Global IT research and advisory firm Info-Tech Research Group has published a new research-driven, step-by-step blueprint for implementing artificial intelligence (AI) solutions. As companies invest more into data and AI solutions, this timely guide, Drive Business Value With Off-the-Shelf AI, details a holistic approach to ensuring implementation success.
According to the new research guide, organizations are faced with multiple challenges when trying to adopt an AI solution, including data issues, ethics and compliance considerations, business process challenges, and misaligned leadership goals. When choosing the right product to meet business needs, organizations should know what questions to ask vendors to ensure they fully understand the implications of buying an AI or machine learning (ML) product.
In the blueprint, Info-Tech considers two main types of off-the-shelf AI products and solutions. The first type has AI/ML capabilities built into the product and might require training as part of the implementation. These solutions include AI-powered search engines, chatbots, and business intelligence or visualization tools.
“When choosing an AI-powered tool, there’s no need to reinvent the wheel and build a product you can buy,” says 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.”
The second type includes off-the-shelf ML/AI models, which are pre-built, pre-trained, and pre-optimized for a particular task. Examples include language models or image recognition models that can be used to speed up and simplify ML/AI systems development.
“When choosing an ML/AI model, using off-the-shelf models enables an agile approach to systems development,” explains Sedenko. “This allows for faster proof of concept and validations of ideas and approaches, but the model might not be customizable for your requirements.”
The research blueprint outlines how organizations can successfully implement an off-the-shelf AI solution. To ensure it delivers value, they must start with a clear definition of the business case and an understanding of their data. Info-Tech recommends having a solid grasp of the following considerations before considering an off-the-shelf AI solution:
- Business Goals – A clearly defined problem statement and business requirements for the tool or model will help organizations select the right solution to deliver business value even if it does not have the latest features.
- Data Requirements – Determining the expected business outcome defines data requirements for implementation. Organizations should know if they have the right data required to train and run the model.
- Skills Training – New skills and expertise are required through all the implementation phases, including design, build, deployment, support, and maintenance activities as well as post-production support, scaling, and adoption.
- Data Architecture and Infrastructure – A new tool or model will impact an organization’s cloud and integration strategy. It will need to be integrated with existing infrastructure, whether in the cloud or on-premises.
- Product, Tool, or Model Selection – Consider the questions organizations will need to ask when choosing a solution. These include questioning what model is powering the AI tool, the data that was used to train the tool, and what data is required to run the solution.
- Measure Impact on Processes – Business processes need to be defined or updated to incorporate the output of the tool back into the business processes to deliver value. IT governance and support processes need to accommodate the new AI-powered tool.
- Realize and Measure Business Value – Organizations should have a clear understanding of the value that AI will bring and measure revenue impacts and operational efficiency.
View and download the complete Drive Business Value With Off-the-Shelf AI blueprint.
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