Olive Adds Clinc’s Conversational AI to Digital Healthcare Employee

Olive Adds Clinc’s Conversational AI to Digital Healthcare Employee

Combined technologies unlock conversational applications for an artificial intelligence solution that is uniquely positioned to improve patient satisfaction, boost efficiency, and reduce burnout and costs.

COLUMBUS OH, June 24, 2019 — While new technologies continue to transform the healthcare industry in unprecedented ways, administrative functions still burden the healthcare industry with 1 in every 3 dollars spent on administration. Olive, the company that introduced healthcare’s first digital employee, has joined forces with Clinc, another trailblazer in Artificial Intelligence (AI), to free up time and resources by adding conversational AI capabilities to its existing technology. The combined offering allows Olive’s digital healthcare employee to bring hospitals and health systems broader applications across revenue cycle, supply chain and other financial and operational departments.

This union expands the versatility of Olive by unlocking a broader range of capabilities like, vocal cognition to further help organizations eliminate bottlenecks, simplify administration, keep costs in check and ultimately improve the experience for patients.

Olive’s existing technology has put the digital healthcare employee to work on back-office functions spanning repetitive, time-consuming, and error-prone administrative tasks like claims processing, prior authorization statusing, and extracting patient data from EHRs. Working with Clinc, Olive will add vocal cognition to her current skill set to deliver a balanced mix of AI capabilities including RPA, CV, ML, and NLP/U to propel new opportunities for optimization and end-to-end automation for the AI-powered digital employee. This represents a pivotal milestone in the advancement of human and machine interaction in healthcare.

With these amplified capabilities, Olive is poised to create major improvements in healthcare, for example:

      • Comprehensive automations – Adding conversational AI to Olive’s skill set means that Olive can trigger and complete additional actions and connect steps in the information process that would have required human intervention before. For example, when a diagnosis code is incorrect or missing information on a claim, Olive will find the right data through a dialogue with patients, physicians and nurses.
      • Customer services in call centers –  Clinc brings its ability to take on high call volumes, understand freeform speech, maintain context, and simultaneously parse out inquiries and commands. This will be a breakthrough in areas like patient scheduling.

“This added technology helps us expand our breadth of AI by adding cognitive conversation to Olive’s capabilities,” said Sean Lane, CEO of Olive. “I envision Olive seamlessly interacting with patients and employees and bringing elevated comprehension into data analysis. We’re excited to be entering a new chapter in building a faster, more efficient, more effective healthcare system — the possibilities are endless.”

Today’s announcement comes on the heels of Clinc’s record $52M in its Series B funding round led by investors from Insights Partners, DFJ Growth, Drive Capital and Hyde Park Venture Partners. Drive Capital has also led previous funding rounds for Olive, and made their first investment in the organization in 2013. To date, Clinc has applied natural language understanding technology to a myriad of industries, including the financial, automotive, and food service sectors, but its latest round of funding is earmarked for expanding to new markets including healthcare.

“Healthcare impacts everyone in life-changing ways, and it is also a sector uniquely positioned to benefit from advances in efficiency and interoperability, enabled by AI,” said Jason Mars, CEO of Clinc. “We are advancing a powerful combination of task automation and voice-enabled interaction services that will help healthcare employees and patients to better understand, access and navigate the healthcare experience.”

“By bringing together two complementary, AI based technologies, the Clinc and Olive collaboration is poised to supercharge our digital workforce’s automation capabilities and shift the paradigm for how administrative work in healthcare is done,” added Lane.

To learn more about Olive and Clinc, visit www.oliveai.com and www.clinc.com.

About Olive

Olive is deploying the first digital workforce built specifically for healthcare, automating healthcare’s most robotic processes, so human employees don’t have to. Olive delivers healthcare organizations improved efficiency and speed while reducing costly administrative errors. Using the systems an organization already has in place, Olive operates as a digital employee intelligently routing information and data between systems automating repetitive, high-volume tasks and workflows, providing true interoperability. Olive is proud to partner with over 50 healthcare organizations made up of nearly 350 facilities in over 35 states across the country, ranging from some of the nation’s top health systems to small regional hospitals.  

About Clinc

Clinc is the leading global provider of conversational artificial intelligence technologies for companies like USAA, İşbank, Barclays and others. Headquartered in Ann Arbor, Michigan, the company was founded in 2015 by world-class AI and systems research professor at the University of Michigan. Utilizing the world’s most sophisticated natural language processing engine and the most advanced scientific discoveries in AI research, Clinc’s AI emulates human intelligence and is able to understand unstructured, unconstrained speech, and can interpret not only semantics and intent, but the underlying meaning of user queries.  Learn more at clinc.com.

Industry Insights from a Revenue Cycle Leader: Healthcare Tech Today and Tomorrow

Industry Insights from a Revenue Cycle Leader: Healthcare Tech Today and Tomorrow

As part of a new interview series with Healthcare Leaders across the country, the Olive team had the chance to interview healthcare consultant, Six Sigma Black Belt and Revenue Cycle expert April Langford about the biggest challenges facing healthcare today. Previous to starting AML Consulting, her own revenue cycle consulting firm, April was the VP of Finance at UPMC, a leading integrated healthcare delivery system. In addition to AML Consulting, she currently is co-founder and CEO of revcyclematch.com, an online platform that connects providers to their future business partners. revcyclematch.com reimagined Revenue Cycle management partnerships with a new platform that makes tedious marketing and client acquisition practices obsolete.

What are the biggest challenges you see leaders in Revenue Cycle facing?

Today, there are so many new regulations Revenue Cycle leaders have to react to, increasing federal, state and payer requirements, and the shift to value-based care has also come into play. The movement to value based care is more closely aligning the clinical and financial world in healthcare.

This expansion of Revenue Cycle into quality of care is interesting – Revenue Cycle leaders now find themselves responsible for health information management and care management, expanding their scope of management.

What role do you see technology playing in solving these challenges now, and five years from now?

As health systems grow and continue to accumulate multiple EMR, EHR and other disparate software, technology has to play a growing role in interfacing and connecting those systems so that organizations can operate as one integrated health system. Interoperability is important for the institution and the quality of care for consumers. At each point along the Revenue Cycle today, there are new technologies emerging to solve any given issue. Defining, selecting and implementing new systems is paramount to a smooth-running revenue cycle.

In 5 years, I foresee technology playing an even bigger role across the continuum of care. Being able to tie patient data together so that physicians and care-givers have a holistic view of a patient will increase the quality of care. What will the implications to billing be? Contracting and billing for value-based care will bring about increased complexities and new technologies to be able to manage billing and collections to ensure proper payment.


How does the shift to value-based care impact revenue cycle?

This has been an ongoing conversation, and as the shift to value-based care continues, it’s becoming more imperative for healthcare systems to master the evolving value-based payment and delivery models. It’s an evolution and it’s still rather new so organizations are just starting to model how to get there. Working to improve reimbursements, focusing on patient care and looking outside of the industry for innovative strategies to implement are a few areas where I see people focusing as the industry shifts to value-based care. Navigating that shift is one of the biggest challenges facing healthcare organizations today.

At Olive, we talk a lot about the concept of ShiftWork (shifting the mundane work currently done by employees to technology, so people can focus on work that requires a human touch) and how it will impact the current staff at health organizations. What higher-value activities do you see employees taking on as burdensome tasks are handed off to technology?

Honestly, it always seems like there is more work to do in the healthcare industry – often times even more work then there are people to complete the tasks. At many hospitals, there are a significant amount of open positions to fill at any given time.

I think the best approach to shifting work successfully is to talk to the employee first, because I’ve learned that if you understand what a person likes to do, it’s generally what they’re good at, as well. And when you have the focus to re-allocate employees time to more meaningful work, it gives them opportunities to grow and learn, ultimately helping them be more fulfilled.

Tell us about a person who mentored, inspired or impacted you during your career.

I have so many! I would say early on at UPMC, Don Riefner hired me not once, but twice, across different areas of the healthcare industry, so he spent many years influencing the trajectory of my career. And he was a great boss, extremely smart and thoughtful, never micro-managed and was always a calm voice of reason.

Can you share a piece of advice that someone gave you over the course of your career?

I’ve gotten a lot of great advice over the years, but the previous CFO and COO at UPMC was a great mentor and taught me something that always served me well. He taught me that I needed to be able to answer the who, what, when, where, and how before he accepted a recommendation. I needed to be 8 levels deep to achieve expertise. That’s always stayed with me as a truly valuable piece of career advice.

Subscribe to OliveReads here to read more about healthcare trends and the future of the industry.

Ethics in Artificial Intelligence

Ethics in Artificial Intelligence

As artificial intelligence and automation continue to advance industries from healthcare to financial services and beyond, there is a critical conversation happening around the ethical implementation of these technologies. At Olive, ethical considerations are at the center of everything we do.

Artificial intelligence already offers great promise to humanity – the possibilities range from improving operational efficiencies to predicting environmental threats to combating poverty. And it’s already proven to be a revolutionary tool in terms of optimizing burdensome, robotic processes currently done by humans on the administrative side of healthcare, proving AI can reduce the cost of care at a massive scale.

“That’s why we created Olive – to carve a trillion dollars out of the cost of healthcare, and increase the quantity and quality of human life. We think the best way to achieve that ethically is by scaling humans with AI. We’re able to accomplish so much more as a humankind with the assistance of AI in terms of providing better, more affordable healthcare to all,” – Sean Lane, CEO of Olive.

At Olive, we’ve already seen the workforce landscape fundamentally changing, because AI and automation are being used to supplement the work that our human employees don’t have time to get to. We call it “Shiftwork” because it’s the trajectory through which our jobs as human employees will evolve over time.

For the healthcare companies we’ve partnered with to deploy AI, we’ve already seen the landscape really start to change and human jobs begin shifting, as well. As their digital workforce starts to take over all of the robotic administrative work, it’s giving their humans the chance to handle tasks that require more of a human touch – like higher value claims and Quality Assurance, to name a few.

An ongoing conversation about the ethical implementation of AI stems from the fear and trepidation about whether or not AI will take human jobs. But that’s not what AI should be doing at all – AI is automating the most robotic tasks bogging down our most inundated industries, so humans can focus on more meaningful, human-centric initiatives such as patient care. For example, in Healthcare today, workers spend more time in front of screens than they do in front of patients, a real problem that AI can effectively solve.

“In the future, entire companies will be created with the intention of being staffed by a digital workforce. It will allow lots of new technology to emerge because the creation of new services and technology companies will be more accessible to more people, increasing entrepreneurship and expediting innovation. And Shiftwork means more than just new job opportunities and new tech companies, but possibly entirely new industries themselves.” – Lane

Another hot topic surrounding the ethics of AI is centered around governance. When healthcare organizations begin implementing AI, there are many things they must consider from how it will be used to how it will be managed. Which processes are the best candidates for automation? What security measures will be in place to maintain patient confidentiality?

How will you train your employees to refocus their time after AI frees them up for more meaningful work?

At Olive, we believe in the transformative power of AI and want everyone to experience its benefits, so we work hard to ensure it’s used responsibly. That’s why the questions above drive everything we do and shape the world we’re dedicated to building with artificial intelligence.  It’s also why we made Olive specifically for healthcare. Unlike other AI solutions on the market, Olive uses her healthcare-specific skills to address common bottlenecks – most importantly, she does it with unrivaled security measures built for healthcare, working seamlessly with common industry processes and technology.   

We also ensure our AI technology is only available to customers after understanding it’s potential use case. We also integrate our product development, sales and customer success teams in our considerations, allowing them to help drive the ethical use of artificial intelligence.  As the implementation of AI reaches critical mass, ethics will remain central to the conversation of how we “shift human work” from robot-friendly tasks to ones that require a human touch and human mind to improve the overall quality of human life.

From the Ground Floor: Intelligent Automation Best Practices

From the Ground Floor: Intelligent Automation Best Practices

In our time developing and building AI-based automations for our healthcare customers, we’ve identified a series of best practices. These practices have helped not only our automation engineers become more effective in their role, but practices that allow our customers to experience quicker value from the automations that we build for them. These practices allow us to build the ideal automation.

Whether you’re an automation engineer using an RPA solution, or a healthcare administrator considering partnership with an Artificial Intelligence as a Service provider like Olive, we think it’s important to highlight the business impacts that these practices can have. In this post, we’ll discuss 3 simple rules we apply to our automation process and the big impacts they have for the healthcare organizations that we serve.

 

Names Matter

Automations built on an intelligent process automation platform like the one we use to build for our customers consist of a series of logic-based rules and actions. These rules are configured through a web-based interface that then allows you to schedule the resulting automations to run on a defined cadence. While it may seem obvious the number one most important best practice when building automations is none other than – labeling each rule and action effectively.

Here’s why: Although these automations may initially be built by a single engineer, depending on the complexity, they will likely be supported over time by several others like fellow engineers or managers. If you work with an AI-as-a-Service vendor like Olive, you are supported by a Customer Success team, who monitors your automations regularly, optimizing and addressing failures when they occur. Automations are also generally not built overnight. In our case, the engineer becomes very familiar with their customer’s processes as they build them, allowing for iterations to occur as they become more familiar with each business process. Providing descriptive and easily understood labels on each of your rules and actions becomes paramount to ensure the success of the engineer, the supporting team, and the automation.

Try v. When

Error handling is important when building workflows to ensure failures are limited and more importantly – that when failures occur, you know why and can address quickly. This is key to ensuring that automations run smoothly and that human intervention is kept to an absolute minimum. After all, the promise of AI and automation is that it will do the repetitive, mundane tasks so that humans don’t have to. This is the promise we seek to deliver everyday to our customers.

Here at Olive, we have a trick for ensuring limited failures and quick error handling – Try and When statements. Here’s how it goes –  whenever you craft an action step in your process automation solution, you wrap it in a Try Wrapping your actions in a Try action ensures that your workflow does not fail, when it doesn’t need to. Here’s an example: When looping through patients, your workflow should ‘Try’ to do something for each patient. Now, when using the Try action, if there is a failure, you should set an error for the patient. Then have it reset to a known point, and have it continue on to the next patient. Now the workflow can continue on, and process the remaining patient list. This can cut the amount of time that your staff spends on specific tasks by 90+%, as they then only need to review and action the errors. The automation has taken care of the rest.

Many workflows will have common failures or optional scenarios that can be handled by a Try, however there are times when a “When” action is more suitable. Let’s say your workflow includes the automation of an action including a browser pop up window, but it does not always include the pop-up. This optional scenario can be addressed by wrapping the action in the proper logic – When. When using a When action, your automation will check the page for the pop up, but will not error out if no pop-up exists. It will simply move on to the next step.

Both of these tricks create a more efficient workflow that requires markedly less human intervention and support.

The Right Page

The first step of every automation should be a step to confirm that you’re on the right page within the given system. Before you start building out actions, before you do anything else, make sure you’re logged in and on the right page or file.

Why is this such an important step? By confirming along the way that you’re in the right place and on the right page, you greatly mitigate the risk of unintentionally doing the wrong thing in the wrong place. This is incredibly important, particularly in healthcare where Olive specializes, as we deal with Protected Health Information (PHI). If we entered PHI incorrectly, there could be grave legal and monetary repercussions.

While it adds a little extra weight to your automation, this step is worth it.

 

In Conclusion

Applying these three simple rules to automation builds can ensure efficiency and effectiveness in your workflow. While these are by no means all-inclusive of the practices we employ at Olive, they are foundational.

As experts in artificial intelligence and automation, our mission is to automate the most burdensome repetitive tasks in healthcare operations to reduce the cost of healthcare and ultimately improve the quantity and quality of human life. If you’re interested in learning more, connect with me on LinkedIn or contact us directly at olive@oliveai.com.

3 Benefits of Intelligent Process Automation for Your Business

3 Benefits of Intelligent Process Automation for Your Business

As a healthcare business professional, what are the biggest benefits of intelligent process automation to your business? If you have never considered that question, then you may be missing out on a myriad of potential benefits. The use cases for it in healthcare businesses are seemingly endless. Given that these technologies are ideal for processes that are high-volume and similar every time, the healthcare industry, with its wide variety of administrative tasks taking up valuable human time, is a prime candidate to leverage the power of automation.

In this article, we will dive into the details of some of the more common intelligent process automation technologies and 3 specific benefits intelligent process automation can bring to the healthcare businesses.

Explaining Process Automation & RPA

Before we dive into the specific benefits intelligent process automation can bring to your healthcare business, let’s dive into some of the nuts and bolts of process automation and RPA (Robotic Process Automation).

What is Process Automation?

Process automation is as simple as the title suggests—a process done automatically, not by a human being but by computer software that does not get tired, frustrated, and doesn’t need to sleep, drink or eat. Processes that become automated require less human involvement and certainly less human time to execute to its utmost efficiency.

Robotic Process Automation

One of the most apt examples of process automation and its benefit to a healthcare business is Olive’s Robotic Process Automation. Olive utilizes RPA to automate cyclical and time-consuming tasks that are rule-based and trigger-driven, freeing your staff from enduring countless hours of productivity that could have been better applied elsewhere in your business’ developments.

Now we’re sure when you hear the word “robotic”, you might immediately think about Rosie from the Jetsons, who performed menial house tasks as a robot made for a futuristic cartoon family from the Hannah Barbera cartoons, or, if you would like a more modern example, the Transformers who can transform into vehicles or other machinery assist human beings in various ways. Those aren’t the types of robots we’re talking about here.

Robots exist in other forms in technology, as detailed by Olive’s blog that also touches upon Robotic Process Automation. These technologies can consist of soft-bots, a computer program that acts on behalf of another user or program, or sensor networks, a group of spatially separated and dedicated sensors that monitor and record an environment’s physical conditions and organize the data collected at a vital location.

Oftentimes, RPA is considered the simplest form of Artificial Intelligence and is therefore used in business practices that require little skill. RPA specifically reaps benefits by giving skilled and specialized workers the opportunity to focus all of their attention on jobs that demand full human cognition and subjective decision making.

RPA vs Cognitive Automation

To put it simply, RPA takes a given set of inputs and produces a predictable, repeatable set of outputs. Not unlike a grunt or, aptly, a robot designed solely to follow instructions without freedom to think independent of its design, while other more advanced forms of intelligent automation, like cognitive automation autonomously improve in performance over time using machine learning. Machine learning is similar to humans gaining experience and figuring out more efficient ways to do things, but it is computers doing the iterating and learning instead of people. Both cognitive automation and RPA are beneficial tools for a myriad of  work processes ranging from simple rule-based processes (RPA) to more complex judgement-based processes (cognitive automation).

Benefit 1: Minimize errors

In order for your organization to fire on all cylinders with maximum profitability and productivity, the main things you have to invest on are: saving time and decreasing or outright eliminating the risk of errors. Why? As they say, time is money, and errors are setbacks that can be avoided if you leverage the benefits of process automation. Software like Olive can assist healthcare organizations, hospitals, and their staff to remedy a human-made mistake or miscommunication.

To help conceptualize and quantify the benefits, let’s consider a common healthcare business process: eligibility checks. Often times, eligibility checks require a human to manually transfer data from one system to another system, and then make a decision (or have one provided to them) about eligibility. This mundane, but important process is prone to typos and human error given the same data being entered multiple times into different forms and User Interfaces (UIs). It is no surprise then that technical errors cause 61% of initial medical billing denials for eligibility. By offloading this business process to  Olive, healthcare organizations can benefit from a high level of automation and repeatability in executing these tasks that minimizes susceptibility to human error and typos while still enabling businesses to use existing EHRs.

Benefit 2: Enhance problem-solving capacity

Automating processes in within your organization business doesn’t simply stop at the ‘cyclical and time-consuming tasks’. Enter, intelligent automation. Intelligent Automation is what is says on the tin: software that actually thinks for you, thus is the wonder of artificial intelligence and its role in intelligent automation. It isn’t simply mind-numbing repeatable tasks with minimum human monitoring, but actual problem-solving software that can actually think independent of human guidance and assist problem-solving on every level imaginable.

As best described in Olive’s article, 3 Trends to Consider Before AI Deployment, by 2026, intelligent automation might save the US healthcare economy a total of $150 billion annually according to a recent analysis by Accenture. It’s no wonder healthcare organizations are investing in intelligent automation, powered by AI software like Olive.

It doesn’t stop at healthcare, however, we’re seeing intelligent automation overtake the workplace and our daily lives all around us, from automated tellers at banks replacing human tellers, to booking hotel rooms online without needing to speak to a live person, to letting Google Maps navigate your next drive, just to name a few.

That being said, the most astounding example of intelligent automation, may indeed lie in healthcare. AI-assisted robots, as the article further explains, are aiding surgeons with medical decision support, image analysis and diagnostics, reducing and eliminating the potential of human error by joining human and machine in order to achieve the best results possible.

Benefit 3: Free clinical staff to work on clinical tasks

Another aspect of intelligent automation is cognitive automation software, which brings intelligence to information-intensive procedures. Cognitive automation is effectively the combination of Artificial Intelligence and Cognitive Computing. What sets cognitive automation apart is its performance of jobs that only human beings used to be able to do.

Often times, healthcare employees are bogged down with tedious administrative tasks that, while important to business, are inherently time-consuming and repetitive (e.g. insurance verification and data recording). These responsibilities can easily be outsourced to an RPA to execute in order to free up said staff so they can concentrate on tasks that humans excel at which require uniquely human skills like empathy and creativity (e.g. corresponding with patients, resolving more complex issues, etc.).

Part of cognitive automation is machine learning in order to have computing technology imitate human operations to complete tasks. While RPA is required to operate on a rule-base that limits its decision making, Cognitive automation expresses its artificial intelligence as a resource that learns as any human would in order to adapt and execute a job to its utmost efficiency, while becoming fatigued as a human being would, mind you.

Conclusion

In conclusion, in the field of healthcare alone, studies have found the increase in automation processing and data recording has decreased the in-hospital mortality rate by 15% and administrations that have adopted RPA have noticed a 200% return of investment in the first year of use according to this Olive white paper. Given the power of the technology and the myriad of high-volume tasks ripe for outsourcing to an intelligent automation solution in healthcare but it’s no wonder that intelligent process automation is a problem solver and driver of profitability-growth in the industry.

Dispelling 10 Myths about AI in Healthcare

Dispelling 10 Myths about AI in Healthcare

Depending on whom you ask, artificial intelligence has the potential to transform our economy, take our jobs, overrun the human race, or maybe even a combination of the three. While AI holds a lot of promise, it has also turned into a buzzword that is frequently misunderstood and misapplied to both our lives and our businesses. This is especially true in healthcare, where the promise of better patient outcomes is often overshadowed by the threat of compromised jobs or regulatory red tape. To help set the record straight on the current state of AI in healthcare, we’ve put together a list of the top 10 myths we hear most frequently.

1. There is just one type of AI.

In fact, AI is a blanket term that comprises multiple types of technology, including optical character recognition, natural language processing, and machine intelligence. At its core, artificial intelligence refers to technology that mimics sophisticated human processes in a way that makes it indistinguishable from a human. In this way, our definition of AI comprises not just computer vision and machine intelligence, but also Robotic Process Automation, which automates repetitive, rule-based tasks.

2. Automation will take away more jobs than it creates.

In fact, industry experts speculate that the opposite will happen. The reason why is because AI adoption won’t happen overnight––and when it does happen, it will primarily replace repetitive, lower-skilled jobs that don’t require human traits such as creativity or empathy. This won’t invalidate the need for a human workforce; on the contrary, it will provide an opportunity for jobs to become less menial and more thoughtful.

3. AI is first and foremost a way to cut costs.

Some organizations may turn to AI as a way to cut costs, but that also can be a side-effect of so many other benefits that automation can bring. AI can help organizations improve their efficiency and KPIs, reduce risk, improve employee satisfaction and retention, and more…while also cutting the costs associated with them.

4. AI’s ROI is difficult to calculate.

Because AI is still a new business tool and ROI may not be as cut-and-dry as it is for other, more conventional business tools, many mistakenly think that AI’s ROI is difficult to ascertain and they choose to avoid the perceived risk. However, the key to assessing ROI is to be diligent in measuring your current-day spend––not only in terms of salary and benefits, but also in terms of risk, of extra days in A/R, and any other subsidiary metrics that might be positively influenced by AI. If you choose to work with an automation vendor, they will be able to help you think through the metrics to consider when evaluating AI’s ROI potential. Then, they will help you understand how AI will impact those metrics so that you can generate buy-in from your team––while also feeling confident yourself.

5. AI is a magic fix for your business.

Many organizations think that AI is the “secret sauce” that will help them improve efficiency, reduce costs, and make their employees happier. And while all of those things can and do happen when AI is executed properly, those effects don’t come quite as easily as some may believe. Many AI companies sell insights, not action, to their clients, which means that your organization still needs to do the work in order for AI to have a tangible impact on your business.*

6. AI requires large amounts of data.

It’s true that more data is always better when it comes to artificial intelligence––after all, the more historical data you have at your disposal, the more opportunities you have to “train” an algorithm to act a certain way based on similar data in the future. However, depending on the task that you intend to automate, certain AI frameworks are flexible enough to work with limited subsets of data.

7. Only large companies with in-house IT teams can benefit from AI.

Even as recently as a few years ago, organizations needed to employ a sophisticated internal IT team in order to build, customize, and implement an AI model for their organization. Not so today. At Olive, we’ve seen AI successfully implemented everywhere from the nation’s largest health systems down to 17-bed rural clinics. If your organization is on the smaller size but is still interested in implementing AI, you might consider contracting with a third party to build and manage your automations rather than bringing on extra in-house support.

8. You can’t build AI in-house.

With the advent of cloud technology, it’s easier than ever to create data-intensive automations and harness the power of AI for your organization. This, coupled with robotic process automation and AI platforms, provides organizations with more of a “do-it-yourself” option so that they can harness the benefits of AI without having to rely on external consultants. If you’re trying to determine whether building in-house or hiring an external consultant would be more beneficial for your organization, ask yourself whether AI is a part of your organization’s core competency (meaning, it directly aligns with the value proposition with which you face the market). If AI is a key component to your organization’s value statement, you might want to consider if you have the skills in-house to execute on your workflows. If that isn’t the case for your organization (which it likely is not for a provider), outsourcing your workflow to an automation vendor will help you harness the same impact without straining your internal resources.

9. AI inherently possesses the ability to learn from itself.

AI “learns” by analyzing test data and determining which inputs translated to a given output. It will make its best educated guess based on the data it has at its disposal, but just like humans, it needs additional support to help it differentiate “right” from “wrong.” Often, humans will re-train the algorithm to help it refine its predictions.

10. AI is still too risky to apply to healthcare.

There are too many applications of AI in healthcare––from diagnostics to imaging to revenue cycle management––for reservations to pervade the entire healthcare industry. It’s true that in a clinical setting, AI can pose a greater risk because the stakes of being “right” are much higher. However, administrative AI is a burgeoning subset of healthcare AI that focuses on improving operational efficiency by optimizing data transfers between healthcare tools and systems. In our experience, the impact potential is undeniable: one of our customers was able to reduce their Days in Accounts Receivable by 34% in the first 180 days of using AI to manage their organization’s insurance eligibility checks.

Even though AI in healthcare still is a new concept and will continue to be defined over time, early signs indicate that the sky is the limit in terms of its potential to benefit an organization’s operational efficiency. If your organization is looking for ways to harness the power of automation and AI, reach out to us today to learn more.

*That said, Olive isn’t one of those “Brain in a Jar” companies (as we like to call them). Our AI solutions automate your repetitive and high-volume tasks so that you can reap the rewards of AI without having to sacrifice your team’s time and bandwidth.