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Can AI and tech help streamline prior auths? What you need to know

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For many physicians, the prior authorization process is one of the most frustrating parts of practicing medicine. What was intended as a cost-control measure has become a significant administrative burden, taking time away from patient care and adding layers of complexity to routine clinical decisions. Physicians often find themselves spending hours navigating insurer requirements, tracking down documentation, and enduring delays that can negatively impact patient outcomes.

But artificial intelligence may be part of the solution.

We spoke with Brad Boyd of BDO Consulting about how new technologies are being developed to streamline and even automate parts of the prior authorization process. From reducing paperwork to identifying which procedures are likely to be approved, AI tools are showing promise in helping practices manage approvals more efficiently—and with less stress.

AI systems can now integrate with electronic health records to gather relevant clinical data, match it against payer criteria, and generate documentation in real time. Some platforms can flag missing information or alert staff to likely denials before they happen. Others can help determine when prior authorization isn’t required at all, eliminating unnecessary steps.

While not a silver bullet, AI offers the potential to reduce the time and cost associated with prior authorizations. And as regulations continue to push for greater transparency and speed in the process, many in the industry believe AI will play a critical role in helping practices adapt.



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Scotta taps Nextail AI powered technology to support retailer’s growth across stores and online — Retail Technology Innovation Hub

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“We’re committed to growing without compromising our values or customer experience. Partnering with Nextail allows us to proactively address operational bottlenecks and bring more precision and agility to our stock decisions. As we grow, it will be even more important to continue delivering on our brand promise of offering high-quality products at a fair price with an authentic story,” says Carlos Serra, Scotta CEO.

By leveraging Nextail, Scotta aims to boost sell-through and margins, reduce markdowns and stockouts, and improve strategic collaboration across teams through data driven insights and automation.

“Growing brands like Scotta prove that forward thinkers don’t need to wait to operate like larger industry leaders,” says Carlos Miragall, CEO and Co-Founder at Nextail. “By choosing to tackle key inventory challenges early on, they’re setting the foundation for sustainable and efficient growth, and we’re proud to be part of that story.”

RTIH AI in Retail Awards

RTIH, organiser of the industry leading RTIH Innovation Awards, proudly brings you the first edition of the RTIH AI in Retail Awards, which is now open for entries. 

As we witness a digital transformation revolution across all channels, AI tools are reshaping the omnichannel game, from personalising customer experiences to optimising inventory, uncovering insights into consumer behaviour, and enhancing the human element of retailers’ businesses.

With 2025 set to be the year when AI and especially gen AI shake off the ‘heavily hyped’ tag and become embedded in retail business processes, our newly launched awards celebrate global technology innovation in a fast moving omnichannel world and the resulting benefits for retailers, shoppers and employees.

Our 2025 winners will be those companies who not only recognise the potential of AI, but also make it usable in everyday work – resulting in more efficiency and innovation in all areas.

Winners will be announced at an evening event at The Barbican in Central London on Wednesday, 3rd September.  



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Virginia 911 call center implements AI technology to allow dispatchers to focus on emergency calls – KTVB

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Virginia 911 call center implements AI technology to allow dispatchers to focus on emergency calls  KTVB



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In test-obsessed Korea, AI boom arrives in exams, ahead of the technology itself

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