As per a recent Forrester survey, the majority of enterprises are investing in AI. While some companies are employing data scientists to spearhead innovation, the other half is providing AI-as-a-service through vendors. In this article at InformationWeek, Jessica Davis suggests how you should tackle this technology dilemma.
Getting Started with AI-as-a-Service
AI means machine learning, natural language processing, text analytics, and computer vision. These are made available by cloud vendors like Amazon, Google, Microsoft, and IBM through their algorithms and APIs. AI-as-a-service options are also available with smaller vendors. However, other company’s IT strategy might not be applicable to your organization. So, you must know what is suitable before investing in AI services.
Take One Step at a Time
Do a thorough research before making your first move. While Forrester says 55% of enterprises are yet to realize benefits from AI, Gartner projects that 85% of companies will fail to realize business outcomes by 2022 because of wrong analysis of data or algorithms.
Instead of Making a Holistic First Approach, Choose an Apt Use Case
In an interview with InformationWeek, Bern Elliot, Gartner VP and renowned analyst, affirms that it is wise to start small and with one use case to find out the impact of AI-as-a-service on your business. Technology should enable you to achieve those business objectives rather than be the goal itself. Contact the vendors that are already providing these services and have a trial run with an appropriate use case.
Prepare to Manage Quality Data
A Gartner 2018 survey reveals that only 4% of CIOs have implemented AI though 46% have developed execution plans. Moreover, 53% of enterprises think they do not have a proper setup to use the available data. You should employ appropriate skills or cloud providers that would collate good quality data, an important ingredient to experience success in these AI initiatives. Also, ensure that your in-house infrastructure and resources gain the ability to store and manage these data. Relying on external help prevents you from working independently.
Testing on Structured Data Shows Your Potential
Third-party AI-as-a-services will help you collect unstructured data, but it will not be specific to your business, opined Brandon Purcell, senior analyst at Forrester. However, if you apply machine learning to your structured data or pilot project, you will gain a lot of insight. Working on existing client purchases makes you identify the reasons behind their buying or not buying products. You could apply this to your present and prospective customers.
Go for Startup Vendors
Startups like Noodle.ai are coming up with innovative AI-as-a-Service offerings. As per Stephen Pratt, CEO of Noodle.ai, while technology giants like Amazon and Microsoft Azure are providing tool kits, his company is offering applications. The majority of organizations want to increase their brand value by utilizing AI and machine learning as Amazon has. Noodle.ai. is turning this increasing need for AI-as-a-Service to its advantage.
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