Artificial intelligence (AI) has become an undeniable force for business transformation. It’s delivering significant business benefits today—and its potential to shape the future is even greater. The main challenge is finding a way to scale up AI innovations to deliver the greatest impact for your company—here’s how.
You need to upgrade IT systems before upscaling
Remember, AI is not about replacing staff but using and leveraging AI to work in conjunction with your staff. Make sure to establish a foundation that’s firmly in place before deciding to scale up your AI systems. Secure networks and make sure they are fair and unbiased. Test your systems regularly to ensure they are robust and reliable and work out any kinks early on. It’s also essential that systems are transparent and explainable to staff and clients.
Experiment with your AI services, developing and executing a metadata management framework for first, second, and third-party data. You can also play around with institutionalizing the AI development life cycle. Additionally, organizations in the scaling stage are often formalizing efforts to raise awareness of AI’s impact, upskilling and reskilling workforce, embracing non-traditional partnerships, and establishing policy frameworks, accountability, playbooks, and monitoring for AI governance.
Push the boundaries
Adopt a data-first, cloud-powered, hypothesis that generates business and tests your technology architecture. You want to establish trust on a larger community scale that sets you apart from competitors.
Staff development to meet AI needs
AI technology requires a broad range of specialized roles and skillsets beyond traditional IT skills; roles such as algorithm developers, machine learning engineers, and data scientists. Gaining access to high-quality talent with those unique skills can significantly impact AI project outcomes and help take your firm to the next level.
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