As artificial intelligence and machine learning technology continue to advance the digital business landscape, you may ask yourself: Can I trust these systems to keep my brand reliable and to remain ahead of the competition?
Building trust in AI is critical to successfully adopting technology-driven strategies that push the envelope and drive efficiency in business operations. While some may be hesitant to fully integrate these technologies into workflows and put processes on autopilot, we have been using AI and ML technology for years. Google Maps, text editors and chatbots are all examples of AI technology that we use frequently—and most people don’t think twice about the accuracy or reliability of their applications.
Still, there are some genuine concerns about how much we can rely on these technologies as they become more advanced and hold more weight in successfully executing critical aspects of our businesses. So, how can companies continue to learn about these technologies to gain enough trust to adopt them on a larger scale?
Evaluating AI Performance And Processes
Trusting AI-driven technology for business starts with trusting its performance and processes. You may already know that a stable and trustworthy AI executes tasks using robust and up-to-date datasets compiled specifically for the industry or market in which it operates. The overarching concern then is how well and how quickly an AI can model data to make predictions appropriately.
The foundation of trust in AI lies in high-quality data. Without timely, tangible and accurate data, you can expect AI data modeling to fall short of your needs and expectations. Businesses can ensure high-quality datasets by vetting and minimizing the number of data sources used. Ultimately, data must be compatible with an AI’s systems and processes to remain accurate and viable.
Continue reading: https://www.forbes.com/sites/theyec/2022/05/18/can-you-trust-ai-to-help-navigate-todays-digital-business-landscape/?sh=46507fa9395f
Building trust in AI is critical to successfully adopting technology-driven strategies that push the envelope and drive efficiency in business operations. While some may be hesitant to fully integrate these technologies into workflows and put processes on autopilot, we have been using AI and ML technology for years. Google Maps, text editors and chatbots are all examples of AI technology that we use frequently—and most people don’t think twice about the accuracy or reliability of their applications.
Still, there are some genuine concerns about how much we can rely on these technologies as they become more advanced and hold more weight in successfully executing critical aspects of our businesses. So, how can companies continue to learn about these technologies to gain enough trust to adopt them on a larger scale?
Evaluating AI Performance And Processes
Trusting AI-driven technology for business starts with trusting its performance and processes. You may already know that a stable and trustworthy AI executes tasks using robust and up-to-date datasets compiled specifically for the industry or market in which it operates. The overarching concern then is how well and how quickly an AI can model data to make predictions appropriately.
The foundation of trust in AI lies in high-quality data. Without timely, tangible and accurate data, you can expect AI data modeling to fall short of your needs and expectations. Businesses can ensure high-quality datasets by vetting and minimizing the number of data sources used. Ultimately, data must be compatible with an AI’s systems and processes to remain accurate and viable.
Continue reading: https://www.forbes.com/sites/theyec/2022/05/18/can-you-trust-ai-to-help-navigate-todays-digital-business-landscape/?sh=46507fa9395f
