AKASA has been nominated for the 2026 World AI Awards in the AI Denial Management category, recognising the healthcare technology company’s work in applying artificial intelligence to insurance claims, revenue cycle operations and the administrative challenges facing hospitals.
The nomination highlights a problem that rarely makes headlines but has serious financial consequences for healthcare providers. Hospitals can deliver treatment, submit claims and still spend weeks chasing payments because of missing information, coding discrepancies or insurance authorisation issues.
The World AI Awards recognises organisations, individuals, products and technologies contributing to the development and practical application of artificial intelligence across industries.
For AKASA, the focus is on helping healthcare organisations recover time lost to repetitive administrative work while improving the accuracy of the information behind insurance claims.
Tackling the costly problem of denied claims
Insurance claim denials remain one of the most frustrating parts of healthcare administration.
Research commissioned by AKASA in 2023 found that 76% of surveyed healthcare financial and revenue cycle leaders identified denial management among their most time-consuming responsibilities. Prior authorisation and insurance follow-up followed closely behind.
AKASA approaches the problem through AI-powered revenue cycle technology that helps organisations identify documentation gaps, improve coding accuracy and automate claim follow-up.
Its tools address different stages of the revenue cycle. Some help staff understand the status of submitted claims. Others examine clinical documentation and coding before bills reach insurers.
That distinction matters. Preventing an avoidable denial can be more efficient than appealing one after an insurer rejects payment.
AI automation delivers measurable results for hospitals
AKASA’s work with Montage Health, a nonprofit healthcare organisation in California, provides a practical example of its technology in operation.
The organisation implemented AKASA’s Claim Status automation to obtain information from insurance payers and return updates to its Epic electronic health record system.
According to AKASA’s published case study, the implementation eventually processed more than 5,000 claims per month, saved over 300 staff hours monthly and contributed to a 13% reduction in accounts receivable days.
These figures relate specifically to claim-status automation, rather than a measured reduction in denied claims.
Another deployment involved Nebraska-based Methodist Health System, where AKASA reported automating status checks for approximately 56,000 accounts over eight months. The company said the implementation saved more than 5,000 hours of work and removed 71.3% of accounts from staff queues.
The results illustrate how automating routine insurance follow-ups can free employees to handle disputes, complex claims and cases requiring human judgement.
Generative AI moves upstream to prevent billing errors
AKASA has also expanded into generative AI tools designed to improve the quality of claims before submission.
Its Coding Optimizer examines clinical records, identifies potentially missed codes and presents supporting evidence for coding specialists to review.
The company’s broader Prebill Optimization Suite brings together medical coding and clinical documentation improvement. Its AI models analyse patient information, including clinical notes, laboratory results and treatment records, to identify inconsistencies or missing documentation.
AKASA says it customises its models to individual health systems, accounting for their documentation practices, clinical services and coding requirements.
Rather than simply accelerating the appeals process, this approach addresses some of the errors that can cause claims to be denied in the first place.
The company has not established that every identified coding opportunity will prevent a denial or result in additional reimbursement.
Why AKASA’s approach matters for healthcare AI
Healthcare organisations face growing pressure to manage administrative costs without compromising the accuracy of patient records or financial reporting.
AKASA’s technology targets that pressure directly. Its combination of machine learning, generative AI and workflow automation helps revenue cycle teams process information that would otherwise require substantial manual review.
The significance of its work lies in connecting AI capabilities to measurable operational tasks, from checking insurance claim status to identifying documentation problems before billing.
Graham Cooke, President of the World AI Awards, said:
“AKASA’s nomination in AI Denial Management highlights an important opportunity for artificial intelligence in healthcare: helping hospitals reduce administrative burdens, improve claims processing and address the costly challenges associated with insurance denials.
“From automating claim status checks to improving medical coding and identifying documentation gaps before claims are submitted, AKASA’s work demonstrates how AI can support healthcare organisations in managing revenue cycle operations more efficiently. We congratulate AKASA on its 2026 World AI Awards nomination and look forward to following how these technologies continue to develop.”
AKASA joins organisations, researchers, entrepreneurs and technology developers being recognised through the 2026 World AI Awards.
The programme highlights the development and application of artificial intelligence across industries, from healthcare and financial services to manufacturing, transportation and enterprise technology.
AKASA’s nomination in AI Denial Management reflects a particularly practical application of the technology. Improving the way hospitals document care, process claims and follow up with insurers may not attract the attention given to consumer AI products, but it addresses a persistent operational challenge across healthcare.
Learn more about AKASA and its healthcare revenue cycle technology at akasa.com.
Discover the World AI Awards 2026, explore the nominees and learn more about the awards at worldawards.ai.
