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Summary Bullets:
- Successful AI projects take a village; project teams that include members from groups across the company are more likely to uncover the ‘what-if’ and ‘then what’ questions that are best addressed early.
- GlobalData’s 2018 survey found that close to 40% of businesses include all affected parties in decisions related to big data and analytics solutions.
We’ve all heard that not only are machine learning (ML) algorithms time-consuming to develop and train, but that they also need access to vast data lakes and specialized data scientists. With these requirements, it’s no wonder that businesses tend to focus on identifying the skilled IT-centric resources required for undertaking an AI deployment. But AI isn’t just the playground of data specialists, successful outcomes take a village. Project teams that include members from different organizations across the company are more likely to uncover the ‘what-if’ and ‘then what’ questions that are best addressed early on. HR, legal, finance, customer service, operations, and other business units have much to contribute to a successful AI deployment.
It is a best practice that has evolved over time. We’ve all heard of, and most likely experienced, the democratization of IT in the enterprise. What started as a device-focused trend with BYOD, largely for cell phones, tablets, and PCs, grew to also encompass applications. With cloud-based options making it easier to adopt industry-specific or collaborative solutions, lines of businesses took it upon themselves to find the tools they needed to get their jobs done more efficiently.
And it’s no different with big data and analytics solutions, such as AI. The number of organizations that include business units in decisions related to big data and analytics has been increasing steadily. In fact, GlobalData’s 2018 worldwide survey of over 3,200 businesses found that line of business involvement in decision making has grown substantially. As shown below, only 17% of respondents reported that IT was solely making the decisions, down from 27% in 2015. This means that today over 80% of organizations are broadening their decision-making teams, up from 73%% in 2015. Also, today close to 40% of businesses include all affected parties in decisions related to big data and analytics solutions?
When looking to adopt an AI solution, therefore, organizations need to pause and ask themselves if they have assembled the appropriate team. Most likely IT as well as departments together will be directly impacted by the new solutions under consideration. But what about business stakeholders that will be impacted indirectly? Or groups that may have insights to share, such as providing a legal or ethical perspective? Including input from lines of business as well as technology stakeholders at the onset will pay off in the long term.
IT Connection 