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AI Gaps
AI is changing work for many businesses, often saving time and cost, while also delivering better outcomes.
Yet, according to multiple studies, the primary factors hindering AI adoption are concerns about inaccuracy and data security.
Inaccuracy – to address, look for sources of data, and read/check everything.
Image by Data Science Dojo
Data security – opt out of your data being used for learning; also, check your data security measures regularly.
There are other elements as well, you should be aware of and keep in mind as you move forward with AI.
Mind the gaps to manage AI implementation
Responsibility – the potential gap between developers, application builders, and end users of AI models. Determine who is responsible for the model’s accuracy and possible harms.
Principles – businesses may enact responsible AI principles, but the teams building and deploying AI offerings often struggle to operationalize them. Ensure the teams building Ai applications have visibility into the data used to train models, have detailed information on and deploy how it may perform.
Goals – business goals need to be aligned; otherwise, gaps occur and anticipated results do not occur. First, make sure everyone is clear and aligned on why AI is being used in the first place: human augmentation or automation, operational efficiency or revenue growth, improved over human accuracy or lower cost, and other business goals. Also consider the role environmental sustainability plays in your business decisions.
Further, consider your own potential gaps:
Knowledge – not just your business knowledge, but that specifically of AI and what it can do for your business.
Patience – the initial result, even multiple iterations, often do not produce the desired outcome. You need to be patient and be more specific when you ask for clarification and provide more detailed information as a basis for going forward.
Remember, AI is not a substitute for human judgment. With AI, it is possible to check more sources and survey larger data pools. But it takes a human in the driver’s seat to decide what to look at, which information to include, and to check the accuracy of the output.
There is a need for AI within businesses. AI is affecting how firms think about career paths within their businesses. Already, there are reports of entry level jobs drying up, being done by AI. Ai expertise is increasingly important to how businesses operate, yet it is often difficult to attract “non-qualified” technical experts.
Please share other gaps you have identified and how AI has affected your business.
