiential strategies that can only be handled by a team of proficient product managers and AI analysts. These team members are masters at doing “trial and error” and AB simulations before coming up with near perfect AI solution that can be termed as truly unique and business centric in nature and positioning.

Problem 3: Have data but not enough “good data”

We are living in an era where success was earlier defined by Big Data mastery. But in the last 5-6 years, there has been a shift in the way data is utilized at the base level to develop a new AI product. AI engineers seek “good reliable data” that they can use to build an AI platform that delivers accurate, precise, and up to date results. Big Data can be useful, but when it comes to business ROI, nothing can replace the good returns of working in a hygienic environment involving accurately labeled data sets that are unbiased and fair in nature, in addition to being 100% reliable in terms of timeliness and historical proofing. In short, the lack of good data governance leads to what we now know as the garbage in and garbage out a scenario that cost heavy losses to AI companies.

Role of AI Training in overcoming ROI failures in an AI project

Team collaboration and communication could solve 60 to 70 percent of the imminent ROI problems that we witness in the world. By following good data governance, your success rate will jump by 2.5 to 4 percent.

The best solution that any AI team can come up with in this regard is “customization”. Top AI Courses in india are training professionals and students on building a resilient and sustainable AI lab that promises to deliver better productivity, superior lab testing results, lower operational costs, and improved scope of team collaboration.