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New Guide Offers Advice for Implementing Off-the-Shelf AI Solutions


A new resource guide has been announced for organizations that wish to implement AI and machine learning solutions. Info-Tech Research Group has published a guide offering a holistic approach for companies implementing data and AI offerings.

The Drive Business Value With Off-the-Shelf AI guide addresses some of the challenges organizations must deal with when adopting AI and big data solutions. These include business process challenges, misaligned leadership goals, data management issues and ethics and compliance considerations. The guide is designed to help organizations understand what questions to ask vendors so they will be aware of all the implications when purchasing an AI or machine learning solution.

There are two main categories of off-the-shelf AI offerings. The first type has AI and machine learning (ML) features built directly into the product, and therefore may require training during implementation. This type of offering generally includes chatbots, AI-powered search engines and business intelligence and visualization tools.

The second type of offering is an off-the-shelf AI/ML model, which is generally pre-built, pre-trained and pre-optimized for a specific task. This category may include language models as well as image recognition models for speeding up and simplifying AI systems development.

"When choosing an AI-powered tool, there's no need to reinvent the wheel and build a product you can buy," said Irina Sedenko, research director at Info-Tech Research Group. "However, when using off-the-shelf solutions, be prepared to work around tool limitations and make sure you understand the data and the model the tool is built on."

"When choosing an ML/AI model, using off-the-shelf models enables an agile approach to systems development," added Sedenko. "This allows for faster proof of concept and validations of ideas and approaches, but the model might not be customizable for your requirements."

Organizations must have a solid handle on a number of operational processes and goals before implementing an off-the shelf AI solution. These include their overall business goals as well as data requirements and data architecture and infrastructure. Skills training in advance of implementation is also important, as well as proper selection of the product, tool or model they wish to implement. Organizations should also take time to measure the impact the new solution will have on all business processes as well as to realize and measure the business value an AI-powered solution will provide.

Be part of the conversation about how AI is driving the Future of Work and both the customer and employee experience at Future of Work Expo 2022. The conference focuses on key elements of today's re-imagined workplace, not just for improving productivity, but also providing a better customer experience, through the intersection of technology and the human element. Future of Work Expo is part of the #TECHSUPERSHOW experience, taking place June 21-24, 2022 in Ft. Lauderdale, Florida.

Edited by Erik Linask
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