Healthcare organisations face a critical decision in adopting AI technologies. Should they develop AI solutions internally using models like ChatGPT and Claude, or should they partner with specialised healthcare AI platforms? This question has far-reaching implications as healthcare AI investment hits $32.3bn in 2024, projected to grow to $208.2bn by 2030. CX automation experts Ushur delve into the debate whether heatlhcare leaders should build or buy for AI solutions.
Building AI in-house appeals because of the promise of high returns and full control. However, internal projects often suffer from hidden costs—recruiting specialised talent can cost $1.8m-$3.85m in the first year, and initial timelines commonly extend beyond 12 months.
Regulatory complexity adds further challenges, with FDA approvals and HIPAA compliance requiring months of documentation and ongoing monitoring.
On the other hand, partnerships with established healthcare AI platforms provide faster deployment (3-6 months) and significant cost savings (60-80%). These platforms come with built-in compliance features and domain expertise that internal teams would take years to develop.
Data shows internal AI projects have a 30-40% success rate, while partnerships achieve 80-90%. The best approach for many healthcare leaders is a hybrid model—using platforms for immediate needs while building internal expertise over time.
Making informed, strategic build-versus-buy decisions enables healthcare organisations to focus on delivering patient care rather than navigating technology and compliance complexities. Embracing specialised AI partnerships is emerging as the most effective way to achieve scalable, compliant, and impactful healthcare AI solutions.
Read the full blog from Ushur here.
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