Simplifying AI Implementation for Maximum Impact

Simplifying AI Implementation for Maximum Impact

Measurements, dashboards, reporting, analytics; these are all things of our recent past. Everyone is now talking about Artificial Intelligence, Chatbots, etc., and they are so stressed out about missing the boat on something huge. Even this soon shall pass, as have so many recent topics like big data, data lakes, data integration, business analytics, etc. People still say the words, but they are now taken for granted as part of some more extensive data strategy that no one ever really seems to execute in a complete fashion for their company.

At this stage, the key message is to stop thinking about the technology behind these solutions and start thinking about the business use case instead. Managing a service, a production line, the financials, or any other business value driver will all require the ability to obtain data, detect conditions, report and alert on those conditions, then respond with the appropriate action. 

With that said, there are a variety of modern tools that allow this. Most of these tools are low cost with low barriers to implementation. Companies have already spent millions on dashboards, data lakes, reports, and other technologies. The cool part is all of these can still be used, and they are not redundant. However, they do need to be leveraged in new ways that add far more value. The hard part is not the technological next step. The hard part is finding a proper analyst that can establish use cases that align to the business value metric that then can be automated with tools like Google Vertex, CoPilot, Cinchy, and many other platforms. People must be reminded that they are not being asked to replace or shut down their lifelong work for the BI environment that they have tirelessly rolled out. They must take the next step and seek a bolt-on AI tool that will leverage all their hard work, pulling together the data. 

AI should not cause anxiety: AI is not overwhelming once you assign mini-use cases to it. You simply just pick a tool, implement it and enable customers to get access to it. Do not boil the ocean for an entire company's worth of data. Just do it one by one. The AI tools prefer that, and they can be much cheaper to implement. 

Last piece of advice, make sure you have a plan to “train” your bot with business rules that your customers care about. They do not train themselves, you have to write the business rules, as well as automated responses based on the conditions. (some tools require code, while others, like Google Vertex, use plain English) After you build the AI system, then just put access to your AI engine in places where your customers need it. (Websites, apps, text or Via MS Teams, etc.)

Aptimized helps you start with gathering data, then building business value drivers (KPIs), and then we help with the AI engines or automated alerting coming out of your dashboards or data lakes. We can help you build a roadmap to AI that will not cost millions. 

Everything starts and ends with the business case. In the coming weeks, we will be sharing more information, examples, and specifics about the business cases for these exciting new AI developments. 

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