AI-powered technology is powering up healthcare finance, reimbursement, revenue cycle, and risk. Five Kodiak leaders explain how to do it the right way.
Rarely does a day go by without a story in the healthcare trade press, or even in the mainstream media, about providers and payors using artificial intelligence-powered technology to battle each other over prior authorization or claims. In fact, it was Kodiak’s own Eric Boggs, Vice President, Revenue Cycle, who coined the phrase “bot wars” at a Kodiak Healthcare Summit several years ago to predict what was going to happen as AI’s brainpower and capabilities grew.
To the uninitiated, the stories are fun reads. They’re computer versus computer science fiction movies, healthcare finance style. But they mask what’s actually happening at the ground level in hospitals, health systems, and medical practices as providers deploy the latest AI tools to optimize their financial, revenue cycle, reimbursement, and risk management performance, often without strong AI governance in place to guide what they’re doing.
To help fill that gap, we put together a panel of five Kodiak leaders to ask them about Kodiak’s internal and external points of view on AI in healthcare finance, revenue cycle, reimbursement, and risk. The five leaders are:
We asked the panel 10 questions, and we captured their collective responses below.
Kodiak:Do customers ask you whether Kodiak has an internal or external AI POV?
Panel: Customers typically begin by asking how Kodiak is using AI, which makes sense given their need to understand our approach and capabilities. As we dig deeper, many conversations naturally expand into a bigger-picture dialogue about how AI can be applied responsibly and effectively across healthcare. That wider lens is where some of the most interesting and strategic conversations happen.
Kodiak:Does Kodiak’s AI POV apply to all lines of business—finance, reimbursement, revenue cycle, risk, etc.—or just a specific line of business, such as revenue cycle?
Panel: We get the impression in market conversations that our customers are looking to engage vendors who use AI in products and services, if only to communicate to their boards that they, our customers, are adapting to the future and doing so with AI. Since our customers are interested in how we, Kodiak, uses AI, we consider our AI POV as applicable to all lines of business.
Kodiak:What’s the rationale for Kodiak having an AI POV? Is it something you see happening in the market? Is it something you see in behaviors by providers and/or payors? Is it the proliferation of AI tools? Is it the lack of AI governance?
Panel: Because AI is so relevant in the news today, it seems to be the expectation of our customers that any company with a technology/data focus must be using AI in some way. We also think that heightened awareness of the data risks related to LLMs (large language models) has increased general AI awareness and questions regarding vendor use of AI.
Kodiak:How will having an AI POV affect the relationship between Kodiak and its customers? Will it be some sort of litmus test of who Kodiak does business with? Will it be used in contracts or in the development of new tools?
Panel: We anticipate that having an AI position will allow our customers to understand how we perceive both the risks and benefits of AI in the healthcare space. It also will help our customers understand how we engage with AI to provide our customers with the best possible products and services.
Kodiak:What are the pillars of Kodiak’s AI POV?
Panel: We have three pillars. One, AI must be data privacy & security first. Two, AI must be verifiable (not a black box). And three, AI must improve outcomes in some way, such as reducing errors or increasing efficiency, rather than be engaged merely as a means of saying “we use AI.”
Kodiak AI governance pillars in healthcare finance
AI must be data privacy & security first.
AI must be verifiable.
AI must improve outcomes.
Kodiak:What’s the rationale behind each of those three pillars? What’s the endgame for each?
Panel: The purpose of the first two pillars is privacy and security assurance, both of which are fundamental to the delivery of healthcare. The purpose of the third pillar is key to justifying the business case for use of any new technology. Without improvement, why bother?
Kodiak:Are these pillars carved in stone? Or will Kodiak be updating, revising, or revisiting them as AI capabilities in healthcare continue to expand?
Panel: We expect the three pillars will remain key for years to come, but certainly we could refine or expand them.
Kodiak:Where do you see AI in healthcare finance, reimbursement, revenue cycle, risk, etc., one year from now?
Panel: We see a proliferation of vendors in the market who claim to be using AI in their work, leading to confusion from buyers regarding how to differentiate the offerings. We expect that established vendors in the industry will have an advantage gaining a foothold with customers and using AI since they already have the foundation of trust and a relational track record with providers.
AI is becoming unavoidable in healthcare finance, but inevitability is not the same as readiness. AI should strengthen financial judgment, not replace it. Any AI that operates as a black box, bypasses controls, or can’t be explained under audit ultimately creates more risk than value.
Kodiak:Who’s leading the AI race right now, providers or payors?
Panel: Providers were quick to adopt the computer vision offered by Olive AI, but just as quickly recoiled from the word “AI” after Olive’s implosion. Providers are entering the AI space again and are engaging AI vendors, but we get the impression that payors have been more effective behind the scenes in using AI to delay claim payments and increase administrative burden for providers.
Kodiak:How do you see that race a year from now? Five years from now?
Panel: Providers have significantly more avenues of opportunity to use AI beyond improving financial outcomes. We expect AI to be explosive in the delivery of healthcare as well as on the business side of healthcare. We expect payors to focus their AI efforts on reducing the cost of care through rigorous enforcement of contract requirements and the funneling of patients toward low-cost providers. We’re not sure we see this as a race either payors or providers win or lose but rather a race toward different desired outcomes.
