AI Questions

Fielding questions to ask about AI adoption, implementation, insurgence

First of two parts

By Rick Dana Barlow

Artificial intelligence has gotten so popular and grown so exponentially that now its own "creators" are moving to control it and stuff the electronic genie back into the bottle. Honestly, the red flags were being waved for years so the architects behind the experiment chose to embrace color-blindness for a while — at least until now.

Beyond the "hallucinations" where AI simply makes stuff up or one firm's AI product invades another firm's AI product in a case of online sibling rivalry or family feud, earlier this year, Bottomline Paymode issued four Examples of warnings to heed about the technology initially designed to help you do your jobs more efficiently (until it starts replacing or eliminating the need for said jobs), which should lower bottom-line costs and hopefully generate top-line revenue.

Bottomline Paymode's warnings include the following:

Hyper-realistic emails that mimic customers and executives you trust
AI-generated voice calls that sound exactly like your finance leaders
Deepfake video meetings pushing for urgent payments
Real-time chat hijacking in tools like Teams and Slack

And that's just a sampling. AI also has been shown to manufacture crises to solve and some companies are forcing staff to use it, while others are trying to regulate heavily its use by staff. Meanwhile, around the same time, LexisNexis expounded on the expansion of digital access and the fact that "fraud tactics are becoming more sophisticated." Even Gartner Group in its "Future-Proof Your Supply Chain" survey showed that most supply chains are working toward deeper AI adoption and implementation.

It's enough for healthcare supply chain executives to consider adding a "risk or fraud prevention leader to their teams to facilitate wading through turbulent AI waters.

As a result, Leaders & Luminaries reached out to the Bellwether Community about two AI-salient topics: What are three questions to ask before implementing in supply chain operations and what they see as some of the red flags to know and warning signs to watch about AI in supply chain operations at their healthcare organizations. In this two-part story, L&L shares what Bellwether Hall of Famers, Ammer Honorees, Future Famers and Foundation Partners think about AI infiltration of digital, analog, financial and physical operations.

Reuben Philip, Future Famers Class of 2025, and director of product, Clarium

"AI can surface insights you didn't have before and increase efficiency through automation, but only if you're thoughtful about where and how you deploy it. With that in mind, here are three questions I'd ask.

"First: Are we automating the right process? Before bringing in any automation, we need to make sure the underlying process is sound. If we're doing something poorly, we don't want to automate that. Fix the process first, then automate best-in-class. Otherwise, you just get bad results faster.

"Second: What information is my team missing today that would help them make better decisions? This shifts the conversation from 'let's buy an AI tool' to 'let's figure out what our people actually need to do their jobs better' and then connect technology to that gap. The best implementations I've seen start with the problem, not the tool, and they bring the end users into the conversation early enough that the solution actually gets adopted.

"Third: What's the true cost of deploying this? Not just the license or token cost, but the total cost of ownership. Are we genuinely reducing cost and improving outcomes, or are we shifting expense from a labor-intensive process to an equally expensive technology-driven one? You want to measure the outcome before you implement and after, so you can prove the investment was worth it.

"What these questions say about leadership is that you're not chasing technology for its own sake. You're disciplined about outcomes, honest about costs, and focused on making your team better."

Ryan Burke, Future Famers Class of 2022, BLF Advisory Council, and vice president, Strategic Sourcing, Pandion Optimization Alliance

"What specific problem are we trying to solve? Is the data and governance set up to support AI? How will AI change workflows and decision-making for our staff?

"It is important to think about AI holistically and how the implementation will impact people. There will be change, so a focus on culture and bringing your staff along on the journey is critical."

Barbara Strain, Bellwether Class of 2021, BLF Board Chairman, and principal, Barbara Strain Consulting

"What processes need to be improved for efficiency?
"What signals need to be created and automated to prevent errors?
"How can help my staff interact with their customers?"

Vance Moore, Bellwether Class of 2019

"Will it provide the ability to ...

"expand the depth — go deeper with knowledge and insight?
"expand the width — process more work with the same of less staff?
"improve the quality — increase the confidence of decision making?

"What is the obsolescence time horizon of the tool?

"With the tech revision cycle advancing so quickly, it is extremely important to understand the real shelf life of the asset being considered. The world has switched from 'years-to-payback' to 'months-to-payback' for technology. As such, it is important to 'buy the organization' as much as buying the product — the product vision and the capabilities of the organization may be more important than the product you are buying — evolution of any AI product will evolve. You are not investing in a tool; you are investing in a partnership of insight.

"These above questions attempt to protect the organization and my area from wasting money and time on unproven promises. At the same time, it ensures that we are responsibly learning and adapting to the changing trends in the world. The only real constant ... is change. We must move forward but we need to do so with joint accountability with our trading partners."

Fred Crans, Bellwether Class of 2020, Board Outreach Ambassador, and healthcare business development executive, St. Onge Co., BLF Silver Sustaining Partner

"What problem are we trying to solve?
"What are the options for solving it?
"Why is an AI approach best?"

John Grande, senior vice president and general manager, Spend Management Services & Delivery, Vizient, and BLF Founding Sustaining and Educational Partner

"The first question is: Where are we creating friction today? AI should solve operational problems that slow organizations down, including manual reconciliation, poor visibility, disconnected workflows and delayed decision-making. If you cannot clearly define the operational pain point, AI becomes technology searching for a problem.

"The second question is: Can this improve execution at scale? Supply chain performance is shaped by thousands of decisions across procurement, inventory, utilization, contracting and payment workflows. The real value of AI is not producing more insight. It is helping organizations intelligently orchestrate decisions across procurement, inventory, contracting, utilization and payment workflows in ways that reduce friction and improve performance at scale.

"The third question is: Does this allow our teams to operate at a higher level? Most healthcare organizations are already stretched. AI should reduce administrative burden and exception management so people can spend more time on strategy, clinical alignment and performance improvement.

"To me, those questions reflect disciplined leadership. The best leaders are not chasing AI because it is new. They are focused on whether it creates measurable operational improvement."

Tina Vatanka Murphy, CEO, Global Healthcare Exchange LLC (GHX), and BLF Platinum Sustaining and Educational Partner

"First, what problem are we actually trying to solve, and will it meaningfully change an outcome that matters? AI is powerful, but it is not the strategy. In healthcare, the bar has to be higher because there is a patient at the end of every supply chain decision. Leaders need to ask whether AI will help solve a real operational problem: Can it identify disruption earlier, reduce manual work, coordinate decisions faster or improve the reliability of affordable care? At GHX, we think about AI through the lens of orchestration, moving beyond visibility and automation to help the industry act with greater speed, confidence and coordination.

Tina Vatanka Murphy, President and CEO, GHX, a Platinum Sustaining and Educational Sponsor of Bellwether League Foundation (BLF) and the Healthcare Supply Chain Leadership Hall of Fame (HSCLHOF) — Tina Vatanka Murphy

"Second, do we trust the data, the context and the decisions this AI will help produce? AI is only as strong as the data and context behind it. In healthcare supply chain, fragmented systems, inconsistent item data and disconnected workflows have limited progress for years. Leaders need to know whether the data is connected, standardized and governed, and whether the right guardrails are in place for transparency, accountability and human oversight. Trust matters because supply chain decisions can affect the continuity and cost of care delivery. At GHX, that is why we are focused on bringing together data, workflows and trading partners, so teams have the shared context they need to make better decisions and coordinate action with confidence.

"Third, are our people ready to not just use AI, but to lead with it? Technology transformation is ultimately human transformation. People need the skills, confidence and context to use AI in daily decisions and redesigned workflows. They also need to see it as a tool that empowers them, not something being done to them. The opportunity is not simply to automate work. It is to reduce the manual friction and exception handling that slows teams down, so people can focus on higher-value work that better supports clinicians and patients. At GHX, we see AI fluency as a critical leadership capability, not just a technical skill.

"Together, these questions reflect what responsible AI leadership requires: purpose, trust and courage. Purpose to stay focused on what truly improves healthcare. Trust in the data, the decisions and the way people are brought along. And courage to lead through ambiguity while keeping the patient at the center. Effective and responsible AI implementation is not just a technology decision. It is a leadership imperative."

Charlie Miceli, Bellwether Class of 2023

"Have we looked in the mirror and assessed our process competence?
"Do we have resources in supply chain, finance and IT to continuously support pursuit?
"Have we engaged with our leaders and front-line staff [about] AI and the potential for improvement and risks engagement required, truth telling and don't bring a knife to a gunfight?"

Maria Hames, partner, HealthCare Links, and BLF event partner

"With healthcare, I think data integrity is something we are still trying to clean, so for AI — I would want to know that the information we are feeding into any system within operations is trusted, accurate and if possible, standardized data.
"Be clear of what operational problem you want to solve. Multiple solutions and ability to be systemized so want to be clear to the objective of said solutions. Be strategic.
"Biggest time shortage is in clinical and support teams, so how can we make AI support the daily routines at this level of operations (not necessarily leadership/C-suite). Be team-focused."

Tom Redding, executive vice president, Healthcare, St. Onge Co., and BLF Silver Sustaining Partner

"Some of the key questions are:

"What specific decision or workflow are we improving and how will we measure success?
"Is our underlying data and process stable enough to support AI?
"Who owns the decision once AI is implemented and how do we maintain accountability?

"These questions indicate that it is important to prioritize intentionality, readiness and accountability."

Cody Fisher, president, Concordance Innovations (Surgence), and BLF Event Partner

"Before implementing AI, I think it is important to step back and ask a few very simple, but very honest questions.

First: What problem are we actually trying to solve and is it important enough to change how the system operates?

"Healthcare supply chain does not suffer from a lack of ideas or technology. It suffers from fragmentation, delay and inconsistency in execution. If the use case does not directly improve how decisions get made and acted on across providers, suppliers, and distributors, then AI is not the answer yet.

"Second: Is the data ready to support coordinated action, not just visibility?

"For years, the industry focused on getting data into one place. That helped awareness, but it did not fundamentally change outcomes. The real question now is whether data is structured, governed and shared in a way that allows organizations to operate together on a common set of facts. Without that, AI introduces more noise than value.

"Third: How will this capability show up in the actual workflow?

"If AI sits outside of the process, it will not scale. It has to live inside the day-to-day system where decisions happen, where trade-offs are made, and where execution occurs across multiple organizations. That is where real value gets created.

"I think those questions reflect a leadership approach that is grounded in reality. At Surgence, we believe strongly in innovation, but we are disciplined about how it is applied. The goal is not to deploy AI. The goal is to solve problems that the industry has not been able to solve on its own, and to do it in a way that scales across the network."